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Student Guide

SAP BusinessObjects XI 3.0 –

Universe Design

SAP BusinessObjects – Universe Design XI 3.0/3.1

2

Table of Contents—Learner’s Guide iii


C O N T E N T S

Lesson 1

Understanding BusinessObjects Universes Lesson introduction.......................................................................................................1

BusinessObjects universe concepts.............................................................................2

What is a universe?................................................................................................2

The Semantic Layer................................................................................................3

What type of database schema is used?..............................................................4

Classes and objects ................................................................................................5

How universes are used .......................................................................................5

Advantages of a universe .....................................................................................5

BusinessObjects Universe Designer components .............................................6

Starting Universe Designer ..................................................................................6

Using the Quick Design Wizard..........................................................................8

Using Universe Designer module commands ..................................................8

Saving and exporting a universe.......................................................................11

Importing a universe ..........................................................................................12

Universe file names as identifiers .....................................................................12

Saving a universe definition as PDF .................................................................13

Giving all users access to a universe ................................................................13

Activity: Viewing a universe in Designer.........................................................14

The Universe Development Cycle.............................................................................15

The Universe Development Cycle process ......................................................15

Preparation phase ................................................................................................16

Analysis phase......................................................................................................17

Planning phase.....................................................................................................19

Implementation phase.........................................................................................20

Implementation phase 1: schema design..........................................................20

Implementation phase 2: building the universe..............................................22

Testing phase........................................................................................................23

Deployment phase...............................................................................................24

Updating/maintenance.......................................................................................25

Prepackaged solutions.........................................................................................25

Activity: Planning a universe.............................................................................26

Quiz: Understanding BusinessObjects universes...................................................27

Lesson summary..........................................................................................................28

Lesson 2

Creating the Course Universe Lesson introduction.....................................................................................................29

The course database and universe ...........................................................................30

iv Universe Design—Learner’s Guide


Course database description...............................................................................30

Creating the universe .................................................................................................32

Creating a new universe......................................................................................32

Defining universe parameters ...........................................................................33

Identifying the universe......................................................................................33

Setting the database connection.........................................................................34

Data access drivers...............................................................................................34

ODBC connection drivers...................................................................................36

More about connection types.............................................................................38

Viewing, modifying, and deleting available connections..............................38

Universe parameters............................................................................................40

Definition tab........................................................................................................41

Summary tab.........................................................................................................42

Strategies tab.........................................................................................................43

Controls tab...........................................................................................................44

SQL tab...................................................................................................................44

Links tab................................................................................................................45

Parameters tab......................................................................................................46

Activity: Creating a new universe and defining its connection....................47

Quiz: Creating the course universe...........................................................................48

Lesson summary..........................................................................................................49

Lesson 3

Building the Universe Structure Lesson introduction.....................................................................................................51

Populating the universe structure.............................................................................52

Designing a schema ............................................................................................52

Schema design and the universe creation process..........................................52

Adding tables .......................................................................................................52

Manipulating tables in the universe structure.................................................55

Activity: Populating the universe structure.....................................................58

Defining joins in a universe........................................................................................60

About joins and SQL WHERE clauses .............................................................60

Creating joins........................................................................................................61

About join properties...........................................................................................63

Editing the join expression .................................................................................64

Using the Join SQL editor ..................................................................................64

Detecting joins .....................................................................................................65

Setting join cardinalities......................................................................................66

About cardinality.................................................................................................66

Setting cardinality manually or with the automatic detection tool..............67

Displaying cardinalities ......................................................................................69

Detecting cardinality automatically..................................................................71

How is cardinality detected?..............................................................................71

Detect cardinality for all joins.............................................................................72

Best practice for setting join cardinality ...........................................................73

Join types ..............................................................................................................74

Equi-joins ..............................................................................................................74

Table of Contents—Learner’s Guide v


Outer joins ............................................................................................................75

Theta joins.............................................................................................................77

Shortcut joins........................................................................................................78

Self-restricting joins .............................................................................................79

List Mode...............................................................................................................81

Checking integrity ...............................................................................................83

Activity: Defining joins in a universe................................................................83

Quiz: Building the universe structure......................................................................86

Lesson summary..........................................................................................................87

Lesson 4

Creating Dimension Objects Lesson introduction.....................................................................................................89

Classes and objects ......................................................................................................90

Classes....................................................................................................................90

Objects....................................................................................................................91

Creating classes and objects ......................................................................................93

Creating classes....................................................................................................93

Automatically creating classes and objects from a table ...............................95

Defining a new object as a detail object............................................................95

Working with classes and subclasses................................................................96

Editing the object properties...............................................................................97

Edit Properties: Properties................................................................................100

Edit Properties: Advanced................................................................................101

Edit Properties: Keys..........................................................................................102

Edit Properties: Source Information................................................................103

Copying and pasting objects.............................................................................104

Find and replace ................................................................................................104

Checking object integrity .................................................................................105

Viewing parent tables........................................................................................106

Testing objects ....................................................................................................107

Activity: Creating and testing classes and objects.........................................107

Quiz: Creating dimension objects...........................................................................113

Lesson summary........................................................................................................114

Lesson 5

Creating Measure Objects Lesson introduction...................................................................................................115

Measure object concepts...........................................................................................116

Defining measure objects .................................................................................116

How a measure infers SQL ..............................................................................116

The Query Process .............................................................................................118

Aggregation at SELECT level...........................................................................119

Aggregation at projection level........................................................................119

Setting selection and projection aggregates...................................................120

Creating measure objects..........................................................................................121

Measure objects .................................................................................................121

vi Universe Design—Learner’s Guide


Testing measure objects.....................................................................................122

Activity: Creating and testing measure objects.............................................123

Delegated Measures..................................................................................................126

What is a delegated measure?..........................................................................126

How does the delegated measure work?........................................................127

Using a delegated measure as a weighted average.......................................127

Best practices for using delegated measures..................................................130

Activity: Creating and using a delegated measure.......................................130

Quiz: Creating measure objects...............................................................................132

Lesson summary........................................................................................................133

Lesson 6

Using Lists of Values Lesson introduction...................................................................................................135

Creating a list of values ............................................................................................136

What is a list of values?.....................................................................................136

Using a list of values (LOV)..............................................................................136

Working with LOVs in Universe Designer ...........................................................137

Associating an LOV with an object..................................................................137

Setting options for generating LOVs ..............................................................139

Editing the LOVs for the entire universe .......................................................141

Adding data to the list by adding columns ...................................................142

Creating a cascading LOV .......................................................................................143

Setting up a cascading LOV ....................................................................................143

Activity: Using a cascading LOV in Web Intelligence Rich Client.............145

Quiz: Using lists of values .......................................................................................147

Lesson summary........................................................................................................148

Lesson 7

Resolving Loops in a Universe Lesson introduction...................................................................................................149

Understanding loops ................................................................................................150

Recognizing loops..............................................................................................150

Problems caused by loops ................................................................................150

Loops in a universe schema and not in the database ...................................151

What is the loop doing?.....................................................................................151

Resolving loops ..................................................................................................152

Resolving loops using aliases ..................................................................................153

About aliases ......................................................................................................153

Detecting loops and inserting aliases .............................................................153

Redefining objects .............................................................................................156

Listing and renaming aliases ...........................................................................157

Choosing which alias method to use ..............................................................157

Resolving self-join loops using aliases............................................................157

Resolving loops using shortcut joins .....................................................................160

Using a shortcut join..........................................................................................160

Activity: Resolving loops with aliases............................................................161

Table of Contents—Learner’s Guide vii


Resolving loops using contexts ...............................................................................164

About contexts....................................................................................................164

Detecting and creating contexts ......................................................................167

Creating objects for each context ....................................................................170

Editing a context ................................................................................................170

Testing contexts .................................................................................................171

Updating contexts .............................................................................................172

Activity: Resolving loops using contexts........................................................173

Quiz: Resolving loops in a universe .......................................................................178

Lesson summary........................................................................................................179

Lesson 8

Resolving SQL Traps Lesson introduction...................................................................................................181

Understanding SQL traps and universes ..............................................................182

About SQL traps ................................................................................................182

Detecting and resolving chasm traps .....................................................................183

Chasm traps .......................................................................................................183

Detecting chasm traps ......................................................................................184

The chasm trap scenario ...................................................................................184

Resolving chasm traps ......................................................................................186

Using multiple SQL statements for each measure to resolve chasm

traps......................................................................................................................187

Drawbacks to the multiple SQL statements for each measure

method.................................................................................................................189

Using contexts to resolve chasm traps ...........................................................190

Activity: Resolving chasm traps.......................................................................191

Detecting and resolving fan traps ..........................................................................195

Fan traps .............................................................................................................195

The fan trap scenario ........................................................................................196

Resolving fan traps.............................................................................................197

Using aliases and contexts to resolve fan traps.............................................198

Solving a fan trap with two tables in a one-to-many relationship..............200

Avoiding fan traps altogether .........................................................................201

Activity: Resolving fan traps............................................................................203

Quiz: Resolving SQL traps ......................................................................................207

Lesson summary........................................................................................................208

Lesson 9

Applying Restrictions on Objects Lesson introduction...................................................................................................209

Restricting the data returned by objects ................................................................210

Defining data restrictions .................................................................................210

Methods of restricting data in end-user modules ........................................211

Drawbacks to applying restrictions to objects ..............................................212

An alternative to applying restrictions to objects .........................................213

Restrictions using condition objects ...............................................................215

viii Universe Design—Learner’s Guide


Applying restrictions using the tables button ...............................................216

Applying each type of restriction ...................................................................218

Activity: Applying restrictions.........................................................................218

Quiz: Applying restrictions on objects ..................................................................221

Lesson summary........................................................................................................222

Lesson 10

Using @functions with Objects Lesson introduction...................................................................................................223

Using @functions.......................................................................................................224

Defining @functions ..........................................................................................224

@prompt .............................................................................................................224

@prompt syntax .................................................................................................225

@select..................................................................................................................227

@where.................................................................................................................229

@aggregate_aware..............................................................................................233

Activity: Using @functions...............................................................................233

Quiz: Using @functions with objects .....................................................................235

Lesson summary........................................................................................................236

Lesson 11

Using Hierarchies Lesson introduction...................................................................................................237

Understanding hierarchies and universes ............................................................238

Hierarchies..........................................................................................................238

Working with hierarchies ........................................................................................240

Default hierarchies ............................................................................................240

Custom hierarchies............................................................................................243

The effect of custom hierarchies on default hierarchies ..............................245

Time hierarchies ................................................................................................247

Testing automatic time hierarchies .................................................................250

Advantages and disadvantages of automatic time hierarchies ..................250

Time hierarchies based on database functions .............................................251

Advantages and disadvantages of database function time

hierarchies...........................................................................................................252

Table-based time hierarchies ...........................................................................252

Advantages and disadvantages of table-based time hierarchies ...............254

Activity: Using hierarchies................................................................................254

Quiz: Using hierarchies ............................................................................................256

Lesson summary........................................................................................................257

Lesson 12

Derived Tables and Indexes Lesson introduction...................................................................................................259

Table of Contents—Learner’s Guide ix


Using derived tables .................................................................................................260

What is a derived table?....................................................................................260

Adding derived tables ......................................................................................260

Derived tables as lookup for multiple contexts.............................................261

Nested derived tables........................................................................................262

Creating nested derived tables.........................................................................262

Activity: Adding derived tables.......................................................................264

Applying index awareness ......................................................................................266

What is index awareness?.................................................................................266

Setting up index awareness..............................................................................266

What happens behind the scenes?...................................................................268

Avoiding joins in tables.....................................................................................270

Multiple foreign key entries.............................................................................271

SQL Editor dialog box ......................................................................................273

Using an index awareness WHERE clause.....................................................273

Activity: Setting up index awareness..............................................................274

Quiz: Derived tables and indexes ...........................................................................275

Lesson summary........................................................................................................276

Appendix A

Relational and Dimensional Modeling Understanding the metadata...................................................................................283

Data warehouses........................................................................................................284

Online Transactional Processing systems..............................................................285

Data Marts...................................................................................................................286

Dimensional Modeling..............................................................................................287

Appendix B

Alternative SQL syntaxes for other RDBMS SQL syntaxes for other RDBMS...............................................................................289

Answer Key Quiz: Understanding BusinessObjects universes.................................................295

Quiz: Creating the course universe.........................................................................296

Quiz: Building the universe structure....................................................................297

Quiz: Creating dimension objects...........................................................................298

Quiz: Creating measure objects...............................................................................299

Quiz: Using lists of values .......................................................................................300

Quiz: Resolving loops in a universe .......................................................................301

Quiz: Resolving SQL traps ......................................................................................302

Quiz: Applying restrictions on objects ..................................................................303

Quiz: Using @functions with objects .....................................................................304

Quiz: Using hierarchies ............................................................................................305

Quiz: Derived tables and indexes ...........................................................................306

Agenda—Learner’s Guide xi


Understanding BusinessObjects Universes—Learner’s Guide 1


Lesson 1

Understanding BusinessObjects Universes

Lesson introduction To design effective and efficient universes for your business users, you need a general

understanding of their structure and application. It is also important to become familiar with

the process involved in building a successful universe.

After completing this lesson, you will be able to:

• Define BusinessObjects universe concepts

• Use the Universe Development Cycle

2 Universe Design—Learner’s Guide


BusinessObjects universe concepts This lesson gives a general introduction to universes.

After completing this unit, you will be able to:

• Describe a universe

• Describe BusinessObjects Universe Designer interface elements

• Save, export and import universes

What is a universe? The BusinessObjects universe is the semantic layer that isolates business users from the technical

complexities of the databases where their corporate information is stored.

For the ease of the end user, universes are made up of objects and classes that map to data in

the database, using everyday terms that describe their business environment. This means that

by using a universe to create a query, users can retrieve exactly the data that interests them

using their own business terminology.

A BusinessObjects universe is a file that contains the following:

• Connection parameters to a single data source.

• SQL structures called objects that map to actual SQL structures in the database such as

columns, tables, and database functions. Objects are grouped into classes.

• A schema of the tables and joins used in the database. Objects are built from the database

structures that you include in your schema.

Note:

You associate data to universes by mapping to a data source. Data is not stored in the .unv file.



End users select the universe they are authorized to access in order to build queries. They build

a query by selecting objects defined in the universe, and in this way, they are not required to

see or know anything about the underlying data structures in the database.

BusinessObjects Designer XI Release 2 gives universe designers the ability to build universes

from OLAP and metadata sources. It also offers the ability to build universes against Unicode

databases and run reports that display data in one of many available languages.

BusinessObjects Universe Designer XI 3.0 offers the following additions:

• Personal file universe creation wizard - universes have supported access to csv and xls files

through generic ODBC.

• JavaBean - the JavaBean driver provides the ability to expose data returned by a JavaBean

class and model it through a universe.

• Java database connectivity (JDBC) - access to a standard JDBC connection and JDBC support

to all major sources is provided.

• Microsoft Analysis Services 2005 - Microsoft Analysis Services 2005 support for OLAP

universes is provided.

Universes are used to query the database The role of the universe is to present a business-focused front end to the SQL structures in the

database. The data used in a universe schema depends greatly on the end user requirements.

It needs to provide an easy-to-use interface for end-users to:

• Run queries against a database

• Create reports

• Perform data analysis

The Semantic Layer

Universe Designer can be seen as the tool which creates the Semantic Layer.

Metadata is imported into Universe Designer, and then the tables structure can be changed

(using Derived Tables) or data can be changed before it is presented to the user (by manipulating

objects). However, the source data essentially remains the same. This is what separates the

Semantic Layer from Data Integrator.

Data Integrator is an ETL Tool which can change the structure of the data, and also cleanse it

from data errors.

The semantic layer is also used for the Performance Management product suite. When building

a Dashboard Manager or Set Analysis Metrics universe, the approach is slightly different to

creating a normal ad hoc reporting universe:

• the Dashboard Manager or Set Analysis Metrics universe requires to have custom tags

embedded within it (which can be considered a form of code), which are used by Dashboard

Manager and Set Analysis products

• a mandatory self join is placed in the Dashboard Manager or Set Analysis Metrics universe

to ensure that calculated metrics apply to one time period granularity in a time dimension,

for example, daily, weekly, or monthly.



• custom filters are placed into the Dashboard Manager or Set Analysis Metrics universe to

be able to compare sets (Joiner Filter, Leaver Filter, and so on), and to build metrics.

This is why it is advisable not to use the same ad hoc reporting universe as your Dashboard

Manager or Set Analysis Metrics universe.

Information on building a Dashboard Manager or Set Analysis Metrics universe can be found

in the Creating universes for use as metrics chapter of the BusinessObjects XI 3.0 Designer's Guide.

What type of database schema is used? Before developing a universe you must familiarize yourself with the underlying data. Which

type of database schema is going to be used for the universe? Will this be a Data Warehouse

model, an Online Transactional Processing system (OLTP), or a Data Mart? How can you best

implement the metadata into a universe schema to meet the end user requirements?

Star Schemas

The star schema is the simplest data warehouse schema. It is called a star schema because the

diagram resembles a star, with points radiating from a center. The center of the star consists

of one or more fact tables and the points of the star are the dimension tables.

A star schema consists of fact tables and dimension tables:

• Fact tables

A fact table typically has two types of columns: numeric facts and foreign keys to dimension

tables. Facts can become measure objects in a BusinessObjects universe file.

• Dimension tables

Dimension tables contain the qualitative descriptions that can be applied to the facts.

Hierarchies may also be built into dimension tables. Dimension table data can become

dimension or detail objects in a BusinessObjects universe file.

Snowflake schemas The snowflake schema is a variation of the star schema used in a data warehouse. It is more

complex than the star schema because the tables which describe the dimensions are normalized.



Data modeling

The traditional entity relationship (ER) model uses a normalized approach to database design.

Database normalization is a technique for designing relational database tables to minimize

duplication of information and to avoid data anomalies. Higher degrees of normalization

typically involve more tables and create the need for a larger number of joins, which can reduce

performance.

Denormalization is the process of taking a normalized database and modifying table structures

to optimize the performance by keeping a minimum relationship between tables; one dimension

table versus one fact table. Another method is to use prebuilt summarized data in the schema.

Classes and objects A universe contains the following structures:

• Classes

• Objects As the universe designer, you use Universe Designer to create objects and classes that represent

database structures. The objects you create in the universe must be relevant to the end user‟s

business environment and vocabulary.

Classes A class is a logical grouping of objects within a universe. It represents a category of objects.

The name of a class should indicate the category of the objects that it contains. A class can be

divided hierarchically into subclasses.

Objects An object is a named component that maps to data or derived data in the database. The name

of an object should be drawn from the business vocabulary of the targeted user group.

How universes are used A universe defines the connection to the database. By selecting a universe when creating new

documents or editing existing documents, the business users automatically receive access to

the data. The access to data, in turn, is restricted by the objects that are available in the universe.

These objects have been created by you, the universe designer, based on the needs profile for

a defined user group.

Advantages of a universe The advantages of a universe are:

• Only the universe designer needs to know how to write SQL and understand the structure

of the target database.



• The interface allows you to create a universe in an easy-to-use graphical environment.

• Data is secure. Users can see only the data exposed by the universe. Users can only read

data, not edit it.

• The results are reliable and the universe is relatively easy to maintain.

• Users can use a simple interface to create reports.

• All users work with consistent business terminology.

• Users can analyze data locally.

BusinessObjects Universe Designer components

You create, modify, and update universes with Universe Designer. Universe Designer provides a

connection wizard that allows you to connect to your database middleware. You can create

multiple connections with Universe Designer, but only one connection can be defined for each

universe. This database connection is saved with the universe.

Universe Designer provides a graphical interface that allows you to select and view tables in

a database. The database tables are represented as table symbols in a schema diagram. You can

use this interface to manipulate tables, create joins that link the tables, create alias tables,

contexts, and resolve loops in your schema. Users do not see this schema.

Universe Designer provides an object explorer view. You use the explorer tree to create objects

that map to the columns and SQL structures that are represented in the schema view. Users

select these objects to run queries against a database.

Starting Universe Designer Universe Designer can only be used with a BusinessObjects repository. You must log onto the

repository before starting Universe Designer.

After you start Universe Designer, you can open a universe in one of the following ways:

• Create a new universe.

• Import a universe from the repository.

• Open a universe directly from the file system. A universe is available to end users once it has been exported to the repository. Importing a

universe, making changes, then exporting the updated universe to the repository is the most

common way of working with Universe Designer.

Note: You can save a universe to the file system. You do this when you are in the process of

developing the universe locally and when you want to share the universe with other users who

may not have connection rights to the target repository.

Note: You can lock and secure a universe before importing it from or exporting it to the Business

Objects repository for maintenance.



To start Universe Designer 1. Click the Start button on the taskbar.

2. Select the Programs menu.

3. Select the BusinessObjects XI 3.0 menu.

4. Select the BusinessObjects Enterprise menu.

5. Select the Designer menu.

The login dialog box for the repository appears.

Login information

System name of the repository server

User Name

your repository user name

Password

your repository password

Authentication

authentication method

Note: This information is normally provided to you by the Business Objects administrator.

Note: You can also use Designer standalone. Use the authentication method Standalone

(No CMS).

6. Click the OK button.

The Universe Designer start-up screen appears, and an empty Universe Designer session

opens. The user name and repository name appear in the title bar.

Note: Depending on options set for Universe Designer, the Quick Design Wizard can start

automatically when you start in Universe Designer. Click Cancel to close the wizard.



Using the Quick Design Wizard When you start a Universe Designer session for the first time, the Quick Design Wizard appears

by default. You can use the wizard to quickly create a universe or to familiarize yourself with

Universe Designer. However, unless your data source is a very simple model, it is not an

appropriate tool for creating a complete universe that responds to end-user reporting

requirements.

Once you are familiar with Universe Designer, you will probably decide to disable the wizard

and not use it to design universes. All the universe design, building, maintenance information,

and procedures in this training manual are structured with the assumption that you have

disabled the Quick Design Wizard.

To deactivate the Quick Design Wizard You can prevent the wizard from appearing automatically when you create a new universe as

follows:

1. Select Tools ➤ Options . Select the General tab.

2. Clear the Show Welcome Wizard check box, and click OK.

Note: This check box is already cleared if you have cleared the Run this wizard at startup

check box from the Startup Wizard Welcome page.

Note: You can activate the Quick Design Wizard at any time by selecting the above check

boxes from the General page of the Options dialog box.

Using Universe Designer module commands There are three ways to issue commands in Universe Designer:

• Menu options

• Toolbar buttons

• Right-click menus

Menu options You can perform most tasks by choosing options from the menu. The Universe Designer menu

bar looks like this:

Toolbar buttons The toolbar gives you quick access to many tasks. Universe Designer has three toolbars: the

Standard toolbar, the Editing toolbar, and the Formula Bar toolbar.



Right-click menus Right-click menus display on your screen when you click the right mouse button. These menus

usually give you access to options related to the task you are currently performing. For example,

if you right-click in the Universe pane, a drop-down menu for creating classes and objects is

displayed:

Universe Designer window

The Universe Designer window is made up of two segments.

• On the right-hand side is the pane in which you insert the database tables and then view

the universe structure that infers the FROM and SELECT clauses into a Select statement.

This is known as the Structure pane.

• On the left-hand side is the pane in which you create the classes and objects that users will

see when they build queries using this universe. The objects physically point to the tables

you see in the Structure pane.

This is known as the Universe pane.

Manipulating the structure view There are three ways to manipulate the Structure pane in the Universe Designer window:

toolbar buttons, drag and drop, and by using the Options panel.

Zoom Often it is not possible to view the entire schema at normal magnification due to its size. Zoom

in or out using the drop-down list on the toolbar to choose your percentage view for the schema.

Arrange tables You can select this button to have Universe Designer automatically organize your tables

sequentially and horizontally.



Note: You can undo only the last command. If you do not like the arrange tables results, choose

Undo from the Edit menu.

Drag and Drop Different views of the universe structure can be achieved by selecting items and applying a

command using one of the following methods:

• Double-clicking

• Dragging and dropping

• Right-clicking For example:

Procedure Action

To mark a single table Click the header of the table.

To mark a join Click it.

To mark more than one table or join Ctrl-click the header of each table (or join) you

want to highlight.

To mark all tables and joins Ctrl-A.

To move a table Click the header of the table and drag and drop

the table to the desired position.

To roll up a table

To view the columns of a table

To view the remaining columns

By default, the table header and a specified

number of its columns are shown for all tables

contained in the universe structure segment.

This view can be altered for an individual table

by double-clicking the table header.

Double-click once to roll up a table so that only

the header is shown. Double-click twice so that

only the table header and key columns are

shown. Double-click three times to return to

an unrolled view of the table.

If the view of a table does not show all the

columns contained within that table, this is

signified by three dots at the bottom of the

table.

Click the header of the table; a scroll bar

appears on the right of the table. Alternatively,



Procedure

To gain a partial view of the data content of

the table

Action

place the pointer on the bottom margin of the

table and a double-headed arrow appears. You

can then drag the bottom margin down to

expand the number of columns shown in the

table.

To achieve this the table header must not be

highlighted.

Right-click the table header and choose the

View Table Values option.

Right-click the column required and choose

the View Column Values option.

To view the data values for a single column By default, data is only displayed for the first 100 rows of the table. This number can be

expanded or reduced using the Tools ➤

Options ➤ Database tab.

To view the number of rows for a table in the

database

Right-click the table header (or structure

segment background if you want the number

of rows for all tables) and then choose the

Number of Rows in Table option.

If you are front ending a large database, this

may not be advisable due to the time it takes

to process.

Saving and exporting a universe Regularly save your universes during a work session. When you save a universe, Universe

Designer stores it as a file with a .unv extension in your local file system. This is usually a

universe folder in the BusinessObjects installation path. Any changes you have made to the

universe file are saved locally but are not propagated to the universe version in the repository

until you choose to export it.

When you export the universe, the updated version is saved on the local file system, but it is

copied to the BusinessObjects repository as well. This version is then available to end users

connecting to the universe.

It is also made available to other universe designers who are authorized by the BusinessObjects

Administrator to access it.

Regularly save your changes to a universe locally. When you have finished updating the

universe, export the latest saved version to the repository.



If you choose to browse to a copy of that universe file on your local file system and open it

directly in Universe Designer, the file may not be the latest version of the universe. If you want

to make changes to a universe that has already been exported to the repository, do not open a

universe file directly using File ➤ Open menu. Instead, use File ➤ Import to ensure that you

are viewing the most recent version. Make your modifications and export your universe again

to make your changes available in the repository.

Importing a universe When you import a universe, you import the latest version of the universe from the repository.

The universe is copied to the local file system, and this file is opened in Universe Designer.

You can import one or more universes stored in a universe folder in the repository.

To import a universe 1. Select the Import command from the File menu.

The Import Universe dialog box appears. 2. Select a universe folder from the drop-down list.

Note: You can also import a universe by clicking the Browse button to select the universe

you would like to import.

Note: If you want to lock the universe, double-click the universe name. A locked universe

appears with a padlock symbol. Locking a universe prevents other designers from importing

or exporting this universe. The locked universe can still be read by users and other designers.

To unlock a universe, double-click it again.

3. Click the universe name.

This is the universe that you want to import. 4. Verify the file path for the import folder in the Import Folder box.

This points to the location where the universes are exported. 5. Click OK.

Universe file names as identifiers Do not change the universe file name after reports have been created based on that universe.

If you change the file name, any report built on the universe with the old name does not point

to the universe after its name has been changed.

The universe name can be different from the .unv file name.

When you use Save As to save the universe under a new name, the new universe is not

associated in the repository. You must export the new universe to the repository to create a

version of the new universe.



You can use the following methods to save a universe:

1. Select File ➤ Save from the menu bar.

2. Click the Save icon.

3. Press CTRL+S on the keyboard.

Do not save two different universes with the same file name. This leads to conflicts when you

attempt to export these universes to the repository.

Saving a universe definition as PDF You can also save the universe information in Adobe PDF format. This allows you to save to

a PDF file with the same attributes that are defined for printing purposes.

Note: You can view the default attributes by selecting the Tools ➤ Options menu and selecting

the Print/PDF tab. The Options dialog box will be presented in detail in a later lesson.

The attributes that you can print or save to a PDF file include:

• General information - parameters, linked universes, and the graphical table schema.

• Component lists - lists of components in the universe including objects, conditions,

hierarchies, tables, joins, and contexts.

• Component descriptions - descriptions for the objects, conditions, hierarchies, tables, joins,

and contexts in the universe.

Saving these attributes as a PDF file may be helpful for troubleshooting or maintenance purposes.

To save universe information as a PDF file 1. In Universe Designer, open the universe you want to save as PDF.

2. Select File ➤ Save As.

3. Select Portable Document Format (PDF) from the Save As type drop- down list.

4. Click Save.

Giving all users access to a universe If you want to make a universe available to universe designers who may not have access to

your Central Management Server, you must save the universe with an unsecured connection.

To make a universe accessible to all Universe Designer users 1. Verify that the universe that you want to make available to all users does not have a secured

connection.

Secured connections are required to export universes to the repository. If a universe has a

secured connection, select or create a new personal or shared connection.



Note: Creating connections is discussed in detail in a later lesson. 2. Select File ➤ Save As.

3. A File Save dialog box appears.

4. Select the Save For All Users check box.

5. Click OK.

Activity: Viewing a universe in Universe Designer Objective

• Open a universe and identify universe elements in Universe Designer

Instructions 1. Open Universe Designer.

2. In Universe Designer, click File ➤ Open. Browse to the eFashion.unv file found in the

default installation folder:

C:\Program Files\Business Objects\BusinessObjects Enterprise

12.0\Samples\en\UniverseSamples

Or, find the same file on the Resource CD for this course. 3. Explore the menu options, toolbar buttons, and right-click drop-down menus.

4. Select View ➤ Toolbars, and ensure that all three toolbars are selected.

5. Zoom to 125% (type directly into the field instead of using the drop-down list).

6. Click View ➤ Arrange Tables to automatically organize tables.

7. Click View ➤ List Mode to list all Tables, Joins, and Contexts.

8. Click the Article_Color_Lookup table in the Tables list and to see it highlighted in the

structure below.

9. Select Tools ➤ Options and click on the Graphics menu tab.

10. Select the Show row count check box, and click OK.

11. Right-click the Article_Color_Lookup table to view the number of rows in the table (Refresh

row count for all tables).

12. Right-click the Article_Color_Lookup table to view a sample of the table values.

13. Open the Product class to view the objects it contains.

14. Double-click the Color object (notice the name, description, and select fields).

15. Select Parameters on the File menu and change the universe long name to New eFashion.

16. Close the universe.



The Universe Development Cycle Universe development is a cyclical process that includes planning, designing, building,

distribution, and maintenance phases. Use Universe Designer to design and build a universe.

However, the usability of any universe is directly related to how successfully the other phases

in the development cycle interact with each other.



The Universe Development Cycle process This unit presents an overview of a universe designing methodology that you can use to plan

and implement a universe development project.

The diagram below outlines the major phases in a typical Universe Development Cycle:

The analysis of user requirements and design are the most important stages in the process.

Users must be heavily involved in the development process if the universe is going to fulfill

their needs both with the business language used to name objects and the data that can be

accessed.

Implementation will be successful if the first three stages are carried out properly. It is advisable

to spend 80% of the time allocated to the development of a universe on the first three stages:

• preparing

• analyzing

• planning



If you have spent the appropriate amount of time in laying the foundation for your universe,

the remaining 20% of the time spent actually using Universe Designer to build your universe

will be much more productive.

Preparation phase During the preparation phase, the scope of a BusinessObjects universe is defined. The production

and development architectures are identified and reviewed. Project teams are assembled and

the initial task plan is defined.

Identify universe scope

The definition and communication of project scope eliminates risk associated with deploying

the universe to pilot users during the Implementation phase. The scope is defined in terms of

intended functionality of the universe. Identification of target users of the universe also helps

create a shared understanding of project objectives.

Key managers should be involved in the scoping process. Once formulated, the objectives of

the project are communicated to everyone involved, directly or indirectly.

Build a project team

In designating the team members, individuals must be chosen to fill the following roles. One

person may fill multiple roles.

Role Task

Sponsor

Usually the individual funding the project. The project

sponsor makes any final decisions regarding scope or

unresolvable issues.

Project Leader

The project leader develops the project plan, assigns

resources, tracks, and reports on progress.

Analyst

Individual who gathers requirements in the form of

candidate objects.

Data Expert

An individual familiar with the data structures.

Key User

Provides ongoing “business” perspective for

developers.

Pilot Users

Users who will work with the universe during the

universe build and development phase.

QA Reviewer

An individual with BusinessObjects experience who

is not part of the development process will perform a

technical review of the final product.



In most cases, a single person will be responsible for the bulk of the work, filling the roles of

Analyst, BusinessObjects Administrator, and Data Expert.

In designing and building the universe, this person will maintain a relationship with the Key

User, who should also be one of the Pilot Users.

This developer usually reports to a Manager or IS Director, who serves as Project Leader. The

Leader maintains a close relationship with the Sponsor.

Other roles that will be impacted by the project include the Database Administrator, the System

Administrator, and the Data Administrator.

Adopt standards

Standards for the components of a BusinessObjects universe will help to guarantee consistency

and stability in the final product. During preparation, the team adopts a set of standards for

BusinessObjects components. Standards can be specified for:

• Universe names

• Object definition guidelines

• Names for objects

• Class names

• Alias names

• Help text

The standards may be revised during the course of the first universe development project as

the team becomes more familiar with the product.

Conduct a meeting

Communicate the preparation phase strategy in a meeting. This is your opportunity to gather

all interested parties (developers, users, the sponsor) to ensure that everyone understands the

scope of the endeavor.

You can use this meeting to demonstrate BusinessObjects products and to help set expectations

of the user community.

Analysis phase The primary objective of analysis activities is to identify user requirements for the ad hoc query

environment.

These requirements are captured in the form of candidate classes and objects.



Identify candidate objects

There are many places to look for candidate objects. The best way to identify them is by talking

to the end users. When interviewing end users, the type of questions to ask are: “What type of

information do you need to do your job?”, “How do you know you are doing well?”, “How

does your boss know you are performing well?”, or “What kind of information do others ask

you for?”

As users answer these questions, document their answers in terms of class and object

requirements. For example, if a user states, “We require to retrieve information on employees

by department and hire date” you have identified a potential class (“information about

employees”) and an object or two (“department” and “hire date”). When you identify a potential

class, probe for objects. For example, “What kind of information about Employees do they

want?”

Candidate classes and objects can also be identified by reviewing existing reports.

Document your classes and objects. For example:

Type

Class

Name

Customer

Description

Information on a customer, including location,

credit ratings, and shipping preferences.

Source

Interview #1

Object

(Measure)

Total

Revenue

This object can be combined with date ranges,

customers, and/or products to provide

meaningful measures.

Interview #3, #4

You should also try to document the qualification of objects (dimension/detail/ measure) and

any potentially identified hierarchies.

Relational modeling versus multi-dimensional modeling

The questions asked during BusinessObjects interviews are similar to those asked in the

development of OLTP applications. What is done with the answers is very different.

When conducting Analysis for an OLTP application, analysts document data requirements in

entity relationship diagrams. Rules of normalization are applied to the items that users request,

breaking them down to an atomic level, or eliminating calculated objects. These activities

optimize the data for storage in a relational database.

By contrast, requirements for an ad hoc query environment should be expressed in terms that

are optimized for retrieval of the information.

A successful BusinessObjects universe presents information to a business person using user

specific business terminology. The developer must “unlearn” analysis techniques used for the



development of application systems. User requirements must be taken at face value, remaining

in business terms.

Basic rules of thumb:

• Do not normalize

• Do not eliminate objects that can be derived from other objects

• Do not try to figure out where this data can be found in the database

For example: in an interview, a user states “I need to look at annual sales figures by region.”

Document this at face value; identify the requirements, but do not attempt to transform them

in a manner appropriate for storage in a relational database. You can identify three candidate

objects: “Year of Sale,” “Sales Amount,” and “Region”. Do not eliminate “Year of Sale” because

you have already documented a “Date of Sale” object. Do not reduce “Sales” to the components

from which it is calculated (perhaps “quantity” multiplied by “price”). Instead of normalizing

object requirements, identify how they will support on-line analysis by end users.

Identifying candidate objects as dimensions, details or measures will facilitate end user reporting

and analysis flexibility. You can also plan for scope of analysis (drill-down and drill-up options)

by identifying dimensional hierarchies.

Once you have gathered and documented requirements in the form of candidate objects, you

are ready to begin to plan the BusinessObjects universe requirements.

Planning phase The planning phase will be used to identify a project strategy and determine resource

requirements.

Create a project plan

The project plan is the key to timely implementation. For each task, the plan should assign

responsibility and target dates. Creation of the plan and the tracking of progress against the

plan are the primary responsibilities of the project leader.

Plan the BusinessObjects architecture

Technical architecture requirements may have been looked at in general in the preparation

phase. A review of the technical architecture should take place during the planning phase of

the project. Items to review include:

Development

environment Identify resources required to support a universe development

environment.



Production

environment

Identify resources required for a universe production environment.

Computers

Review required computing resources for developer and user workstations.

Connectivity

Ensure infrastructure is in place to support connectivity between users/developers

and the repository and data stores, including appropriate middle-ware to support

communication between clients and servers.

Configuration

Identify planned configuration for client software. Ensure appropriate resources are

available.

Security

Initiate a first look at security requirements.

Support plan

Develop support policy for when the universe goes into production.

Change management

plan

Identify procedures for the request, review, approval, and implementation of changes

to the universe when in production.

Training plan

Plan for a user training program.

Implementation phase

The implementation phase can be split up into two stages:

1. Designing the schema

2. Building the universe

Implementation phase 1: schema design

The first task during schema design is to determine and document the data source for each

candidate object. If requirements were gathered in a tabular format, add a column to the table

where you can indicate the SQL fragment and source tables that will be used to retrieve the

object.

Type

Class

Name Customer

SQL fragment Description

Information on a customer,

including location, credit ratings,

and shipping preferences.

Source

Interview

#1



Type Name SQL fragment Description Source

Object

(Measure)

Total

Revenue

SQL:

sum(order_lines.quantity*

products.price)

Source Tables: Order_Lines,

Products

This object can be combined with

date ranges, customers, and/or

products to provide meaningful

measures.

Interview

#3,4

Any candidate classes that were captured as general requirements without specific objects

must be expanded now. For example, suppose there was a candidate class called “Customer”

and the specific objects within this class were not identified. During the schema design stage,

the developer must “fill out” this class. The developer might fill it out based on knowledge of

the business by including all columns from one or more tables, or the developer might go back

to users for more detail.

There are several ways that objects can be mapped to enterprise data. Simple objects map back

to a single column in the database. An example would be “Customer First Name,” which maps

back to the First_Name column in the Customers table. Complex objects make use of SQL to

manipulate data that comes from one or more columns. For example, a Customer Full Name

object might connect the First_Name and Last_Name columns from the Customers table.

Aggregate objects involve SQL GROUP functions. Counts, sums, and averages are all aggregate

objects. The Total Revenue object is an aggregate object; it uses the SQL SUM function.

Plan for object qualifications and drill-down functionality As you design the universe, you must complete the process you began during analysis. Identify

each object as a measure, a dimension or a detail. For each detail object, identify the dimension

it is associated with.

Similarly, you need to identify hierarchies within your dimensions. These hierarchies will later

enable users to “drill-down” and “drill-up”.

Design a table diagram Now that the objects are mapped back to data sources, the developer reviews all the objects

and produces a table-diagram of the database objects that will support the universe. Joins

between the tables are then added to the diagram. The table diagram is a valuable tool for

resolving loops and SQL traps in the model. It will also become an important reference for

developers.

Note: This diagram design is usually done on paper, however this can be created directly in

the BusinessObjects Universe Designer software.

Tip: If you find that you have documented a vast amount of classes and objects based on user

requirements you may consider designing schemas that can be used to build:

1. Multiple universes which cater to a specific function within the business, reducing the

complexity and amount of classes and objects.

2. Multiple universes specific to a business function, as this will prevent users from creating

queries that can span the spectrum of the business.



Revise objects and table diagram Once loops and SQL traps are resolved, the design of some objects will require modification.

Any object based on a table that was replaced by an alias must be updated. Consult your table

of objects created in the preparation phase for such objects.

Note: If you are already using Universe Designer for the schema design you can view a table‟s

associated objects to identify which objects require changes.

Some objects may be applicable in the context of more than one of the aliases; these objects will

be split into multiple objects. Make sure that object names make it clear what each one represents.

Review join strategy Where table relationships are optional, the type of join to use must be chosen carefully. The

use of standard (or inner) versus outer joins will impact the results of user queries. Using the

wrong type of join may provide results that are not what users expect.

In SQL, a standard join between two tables will return only rows where both tables meet the

join criteria. If one of the tables has no corresponding row in the second table, its data will not

be returned.

An outer join tells the database processing the SQL query to substitute a “null” row if one of

the joined tables has no corresponding row in the other table. With an outer join, information

in one table that does not have corresponding data in the second table is returned with “blanks”

in columns from the second table.

The developer must review join possibilities with a key user wherever optional relationships

exist. The chosen solution should produce results that users are most likely to expect.

Identify allowable object usage The developer may identify certain objects that should not be used in qualifications by end

users. Certain complex objects may not be usable in qualifications for technical reasons, or there

may be performance considerations.

Determine security approach Security requirements must also be addressed during the Implementation phase. Solutions to

security requirements may involve complex object definition, reliance on database-level security,

use of BusinessObjects access levels (public, private, controlled), restriction sets or the

development of multiple universes. Chosen solutions may impact the database administrator

and developers.

Implementation phase 2: building the universe



Once the schema design stage is complete, the development team is ready to begin using the

BusinessObjects Universe Designer software to build the universe.

Tip: Remember that it is better to have several smaller less complex universes than one large

universe. This will reduce maintenance, avoid potential security impacts and will improve

overall usability.

Pilot users then begin to use the universe. They provide feedback to developers who refine the

universe until build is completed.

Build the universe The BusinessObjects Universe Designer software is used to actually build the universe. The

developer must:

• Name the universe.

• Set up the universe parameters and connect to the relevant data source.

• Create aliases and contexts as identified in the schema design.

• Create joins as identified in the schema design.

• Create classes, subclasses and objects as identified in the schema design.

• Define objects as dimensions, details, or measures.

• Define hierarchies.

• Define lists of values and help text.

• Define conditions and implement user security, where applicable.

Supply prebuilt queries and reports During the build stage, the team may identify certain queries and reports that will be of value

to the entire enterprise. Created at anytime throughout the build, these queries and reports are

re-checked after the universe is finalized to ensure that objects used have not been renamed or

removed. They are then exported to the repository so that they are available to all users.

Testing phase

The pilot testing and refinement phase follows universe design implementation.

Once an initial universe is built, it is deployed to the pilot users. These users work with the

universe and provide feedback to the developers.

Types of feedback include:

• Better names for classes and objects.

• Objects not in the universe that should be added.

• Objects that can be removed.

• Better ways to organize objects (for example, move an object from one class to another,

reclassifying a dimension as a detail, and so on).

• Objects or queries that do not behave as expected.



Based on this feedback, the universe is modified. The modified universe is made available to

the pilot users for further evaluation. The testing phase can also address potential performance

issues. As a developer you can look at implementing performance enhancements to the universe.

Quality assurance

After the build is finalized, the universe is reviewed for quality assurance.

An independent reviewer makes the following checks:

• Corporate standards for universe, object, class, and alias naming are followed.

• Objects are only defined with tables that are referenced in the select text or Where condition.

• Objects return results without syntactic error.

• Objects return intended business results.

• Objects are correctly classified as dimensions, details or measures.

• Defined hierarchies make sense.

• Objects have help text.

• Aliases are used appropriately.

• Join syntax and foreign keys are accurate.

• Standard and outer joins are used appropriately.

These checks are best made by an individual who was not part of the development of the

universe, guaranteeing an objective perspective. Any issues that are identified are reported to

the developers for correction and review.

Deployment phase The universe has been built, and has passed all quality assurance checks. It is now ready for

deployment.

The final deployment of the universe cannot begin until any architectural issues identified

during planning phase have been addressed. These issues include the establishment of user

connectivity, planning the installation configuration, preparation of a training program, and

identification of support and change management processes.

Architecture

Architectural considerations identified during the planning phase are reviewed. Any issues

that have not been resolved will delay the deployment phase.

Production environment

The production environment has been set up in accordance with the architecture and security

plans identified during preparation and planning. The universe is modified to access data from



production systems, rather than from development systems and is exported to the production

repository.

Granting user access

Any database accounts that will be required for BusinessObjects users should be created by

the database administrator. These accounts should be given appropriate access privileges to

the data objects used by the universe.

Users are also added to the Central Management System (CMS) and granted access to the

universe.

Conduct training

The release of the BusinessObjects universe to production users is coordinated with system

and database administrators as appropriate. The user training program is executed in conjunction

with the roll-out of the universe. Without appropriate training, users will not derive benefits

from BusinessObjects, regardless of the quality of the universe.

Updating/maintenance

Be sure to inform users about the support and change control mechanisms available to them.

They need to know who to call if they have a problem or question, and what procedure should

be followed to request a change to the universe. These mechanisms were identified during the

planning phase.

Prepackaged solutions If you are designing a universe for Business Objects developers for developing precreated/

prepackaged reports, then the following items should be taken into consideration:

• Predefine all filters and calculations that are used in standard documents, to remain consistent

throughout

• The universe can cover more than one business function, to allow cross functional reporting.

Precreated reports tend to cross reference reports against different business functions. The

universe will, therefore, have to cover multiple business functions to provide end-to-end

business reporting.



Activity: Planning a universe Objective

• Use the first three stages of the Universe Development Cycle.

Instructions 1. From the resource CD launch the Planning_universe_activity.html file.(Activity_Resources

> Lesson 1) to familiarize yourself with the Universe Development Cycle and to complete

the activity questions.

2. Use this checklist of questions you need to ask when you begin designing a universe:

• What are the target data sources for your universes?

• What is the schema/structure of each of these data sources?

• Do you know the contents of each of the tables?

• Do you know how each of the tables are interrelated?

• Are you familiar with all of the necessary joins?

• Are you familiar with the cardinality of each of these joins?

• Have you procured database schemas from the database administrators who administrate

the data sources?

• Are you familiar with your different user populations and how they are structured?

• Do you know what standard reports are required?

• Do you know what the users' ad-hoc information needs are?

• Are you familiar with their business terminology and formats?

• Have you considered how many universes need to be created to address users' needs?

• Have you considered how long universe development may take?

• Have you considered which universes should be developed before others?

• Have you considered who should test your universes for you?

• Have you considered how data sources and/or user requirements may change over

time?

• Do you already have all of the information necessary to implement your universes?



Quiz: Understanding BusinessObjects universes 1. What are the two main panes in Universe Designer?

2. What are the three ways to issue commands in Universe Designer?

3. Where can you define what specific information about the universe gets printed?

28 Universe Design-Learner's Guide


Lesson summary

After completing this lesson, you are now able to:

• Define BusinessObjects universe concepts


Creating the Course Universe—Learner’s Guide 29


Lesson 2

Creating the Course Universe

Lesson introduction This lesson introduces you to the database that is used in this course. It teaches you how to

create a new universe and define a connection from the universe to the course database.

To create a new universe and maximize its potential, it is necessary to learn about parameters.

Parameters allow you to set the structure of your universe, including setting up a database

connection.


• Describe the course database and universe

• Create the universe



The course database and universe In order to create a BusinessObjects universe, you must first be familiar with the data and

structure of the database to which the universe will be connected. You also need to fully

understand the users‟ reporting requirements.


• Understand the database used during this course

• Know the specifications of the universes built during this course

Course database description During this course, you are going to build universes to report on a database for a fictional car

sales and rentals organization called Prestige Motors. The database has the following

characteristics:

• There are three showrooms, two in the US and one in the UK.

• Each showroom has the franchise for a number of different car makers, who all manufacture

a number of different models, available in a range of colors.

• No new models have been brought out during the period.

• Customers may either rent or buy cars.

• Customers will usually rent or buy from the showroom in their own country but this is not

always the case.

• The database contains data for two financial years 2003/2004 and 2004/2005. Each year

begins on April 6 and ends on April 5 in the subsequent year.

• Information about employees who work within the organization is also available in the

database.

• There are summary tables for quarterly and annual revenue and numbers to speed up

queries.

• The data is stored in a SQL Server database.

• Connections to the database are to be made using ODBC.

Assumptions • There has been no inflation over the different years for which data is held.

• There is no stock data. All manufacturers are able to supply on demand.

• Users in all countries use the same currency (the US dollar).

Analysis of reporting requirements Following an analysis of the company‟s reporting needs, the following specification has been

identified.

1. Ad hoc reports are required on models.

• These are required to list the cars for sale and rent.



• Such reports may include the following:

manufacturer, model, trim, engine size, available colors, and sale/rental price.

• Reports may be grouped by price range and style (for example, sport, or estate.)

• These reports will be used to show potential customers model availability and for general

management reporting.

2. A report is required which lists the showrooms, their location and which manufacturers

they have a dealership agreement with. This report will be created by the universe designer

and distributed as a corporate document for all to read and refresh.

3. Ad hoc reports are required on car sales.

• These are required to list car, sale and customer details.

• Reports may be grouped according to customer, showroom, sale, model and manufacturer

dimensions.

• These reports will be used to analyze results at all levels from sales specific details to

general high level reports such as sales revenue per annum, per showroom, by

manufacturer, or by car.

4. Ad hoc reports are required on car rentals.

• These are required to list car, rental and customer details.

• Reports may be grouped according to customer, showroom, rental, model and

manufacturer dimensions.

• These reports will be used to analyze results at all levels from specific rentals details to

general high-level reports such as rentals revenue per annum, per showroom, by

manufacturer, or by car.

• Reports related to 2, 3 and 4 above will be used by sales staff, finance department staff,

and managers.

Development plan

The remainder of this course will be spent developing universes for this imaginary deployment.

In accordance with the iterative approach, the development will be phased as indicated below.

1. Design and develop a universe which enables end users to build reports which meet

requirements 1 (model reporting) and 3 (sales reporting). The universe needed to do this

can be regarded as relatively simple to create.

2. Extend the universe to meet reporting requirements 2 (franchise reporting) and 4 (rental

reporting). This requires the introduction of loops, chasm and fan traps into the universe

structure which need to be resolved. This constitutes a fairly complex universe structure.

3. Further extend the universe to refine and enhance the universe for end users by introducing

conditions, LOVs and hierarchies for drilling.

4. Design and develop a universe for end users that enables them to build reports which meet

requirements 5 (ad hoc reporting on employees).



Creating the universe In this unit, you will begin to create the course universe, based on the analysis of business

requirements and the development plan.


• Create a new universe

• Create a new data source name

• Create a new connection in Universe Designer

• Describe the universe parameter settings

Creating a new universe Before you can build a universe, you must firstly create a new universe file.

You save the new universe as a .unv file.

The new universe contains no classes and objects. You create these during the universe

development process by designing a table schema and then creating objects that map to database

structures.

To begin creating a new universe 1. In Universe Designer, select New from the File menu.

The Universe Parameters dialog box displays:

Note: Make sure the Universe Parameters dialog box displays with the Definition tab

active.



2. In the Name field, enter a name for the universe.

3. In the Description field, enter a brief description for the universe.

This is used as a help description for the end user. It needs to accurately describe the content

of the universe using terminology the end user will easily understand.

4. Select File ➤ Save from the menu bar.

5. Provide a name for the file.

The universe file is saved as a .unv file

Defining universe parameters To be able to start building the universe structure, you must first define a number of parameters,

such as the parameters to be used to connect to the data source.

Universe parameters are definitions and restrictions that you define for a universe. These

parameters:

• identify the universe

• identify the database connection

• specify the type of queries that can be run using the universe

• set the controls on the use of system resources

An important element of this setup process is selecting the kind of database connection you

will use.

Select an existing connection or create a new one. The other parameters can be set at this point

but are better done at a later point in the universe building process.

Identifying the universe Each universe is identified by the following parameters:

Identifier Used by

File name File system, Business Objects end-user

querying tools to reference the universe

Long name Business Objects end-user querying tools

Description Business Objects end-user querying tools

Unique system identifier Central Management Server



File names A file name is created when you save the universe. The length of the name is dependent on

your operating system maximum. Windows allows approximately 156 characters. The file

name extension is .unv.

The local file system is the server on which Universe Designer is installed. Your universes are

saved by default in the universes folder in your user profile path as follows: \\Documents and Settings\<user>\Application Data\Business Objects\Business Objects

12.0\Universes\<universe>.unv

Note: Do not change the universe file name after reports have been created on that universe

or the report files will no longer point to the universe.

Long names The universe long name is set in the Name field on the Definition tab. You can enter up to 200

characters and there are no character restrictions.

Universe descriptions The universe description is an optional field. Information in this field can provide useful details

about the universe‟s role and is viewable by end users.

Unique system identifiers The unique system identifier is assigned by the Central Management System (CMS). This occurs

when the universe is exported to the repository for the first time.

Setting the database connection In order to connect to the database for which you intend to build a universe, you need to create

a BusinessObjects connection.

A connection is a named set of parameters that defines how a Business Objects application

accesses data in a database file. A connection links Web Intelligence to your middleware. You

must have a connection to access data.

The BusinessObjects connection contains all pertinent information for how to connect to the

target database (for example: data access driver (middleware), connect string, connection type,

and advanced connection parameters).

If you are building several universes to front end the same database, then the connection may

already exist. Therefore, you only have to select it from the available connections. However, if

the connection does not exist, you will have to create one.

Data access drivers A data access driver is the software layer that connects a universe to your middleware.



Data access drivers are shipped with Business Objects products. There is a data access driver

for each supported middleware. When you install Universe Designer, your data access key

determines which data access drivers are installed.

When you create a new connection, you select the appropriate data access driver for the relational

database management system (RDBMS) middleware that you use to connect to the target

RDBMS.

The types of databases supported through data access drivers are:

• IBM DB2

• Informix

• Microsoft SQL Server

• Oracle

• Red Brick

• Sybase

• NRC (Teradata)

• Hyperion

• Generic ODBC

With the new XI architecture, connections can now be made to MS Analysis Services 2000,

MySQL, and SAP. Additional connection options shown below have been added in XI R2 and

XI 3.0.



ODBC connection drivers Open Database Connectivity (ODBC) is Microsoft's strategic interface for accessing data in a

heterogeneous environment of relational and non- relational database management systems.

An ODBC Driver can be the "back end" for a DBMS (Database Management System) server

environment. Any ODBC client can access any DBMS for which there is an ODBC Driver, for

example SQL Server, Oracle, AS/400, Foxpro, Microsoft Access, or any DBMS for which an

ODBC driver exists.

Note: Connections to the database can be made using ODBC as well as OLE DB (Object Linking

and Embedding, Database). OLE DB extends the ODBC feature set to support a wider variety

of non-relational databases, such as object databases and spreadsheets that do not necessarily

implement SQL.

To create an ODBC connection for SQL Server Note: This example describes how to create an ODBC connection. Direct connections are

supported for certain database vendors, therefore the ODBC setup is not always required.

SQL Server is the database used for this course, and requires an ODBC connection.

1. Navigate to the ODBC Data Source Administrator wizard.

• Start ➤ Programs ➤ Administrative Tools ➤ Data Sources (ODBC)

• Start ➤ Settings ➤ Control Panel ➤ Administrative Tools ➤ Data Sources (ODBC)

2. Click the System DSN tab.

3. Click Add.

4. Scroll down to select the SQL Server driver, and then click Finish.

5. In the Create a New Data Source to SQL Server window add or select the following:

• In the Name box, type a name that identifies the database you want to connect to.

• In the Server box, type (local) - unless SQL Server is installed on another machine. In

that case, select the machine name from the list.

6. Click Next.

7. For the authentication, select the appropriate method for SQL Server to authenticate the

login ID.

Depending on the selected option, type in the required Windows or SQL Server authentication

user name and password.

8. Select the Change the default database to check box, and then select the database to connect

to from the drop-down list.

9. Click Next, and then click Finish.

10. Click Test Data Source.

You should get the message TESTS COMPLETED SUCCESSFULLY.



If you don‟t get this message, review your steps and verify the added authentication

credentials.

11. Click OK until you can close the Administrative Tools window.

To define a connection in Universe Designer 1. In the Universe Parameters dialog box, verify that the Definition tab is selected.

2. Click New.

Note: You can also create a new connection from the Connections dialog box. Select Tools

➤ Connections and click the Add button in the Connections list.

The Welcome page of the Connection Wizard appears. 3. Click Next.

The Database Middleware Selection page appears. It lists the database and middleware

that correspond to your data access driver key.

4. Select the connection type from the Type list box.

Note: In order to deploy a universe to the BusinessObjects repository, you must define this

connection type as “Secured”.

5. Define a name for the connection.

You can enter up to 35 characters. 6. Expand the + box for the target database for the connection.

The supported middleware for that database appears in the expanded area. 7. Expand the + box for the target middleware for the connection.

The data access driver for the middleware appears. 8. Select a driver name and click Next.

The Login Parameters page appears.

9. Select the required authentication mode.

10. In the User name and Password field enter the database login credentials.

11. In the Data source name field, select the appropriate data source for the database you are

connecting to.

12. Once you have entered this information, click Next.

13. In the Configuration Parameters page, apply the required parameters or keep the default

values selected. Click Next.

14. In the Custom Parameters page, apply the required parameters or keep the default values

selected. Click Finish.

15. In the Wizard Connection dialog box, click the Test button to test the connection.



If the connection is valid, a message dialog box appears indicating that the connection is

correct. If you receive an error message, check that you entered all the parameters correctly.

If the error persists, refer to the section of your RDBMS documentation relating to error

messages.

16. Click Finish to exit the wizard.

If you created the connection from the Universe Parameters dialog box, the new connection

is listed in the connection drop-down list.

Note: Avoid creating two different secured connections with the same name. For example,

one connection named "Status" and the other named "status". This may lead to a conflict in

the repository.

More about connection types The connection type determines who can use the connection to access data. You can create

three types of connections with Universe Designer: personal, shared, and secured.

Personal connections Use personal connections to restrict data access to the universe creator and the computer on

which it was created. Using a personal connection, you have access to personal data on a local

machine.

You do not use personal connections to distribute universes.

Shared connections Allow access to data for users. These connections are unsecured. Shared connections can be

useful in a universe testing environment.

Secured connections Secured connections centralize and control access to data. They are the safest type of connection.

Use secured connections to protect access to sensitive data.

You can create secured connections with Universe Designer.

Connections are stored in the BusinessObjects repository. These can be shared with other

designers with the appropriate privileges.

You must use secured connections if you want to distribute universes through the

BusinessObjects repository. Secured connections can be used and updated at any time. To

define a secured connection you must be connected to the BusinessObjects repository.

Viewing, modifying, and deleting available connections You can view all available stored connections in the Connections List .

Using the Wizard Connection, you can edit existing connections, or create new ones.



Note: You cannot modify the name of an existing connection.

Created connections can be removed from the Connections List.

To view available connections

1. Select Tools ➤ Connections.

The Wizard Connection dialog box appears with the Connections List page. This list displays

all the connections available to the designer, regardless of the universes. The current universe

may be based on a SQL Server database, but you can add a new connection to an Oracle

database in this wizard. You can add, delete and edit existing connections from this dialog

box.

2. Click Cancel to close the dialog box.

To edit a connection

1. Click Tools ➤ Connections.

The Wizard Connection dialog box appears. 2. Select the connection that requires editing from the list of available connections.

3. Click Edit.

The Login Parameters page for the connection appears. 4. Modify the login parameters or select a different data source for the connection.



5. Click Next.

6. Modify the configuration parameters as required, and click Next.

7. Modify the custom parameters as required, and click Finish.

8. Click the Test button to verify the modified connection.

9. Click Finish to apply the changes to the connection.

To delete a connection

1. Click Tools ➤ Connections.

The Wizard Connection dialog box appears. 2. Select the connection you want to delete from the list of available connections.

3. Click the Remove button.

A confirmation dialog box appears. 4. Click Yes.

The connection is removed from the list.

Universe parameters

This topic describes the parameters that you can define using the different tabs available in the

Universe Parameters dialog box.

Note: For more detailed reference information about these parameters, refer to Chapter 2 - Doing

Basic Operations, Setting Universe Parameters in the Business Objects XI 3.0 Designer’s Guide.

Universe Parameters dialog box There are seven tabs on the Universe Parameters dialog box that allow you to change different

parameters. This lesson provides a brief introduction to these tabs. They are discussed in more

detail later in the course.

This table provides a quick snapshot of the different tabs:

Parameter Description

Definition

Universe name, description, connection

parameters, and information. These parameters

identify the universe.

Summary Version and revision information, designer

comments, and universe statistics.



Parameter Description

Strategies

Strategies used by the universe. A strategy is

a script used to extract structural information

from a database.

Controls Limitations set for the use of system resources.

SQL Types of queries that the end user is allowed

to run.

Links Settings defined for linked universes.

Parameter

Definition tab

SQL parameters that can be dynamically

configured.

On the Definition tab you can set the universe name and a meaningful description. There is

no character limitation. End users will see these in their Business Objects querying tool when

they select the universe.

The Connection field displays the connection name defined against the database.



Summary tab

The Summary tab displays universe administration information.

Information Description

Created Universe creation date and the name of the

creator.

Modified Date of last modification and the name of the

modifier.

Revision

Revision number indicates the number of

timesthe universe has been exported to the

repository.

Comments

Information about the universe for yourself or

another designer. This information is only

available in Universe Designer. Includes

information about the universe for users in the

Description field on the Identification page.

You can print the text contained in this box,

which means that you can use it to track

changes made to the universe and by whom,

if you so desire.



Information Description

Statistics

Strategies tab

List of the number of classes, objects, tables,

aliases, joins, contexts, and hierarchies

contained in the universe.

A strategy is a script that automatically extracts structural information from a database or flat

file. Default strategies have two principle roles:

• Automatic join and cardinality detection

• Automatic class, object, and join creation Strategies are useful if you want to automate the detection and creation of structures in your

universe based on the SQL structures in the database.

Strategies that automate the creation of universe structures are not necessarily an essential part

of universe design and creation. They are useful if you are creating a universe quickly, and

you want to use metadata information that already exists in a database or database design tool.

However, if you are building a universe by creating objects and joins that are based on

relationships that come directly from a user needs analysis, then you will probably not use the

automatic creation possibilities that this tab offers.

Built-in strategies are the default strategies that are shipped with Universe Designer. You can

select them by clicking the drop-down menus in this strategies parameters tab. There are built-in

strategies for all supported databases, which cannot be modified. You can, however, create



custom strategies, which are known as external strategies. Built-in strategies appear by default

before external strategies in the drop-down lists.

Note: The built-in strategies for detecting joins will only select on matching column names, ignoring

all other column names, and may create unnecessary joins.

Controls tab

On the Controls tab, you can limit the result size and execution times for queries that use this

universe.

The Limit execution time option allows you to restrict the execution time for any query

generated via the universe for queries generating more than one SQL statement.

The time limit that you specify for query execution is the total execution time for a query. If

the query contains multiple SQL statements, then each statement is given an execution time

equal to the total query execution time divided by the number of statements. The result is that

each statement in the query has the same execution time.

If one statement requires a lot more time than others to run, it may not complete as its execution

time will not correspond to its allotted execution time within the query.

When you specify an execution time limit for multiple SQL statements, you need to take into

account the normal execution time of the single statement that takes the longest time to run,

and multiply this value by the number of statements in the query.

SQL tab



You can set controls on the types of queries that end users can build in Business Objects querying

tools.

You can indicate controls for the following areas of query generation:

• Use of subqueries

• Use of operators and operands in individual queries

• Generation of multiple SQL statements

• Selection of multiple contexts

• Prevent or warn about the occurrence of a Cartesian product

Note: The Multiple SQL statements for each measure option is selected by default. Accepting this

default value could potentially impact query performance. This issue will be discussed in more

detail in later lessons.

Links tab



Links specify dynamic links between universes related to the same database. This allows a

universe and its content to be embedded in another universe. Embedding universes optimizes

maintenance where some objects are used in many universes.

Note: Universes need to be exported to the repository before linking.

Parameters tab

In Universe Designer, you can configure certain SQL parameters that are common to most

databases to optimize the SQL generated. These parameters apply only to the active universe,

and are saved in the .unv file.



Activity: Creating a new universe and defining its connection Objective

• Create a new universe and define its connection to the database.

Instructions 1. Create a DSN for SQL Server 2005 called MotorsDSN.

2. Start a Universe Designer session and log on.

3. Create a new universe and define the following parameters:

• Name = Motors

• Description = This universe provides information on the Prestige Motor Cars

Database for Showrooms, Models sold, Rental and Sales Business

• Connection = Motors_conn

Tip: Use the New Connection Wizard to create the Motors connection against the Motors

database in SQL Server.

4. Save the new Motors universe.

The universe is saved in the local universe directory. 5. Create another new universe and define the following parameters:

• Name = Staff

• Description = This universe provides information on the personnel of Prestige

Cars.

• Connection: Motors_conn

Note: Use the same connection that you used in Step 5: that is, Motors_conn against the

Motors database.

6. Save the Staff universe.



Quiz: Creating the course universe 1. Information about universe administration appears on the Universe Parameters dialog box.

Under which tab can you find this information? 2. Can a universe and its content be embedded in another universe?

3. If you want to distribute the completed universe to the user population using the

BusinessObjects repository, which type of connection should you use?

Creating the Course Universe-Learner's Guide 49


Lesson summary


• Describe the course database and universe

• Create the universe

Building the Universe Structure—Learner’s Guide 51


Lesson 3

Building the Universe Structure

Lesson introduction This lesson describes how to add tables to the universe structure and how to customize the

way you work with tables.


• Populate the universe structure

• Define joins in a universe



Populating the universe structure A schema is a graphical representation of a database structure. In Universe Designer you create

a schema for the part of the database that your universe represents.


• Design a schema

• Add tables in the Structure pane

• Organize your view of tables

Designing a schema

The schema contains tables and joins. Objects are mapped to columns in tables that end users

use to create reports. The joins link the tables so that the correct data is returned for queries

that are run on multiple tables.

Design the schema in the Structure pane by selecting tables from the target database using the

Table Browser. You create joins to link the tables. When you have designed the schema for

your universe, you can verify the schema using an automatic integrity check.

Good schema design is essential to good universe design. Populate the schema with tables

based on the columns that correspond to the objects that end users need to create reports. Define

the objects according to a user needs analysis. Examine the database for tables that allow you

to create these necessary objects.

Schema design and the universe creation process After the initial schema design in the first implementation phase of the Universe Development

Cycle, you will start using Universe Designer to build your universe.

Adding tables The Structure pane of the Universe Designer interface is used to create a visual representation

of the physical data structure to which the universe is mapped. When you create a new universe,

the structure is empty and you need to populate it with the appropriate tables. Database tables

are placed in the structure using the Table Browser, which provides a list of tables in the

database.

The Table Browser is an independent window that shows a tree view of the tables and columns

in your target database. Use the Table Browser to view and select tables in your database that



you want to insert into your schema. Expand the + box next to a table name to display the

columns for the table.

To open the Table Browser The Table Browser is not visible by default. You must activate the Table Browser when you

want to add tables to the Structure pane. You can activate the Table Browser using any of the

methods listed below.

Note: A universe file has to be open in Universe Designer to be able to access the Table Browser.

1. You can open the Table Browser using one of the following methods:

• Click the Table Browser button on the Editing toolbar.

• Double-click the background area of the Structure pane.

• Select Insert ➤ Tables from the menu bar.

• Right-click the Structure pane and choose Tables from the drop-down menu.

The Table Browser displays:

From the Table Browser you can select tables to include in the universe schema. You can

insert a single table or multiple tables simultaneously.

To insert a single table

1. You can use the following methods to insert a single table:



• In the Table Browser, click a table and drag it into the Structure pane.

• In the Table Browser double-click a table.

• In the Table Browser click a table, and click Insert.

The table appears in the Structure pane.

To insert multiple tables

1. In the Table Browser, hold the Shift key while you click the first table and last table to select

a continuous block of tables. Multiple tables are selected.

Note: The Ctrl key can also be used here to select multiple tables.

Tip: It is a good practice to insert only a few tables together at one time. This makes the

schema more manageable when making further adjustments and adding joins.

2. Use one of the following methods to add the tables to the Structure pane:

• Click Insert

• Drag and drop the selected tables in the Structure pane.

Each table including all of its columns appears in the Structure pane. In the Table Browser,

any table that you insert in the universe displays with a check mark beside its name.

Note: Columns cannot be selectively chosen. When you select a table, all columns will be

included in the structure.

To view data from the Table Browser You can use the Table Browser to view the data contained in a table, or in an individual column.

1. Expand a table +box in the Table Browser and right-click a column or the entire table.

2. Select View Table Values from the right-click menu.

A dialog box appears listing the data contained in the table or column.



Manipulating tables in the universe structure When a table has been placed in the Structure pane, it shows the names of the columns it

contains.

You can use various commands to manipulate tables within the Structure pane. These are

described in the sections that follow.

You can move, copy, or delete tables in the Structure pane, as well as organize and change the

table display.

To select tables Usually the first step in moving, copying, or deleting tables is to select them.

1. To select a single table, click the table header.

2. To select several tables, press Ctrl and click the table header of each table you want to select

in turn.

3. To select all tables, press Ctrl + A or choose Edit ➤ Select All from the menu bar.

Tip: You can also select multiple tables by:



• clicking on the Structure pane

• holding the left mouse button down

• dragging the mouse across the tables you want to select

A line appears when you do this and boxes in your selection.

4. To deselect a table, click the background of the Structure pane.

To move tables 1. Select the tables you want to move.

2. Drag the tables to a new position.

To delete tables 1. Select the tables you want to delete.

2. Press the Delete key.

To organize your tables There are several options that enable you to obtain a better view of your tables:

1. Use drag and drop to move the tables around the Structure pane.

2. Click the Arrange Tables button to arrange tables horizontally.

3. Select from the Zoom drop-down list to minimize or magnify the Structure pane.



4. Double-click the table header in Structure pane to change the table display.

To change a table display You can change tables so that they display all columns of a table, the table name only, or the

primary and secondary keys (join columns) only.

1. There are three options to change a table display:

• Select View ➤ Change Table Display from the menu bar.

• Select Ctrl + T.

• Double-click the table header.

Table name displays:

2. If you select View ➤ Change Table Display , Ctrl+T, or double-click a second time, only

the Join columns will display in the table.

Join columns only display:

If you repeat one of those actions a third time, the original table view appears again.

To view table values

You can view the data for a database table or column in the same way as in the Table Browser.

1. Right-click the header of the table whose values you want to see.

The following menu displays:



2. From the menu, choose Table Values.

3. Click Close.

Activity: Populating the universe structure Objective

• Insert tables into the Motors universe.

Instructions 1. Insert the tables listed below into your blank Motors universe.

• CLIENT

• COLOUR



• COUNTRY

• FINANCE_PERIOD

• MAKER

• MODEL

• REGION

• SALE

• SALES_PRICE_RANGE

• SALE_MODEL

• SHOWROOM

• STYLE 2. Order the tables so that they are laid out in the same way as the illustration below.

3. Save the changes to the universe.



Defining joins in a universe After you have inserted more than one table in the schema, you need to create joins between

related tables. A join is a condition that restricts the resultset of a multi-relational query. Joins

are as important as tables in a schema because they allow you to combine data from multiple

tables in a meaningful way.


• Understand why you need joins in the universe structure

• Create joins

• Set join cardinalities

• Explain the join types

• View join expressions using List Mode

• Check the integrity of the universe structure and its joins

About joins and SQL WHERE clauses SQL specifies a join implicitly in a WHERE clause through a reference to the matching or common

columns of the tables. Normally there is one WHERE clause for each pair of tables being joined.

For example, if four tables are being combined, three WHERE conditions are necessary.

In BusinessObjects querying tools, if you run a query that involves inferring a SELECT statement

on two tables that have not been joined in the universe structure, the resulting report produces

a Cartesian product, that is, an illogical question resulting in illogical data, as illustrated below.

In other words, it outputs a report that joins every column in the first table to every column in

the second table.

To prevent this from happening, you need to specify a join between the tables in the Structure

pane in Designer.



Creating joins You have several approaches to creating joins in Designer:

• Defining joins manually in the schema

• Defining join properties directly in the Edit Join dialog box

• Using the Join SQL Editor to specify the join expression

Each of these approaches is described in detail below.

Defining joins manually in the schema

You can graphically create individual joins between tables by using the mouse to drag a line

from a column in one table to a matching column in another table.

Creating the join by defining properties You can also create a join by directly defining the join properties in the Edit Join dialog box.

To create a join by tracing manually 1. Click on any blank area of the Structure pane to deselect all tables.

2. Position the pointer over a column that you want to be one end of a join.

The pointer appears as a hand symbol. 3. Click and hold down the left mouse button.

The column is highlighted. 4. Drag the mouse to the column in another table that you want to be the other end of the join.

As you drag, the pointer changes into a pencil symbol.

5. Position the pencil symbol over the target column.

The target column is highlighted. 6. Release the mouse button.

The join between the two tables is created. Note that the definition of the join appears in the

Formula toolbar. 7. Double-click the new join.

The Edit Join dialog box appears showing the join properties.



Note: The properties that you can set for a join, including cardinality and join type, are

described later in this lesson. The Edit Join dialog box displays the default properties of the

join.

8. Enter and select properties for the join.

9. Click OK to close the Edit Join dialog box.

To create a join using the Edit Join dialog box

1. Select Insert ➤ Join from the menu, or click the Insert join button.

The Edit Join dialog box appears. 2. Select a table from the Table1 drop-down list.

The columns for the selected table appear in the list box under the table name. 3. Click the name of the column that you want to be at one end of the new join.

4. Select a table from the Table2 drop-down list box.

The columns for the selected table appear in the list box under the table name. 5. Click the name of the column that you want to be at the other end of the new join.

The join expression is dynamically built in the zones below and can be modified as necessary.

Note: The properties that you can set for this join, including the join operator, cardinality,

and join type are described later in this lesson.



6. Click OK.

The new join appears in the schema, linking the two tables and columns that you specified

in the Edit Join dialog box.

Note: Another method for inserting a join is to click the first table in the Structure pane,

hold down the Ctrl key, click the other table, and then click Insert Join. The two tables are

automatically entered in the Edit Join box and you can edit the join properties as required.

About join properties You can define the following properties for a join.

Property Description

Table1 Table at the left end of the join. Columns are listed for

the table selected in the drop-down list.

Table2

Table at the right side of the join. Columns are listed

for the table selected in the drop-down list.

Operator

Operator that defines how the tables are joined. The

operators available to a join are described in the

following section.

Outer Join

When selected, determines which table contains

unmatched data in an outer join relationship. Outer

joins are described fully in the following section.

Cardinality

When selected, allows you to define the cardinality

for the join. Defining and using cardinalities is

described in the following section.

Shortcut Join

Defines the join as a shortcut join. Shortcut joins are

described in the following section.

Expression

Join operators

WHERE clause used to restrict the data that is returned

when the two joined tables are included in a query.

This clause can be edited as necessary.

You can select an operator for a join from the drop-down list between the Table1 and Table2

boxes. The operator allows you to define the restriction that the join uses to match data between

the joined columns.

You can select the following operators for a join:

Operator Description

= equal to

!= not equal to



Operator Description

> greater than

< less than

>= greater than or equal to

<= less than or equal to

Between between (theta joins)

Complex

Editing the join expression

complex relationship

Use the Edit Join dialog box to define and edit join properties. You can also access the Join SQL

editor to edit join syntax directly from this dialog box.

The Edit Join dialog box also has two features available that allow you to edit and verify the

join syntax:

Edit The Edit button opens an SQL editor. Use this graphic editor to modify the syntax for tables,

columns, operators, and functions used in the join.

Parse The Parse button starts a parsing function that verifies the SQL syntax of the join expression.

If the parse is successful, you receive a result is OK message. If Designer encounters an error,

you receive an error message indicating the source of the problem.

Using the Join SQL editor You can use a graphical editor to directly modify the SQL expression for a join. You access this

editor from the Edit Join dialog box by clicking the Edit button.

To modify a join using the Join SQL editor

1. Double-click a join in the Structure pane, or click a join and select Edit ➤ Join.

The Edit Join dialog box appears. 2. Below the Expression text box, click the Edit... button.



The Join SQL Definition dialog box appears. The SQL expression for the join appears in

the text box.

3. Modify the SQL syntax as required.

You can use the following editing features to modify or add SQL syntax:

If you want to... Then...

Change a column at either join end Expand the table + box in the Tables and Columns

box and double-click on a new column name.

Change an operator used by the join

Double-click an operator in the Operators box.

Use a function in the join

Expand a function family + box and double-click on

a new function, or edit the SQL text directly.

The column, operator, or function appears in the join definition.

4. Click OK to validate your changes.

5. Verify that the join expression in the Expression text box has been modified.

6. Click OK to close the Edit Join dialog box.

Detecting joins Joins can also be created automatically. This procedure can be applied to multiple tables or, if

none are selected, all tables in the Structure pane.



Note: The automatic detection of joins assumes that all columns with matching names are to be

joined, and other columns will be ignored. This may not be appropriate, in which case it is better

to insert the joins manually.

To detect joins automatically 1. Click the table you want to select joins for.

Note:

You can select multiple tables by pressing the Shift key, and clicking each table. You can

also select all tables in a zone by clicking in an empty space, and dragging the cursor to

define a rectangular zone that includes any number of tables.

2. To detect the joins automatically:

• Select Tools ➤ Automated Detection ➤ Detect Joins.

• Click the Detect Joins button from the Editing toolbar.

A Candidate Joins dialog box displays listing all the joins detected. 3. Click the join or joins you want to accept in the Candidate Joins dialog box.

Note: You can accept and insert several joins at the same time using Shift-click or Ctrl-click.

4. Click Insert.

The join or joins are inserted in the Structure pane. 5. Click Close.

Setting join cardinalities Setting cardinality is a critical step in universe development. Cardinality is the term that refers

to the relationship between two tables based on a join, specifically how many rows in one table

will match those in the other. Whether or not cardinality is defined or how it is defined does

not directly impact the SQL that is inferred in universe queries. Rather, a universe designer

defines cardinality to benefit from powerful assistance from the Designer resolving-loops tool.

About cardinality Cardinality is the means by which Designer identifies the relationships between tables in the

universe structure. The cardinality can be:

• one-to-one (1-1)

• one-to-many (1-N)

• many-to-one (–1)

• many-to-many (N-N)



For example, a country can have many regions, so the relationship between a Country and a

Region table is 1-N.

Designer uses cardinality to detect and resolve loops.

Note: It is very important that all cardinalities are set correctly for loop and context detection. This

will be discussed in more detail later in this course.

You can choose to set cardinality manually or by using an automatic detection tool.

Setting cardinality manually or with the automatic detection tool Cardinality in universe design is based on a logical algorithm using a physical count. The

automatic detection tool only works properly if the database is populated with realistic data

in a completely normalized structure (for example, no multiple lookup tables or other tricks

that are sometimes applied by database administrators).

Also, it is important to understand that because the detection tool runs three queries on every

join, it can take a long time to complete the detection method. The cardinality detection tool

works by running the following queries:

• A count of the rows in each of the two tables that are joined (two queries)

• A count of the rows output when applying a query with the join specified in the WHERE clause

(one query) For these reasons, you are strongly advised to apply cardinality manually for efficiency and

accuracy.

When you set cardinalities manually, you must consider each individual join. This helps you

to become aware of potential join path problems in your schema.

You may not find these problems if you only select automatically detected cardinalities; for

example, isolated one-to-one joins at the end of a join path, or excessive primary keys where

not all columns are required to ensure uniqueness.

To set cardinality manually It is recommended that you systematically set the join cardinality when you first create a join,

using the following manual method.

1. Double-click a join, or click a join and select Edit ➤ Properties.

The Edit Join dialog box appears with the join expression already defined. In the center of

the dialog box is the Cardinality zone.



2. To set the cardinality manually, click the appropriate 1 and N option buttons in the

Cardinality zone.

Note: 1 = one end of join; N = Many end of join.

Tip: As you click the different options in the Cardinality zone, a message appears below

the buttons to describe the relationship between the tables, based on the settings you select.

3. Select the 1 or N radio button for Table1.

4. Select the 1 or N radio button for Table2.



5. Click OK to accept your changes and close the Edit Join dialog box.

Displaying cardinalities You can display cardinalities in the Structure pane using the following symbols:

Cardinality symbol Example Description

Arrow

Arity

Arrow indicates the “one”direction

of the join. If cardinality is 1,1 then

an arrow head is shown at each join

end. Crow‟s foot indicates the “many”

end of the join. If cardinality is 1,1,

then a straight line is shown.



Cardinality symbol Example Description

1,N

To display cardinalities

1. Select Tools ➤ Options from the menu bar.

2. The Options dialog box opens to the General page.

3. Click the Graphics tab.

The Graphics page appears.

Cardinality is shown as a ratio at

each end of the join.

4. Click the Arrow, Arity, or 1,n option.

5. Click OK to save the changes.



Detecting cardinality automatically You can set Designer to detect cardinality automatically as you insert joins, however it is

recommended that you use the manual method described previously, to ensure accurate results.

You can detect cardinality for a single join by selecting that join and clicking the Detect

Cardinalities icon in the Editing toolbar. This is due to the fact that, if the database is large,

running the cardinality detection queries for every join can take considerable time.

How is cardinality detected? To detect the cardinality of a join between two tables, the following three queries are run:

SELECT count (*)

FROM table1, table2

WHERE table1.column = table2.column

SELECT count (*) FROM table1 SELECT count (*) FROM table2.

The results of the three queries are then compared in an attempt to determine which query is

the end of the join with one entity and which is the end with many (if there is one).

To detect cardinality on a single join Cardinality can be detected on a single join using one of two methods.

1. Using the Edit Join dialog box:

a. Double-click the join in the Structure pane to open the Edit Join dialog box.

b. In the Cardinality zone of the Edit Join dialog box, click the Detect button.

c. Check the cardinality statement to make sure that the one-to-many relationship proposed makes logical sense.

d. Click OK to accept the proposed cardinality and close the Edit Join dialog box.

In the Structure pane, Designer applies the cardinality symbol to the appropriate end of

the join, based on the cardinality proposed by the detection tool.

2. Using the Detect Cardinality button:

a. Select the join.

b. Click the Detect Cardinalities button.

The automatic tool detects the cardinality of the join and applies the arity symbol to the

appropriate end of the join.

c. Check the arity symbols displayed between the tables to make sure that the one-to-many

relationship proposed makes logical sense.

d. Edit the cardinality proposed in the Edit Join dialog box if necessary.



Detect cardinality for all joins You can use the Designer feature Detect Cardinalities to automatically detect all joins in the

schema.

When using automatic cardinality detection, cardinalities are implemented automatically on

detection.

You should use automatic cardinality detection appropriately. It can be very useful to quickly

get all the cardinalities detected in the schema, however, there are a number of structural

problems inherent in many relational databases which can lead to incorrect cardinality detection.

To detect cardinality for all joins You can also detect cardinality all at the same time, although this is not a recommended

procedure to ensure accurate results.

1. Click the Structure pane background to ensure no join is selected.

2. Click the Check Cardinality button on the toolbar.

Note: Cardinality is detected by automatically running three subsequent queries at the

target database per join. You are therefore advised to avoid automatic detection of

cardinalities on large databases. Use the manual method whenever cardinality is known.

A message appears.

Designer requests confirmation because executing the detection tool takes a long time if it

is being applied to a large database.

3. If you are sure you want to use the automatic detection tool, click OK to detect the

cardinalities.

The system inserts the cardinality symbols on the many ends of the joins.



Designer offers yet another method for detecting cardinalities automatically:

1. Select Tools ➤ Options from the menu bar.

2. Click the Database tab.

3. Select the Detect cardinalities in joins check box.

4. Click OK.

Best practice for setting join cardinality As mentioned previously, there are three reasons why using the automatic detection tool to

set join cardinalities is not recommended:

• Cardinality is based on logic. It is logical that every country has more than one region; it is

not logical that a region may have more than one country. The automatic detection tool uses

physical cardinality, and runs a physical count on the values in both columns being joined.

You may get incorrect results if the physical count does not return the same result as a logical

analysis of the data.

• The algorithm used by the automatic detection tool assumes that you have sufficient quantity

of data in both tables to be representative in ratio to the database in a live environment. If

you are designing against a test database, for example, with only a representative sampling

of data, you could receive an incorrect answer because the tool runs a physical count.

• The automatic detection tool runs three subsequent queries against the target database per

join. You are, therefore, advised to avoid automatic detection of cardinalities on large

databases.



Join types

Join Type Description

Equi-join (default) (includes the complex equi-join)

Outer join

Link tables based on the equality between the

values in the column of one table and the

values in the column of another. Because the

same column is present in both tables, the join

synchronizes the two tables.

You can also create complex equi-joins, where

one join links multiple columns between two

tables.

Equi-join is the join type created by default

between two tables. Link two tables, one of which has rows that may not

match those in the common column of the other table.

Theta join (conditional join)

Link tables based on a relationship other than equality

between two columns, as in for example, a BETWEEN

join.

Shortcut join

Self-restricting join

Equi-joins

Join providing an alternate path between two tables,

bypassing intermediate tables, leading to the same

result regardless of direction. Optimizes query time

by cutting long join paths as short as possible.

Single-table join used to set a restriction on the table.

An equi-join is a restriction that conforms to the syntax set out below:

Table1.column_a = Table2.column_a

An equi-join is a join based on column values between two tables. In a normalized database,

the columns used in an equi-join are often the primary key from one table and the foreign key

in the other. A primary key of a relational table uniquely identifies each record in the table.

Primary keys may consist of a single attribute or multiple attributes in combination. A foreign

key is a field in a relational table that matches the primary key column of another table.

When a SELECT statement is run, the SELECT and FROM clauses are now properly defined and

prevent a Cartesian product.



Outer joins

An outer join is a join that links two tables, one of which has rows that may not match those

in the common column of the other table.

You define an outer join by specifying which table is the outer table in the original equi-join.

The outer table contains the column for which you want to return all values, even if they are

unmatched. You specify the outer table from the Edit Join dialog box for the selected join.

For instance, the example illustrated above shows the Country and Region tables from a

database. Note that there are three different values in the primary key of the Country table and

only two distinct values in the corresponding foreign key of the Region table. If you were to

apply an equi-join, the resultset of a query would only show information on US and UK.

However, you may wish to show all three countries irrespective of equivalent foreign key

values in the Region table. To achieve this, use an outer join.

In specifying an outer join in a standard SQL SELECT statement, you are required to identify

which of the two tables is the outer. Using straight SQL (as opposed to generating it using a

universe), the problem is that different RDBMS define outer differently and the syntax of the

statement also differs. For example, depending on the underlying RDBMS, the outer join may

be on the left or right.



In a universe, the outer join is always placed on the table that contains all the data. That is, on

Country in the example above. To do this, place a check against that table in the Edit Join dialog

box.

Tip: A good way to find out where to place your outer join is by reading the description that shows

up in the Cardinality zone. If you select the outer join check box for Country the description reads:

Each Country has ZERO or more Regions, AND each Region has one and only one Country.

When you check the outer join box for the Country table, you will retrieve all countries whether

they have a region or not.

Once this is done, the correct outer join is inferred when used in the generated query, and the

syntax is correctly inferred for the appropriate RDBMS (assuming you have the correct SQL

inference driver).

An outer join is shown by a small circle on the join line in the universe structure at the end that

points to the table that may have missing values.

Best Practice with Outer Joins It is recommended that outer joins be placed at the end of the flow of data, otherwise ambiguous

outer join errors may occur. Potentially, this could cause the SQL to try to match on the equality

of a NULL value, which it cannot do.

If you do place outer joins in the middle of a table path, the subsequent joins in the path may

also have to be made outer to avoid errors.



Always remember that outer joins may cause the query to run slower than a query with no

outer joins.

This problem can be resolved by using aliases and aggregate aware.

Theta joins A theta join is a “between-type” join that links tables based on a relationship other than equality

between two columns. It is used to demonstrate ranges, such as start date and end date, or

minimum and maximum. A theta join can use any operator other than the equal operator.

For instance, there is a table in the Motors database called Sales_Price_Range. This contains a

number of rows defining fixed price ranges by which you may wish to analyze data as illustrated

above.

To do this, the table needs to be included in the universe structure and a join set. The obvious

table to join it to is the Model table which includes the price of a model. However, there is no

common column between the Sales_Price_Range and Model tables so an equi-join cannot be

used. Instead you need to infer that a join exists where the value in a row of the Model_Price

column in the Model table is between the values in a row for the Price_Range_Min and

Price_Range_Max columns of the Sales_Price_Range table.

To create a theta join

To create a theta join using range columns:

1. Click the Insert Join button, or select Insert ➤ Join.

The Edit Join dialog box appears. 2. Select a table from the Table1 drop-down list.

The columns for the selected table appear in the list under the table name. 3. Click the column you want to join.

4. Select the a table from the Table2 drop-down list.



The columns for the selected table appear in the list under the table name. 5. Press and hold down the Ctrl key and click two columns from the Table2 column list box.

Note: The operand changes to Between automatically, and indicates that the join expression

is dynamically built as a Between syntax.

6. Click the Parse button to test for the validity of the join.

If you receive an error message, check to see that you have correctly selected the columns.

7. Set the correct cardinality.

8. Click OK.

The theta join now appears between the two selected tables.

Shortcut joins

A common use of shortcut joins is to link a shared lookup table to another table further along

a join path. The join path is comprised of several different tables in the same context.

A shortcut join is a join that provides an alternate path between two tables. It improves the

performance of a query by not taking into account intermediate tables, and shortening a normally

longer join path.

In such a case, the shortcut join is only effective when the value being looked up has been

denormalized to lower levels in a hierarchy of tables so the same value exists at all the levels

being joined.



In the Motors sample database you can apply a shortcut join from the Country table to the

Client table, bypassing the Region table. As there is already a join between Country and Region,

adding a new join between Country and Client will effectively create a loop. You can avoid

and solve this loop by using a shortcut join.

To create a shortcut join 1. Identify the two tables in a join path that can be linked directly.

2. Create a join between the two tables.

3. Double-click the new join.

The Edit Join dialog box appears. 4. Set the correct cardinality.

5. Select the Shortcut Join option.

Note: Note that this will not change anything in the operands or the expression field.

6. Click OK.

The shortcut join now appears as a dotted line between the two selected tables.

Self-restricting joins A self-restricting join is not really a join at all, but a self-restriction on a single table, usually a

transaction table. You can use a self-restricting join to restrict the results returned by a table

using a fixed value.



The table in the example above contains rows of data for cars both sold and rented. The sale

type column is used as a flag to indicate the type of transaction. Without the self-restricting

join, the results set of the query would produce rows where the sale type column is equal to

either car sales ('S') or car rental ('R'). With the self-restricting join expression set to sale type

equal to „S‟, any object based on the table or joins passing through that table would produce

query results covering only car sales.

To create a self-restricting join 1. Use one of the following methods to insert a join:

• Click on the Insert Join button.

• Select Insert ➤ Join.

The Edit Join dialog box appears. 2. Select the table from the Table1 drop-down list.

Select the table that you want to set the self restricting join against from the Table1 drop-

down list box.

The columns for the selected table appear in the list under the table name. 3. Click the column that you want to use to define the restriction from the column drop-down

list box.

4. From the Table2 drop-down list, select the same table that you selected from the Table1

drop-down list box.

5. Click the same column that you selected in the Table1 column list box.

The expression for the join appears in the Expression text box.

6. Replace the operand value in the join expression with the restriction value that you want

to set on the join column.

For example, if you want to restrict the returned values from the sale type column to car

sales values only, you replace SALE_TYPE after the = sign with 'S' as shown below:

Tip: This can also be done directly in the Expression field.



Note: It is recommend that you set the cardinality of a self-restricting join to 1:1. Otherwise,

when running detect contexts, you will get an error that not all cardinalities have been

detected.

7. Click OK

The self-restricting join now appears as an unconnected join line.

You can view the join expression underlying a join line or all the join expressions for a table

using List Mode as well as the Edit Joins dialog box.

List Mode

You can use List Mode to list the tables, joins, and contexts used in the active universe. In List

Mode, Designer adds three panes above the display of the Structure pane; tables, joins, and



contexts. You can view the join expression underlying a join line or all join expressions for a

table using List Mode as well as the Edit Joins dialog box.

To use List Mode 1. Click the View List Mode button.

After List Mode opens, you can view tables and join information and expressions in various

ways. For example:

2. Click a join in the graphical Structure pane.

The expression for the join is highlighted in the Joins pane in the List Mode. 3. Click a table in the Tables pane of List Mode, and click the arrow pointing to the Joins pane.

Only the joins for the selected table are shown in the Joins pane. 4. Clear the highlighted arrow to view all the joins and tables again.

5. Click the View List Mode button to return to normal view.

Note: Make sure you clear any arrows in List Mode before returning to normal view. The restricted

view of tables could interfere with operations that you perform in normal view, such as detecting

contexts.



Checking integrity Use the Check Integrity option to detect any errors in the structure and joins of a universe.

Be careful of checking cardinality automatically for all the reasons mentioned previously. As

a general rule, never select the Check Cardinalities check box when you are checking the

integrity of your universe.

To check the integrity of a universe 1. Click the Check Integrity button.

The Integrity Check dialog box displays:

2. Select check boxes for components to be verified.

3. Clear check boxes for components not to be verified

4. Click OK.

Designer checks the universe and displays the Integrity Check Results dialog box.

If there are no errors, click OK. Otherwise, you need to return to your Structure pane and

correct any errors as indicated in the Integrity Check Results dialog box.

Note: Some divergences in integrity results are acceptable.

Activity: Defining joins in a universe Objective

• Insert joins between tables in the Motors universe and set cardinalities.

Instructions 1. Insert the following equi-join using the drag-and-drop technique:



• COUNTRY.COUNTRY_ID to REGION.COUNTRY_ID

2. Set the cardinality for the join manually in the Edit Join dialog box.

3. Insert the following equi-join using the Edit Join dialog box and set the cardinality.

• REGION.REGION_ID to CLIENT.REGION_ID

4. Insert the following theta join and set cardinality.

• MODEL.MODEL_PRICE BETWEEN SALE_PRICE_RANGE.PRICE_RANGE_MIN AND SALE_PRICE_RANGE.PRICE_RANGE_MAX

5. Insert the following self-restricting join and set cardinality.

• SALE.SALE_TYPE ='S'

6. Check integrity for:

• Universe structure and joins 7. Notice the divergences found in the integrity check of the Motors universe. This is the result

of having un-joined tables.



8. Check that the following joins and cardinalities are included in the universe structure. If

not, add the remaining joins and cardinalities as specified in the table below:

Joins Type Cardinality

COUNTRY.COUNTRY_ID = REGION.COUNTRY_ID Equi 1:N

REGION.REGION_ID = CLIENT.REGION_ID Equi 1:N

MODEL.MODEL_PRICE BETWEEN

SALE_PRICE_RANGE.PRICE_RANGE_MIN AND

SALE_PRICE_RANGE.PRICE_RANGE_MAX

Theta

N:1

SALE.SALE_TYPE ='S' Self 1:N

CLIENT.CLIENT_ID = SALE.CLIENT_ID Equi 1:N

SHOWROOM.SHOWROOM_ID = SALE.SHOWROOM_ID Equi 1:N

SALE_MODEL.MODEL_ID = MODEL.MODEL_ID Equi N:1

MODEL.STYLE_ID = STYLE.STYLE_ID Equi N:1

MODEL.MAKER_ID = MAKER.MAKER_ID Equi N:1

SALE_MODEL.COLOUR_ID = COLOUR.COLOUR_ID Equi N:1

SALE.SALE_DATE BETWEEN

FINANCE_PERIOD.FP_START AND

FINANCE_PERIOD.FP_END

Theta

N:1

SALE.SALE_ID = SALE_MODEL.SALE_ID

9. Save the changes to the universe.

Equi 1:N



Quiz: Building the universe structure 1. A schema contains two elements. What are they?

2. What are three reasons why using the automatic detection routine for setting join cardinalities

is not recommended?

3. What type of join is created by default between two tables?

Building the Universe Structure-Learner's Guide 87


Lesson summary


• Populate the universe structure

• Define joins in a universe

Creating Dimension Objects—Learner’s Guide 89


Lesson 4

Creating Dimension Objects

Lesson introduction This lesson describes how you can create classes and objects that are used by end users to run

queries and create reports.


• Describe classes and objects

• Create classes and objects



Classes and objects Because universes are made up of objects and classes, it is important to understand exactly

how each of these elements is used.


• Explain what universe objects are

• Explain what universe classes are

Classes

Within a universe, objects are grouped into classes. This is done to provide a structure for the

universe and makes it easier for users to locate particular objects. The strategy most often

employed is to group related dimension and detail objects into one class and place measure

objects into a unique and single-measures class.

This strategy can be extended by introducing subclasses to break down the objects into further

subsets.

Each object in a universe must be contained within a class. You can create new classes and edit

the properties of existing classes. Classes are represented as folders on a tree hierarchy in the

Universe pane.

In Universe Designer, you can qualify an object as being one of three types:

Object qualification Examples Description

Focus of analysis in a query. A

dimension maps to one or

Dimension more columns or functions in

the database that are key to a

query.

Detail

Provides descriptive data

about a dimension. A detail is

always attached to a

dimension. It maps to one or

more columns or functions in

the database that provide

detailed information related to

a dimension.



Object qualification Examples Description

Contains aggregate functions

that map to statistics in the

Measure database. These are the metrics

by which you want to compare

dimensions.

Dimension objects, where possible, tend to be organized hierarchically within a class. This is

important if you intend to make use of default hierarchies for drilling. Detail objects are

organized below their associated dimension objects.

Note: Detail objects cannot be included in a drill path.

Measure objects may be grouped in a separate class. This makes them easier for the user to

find and also emphasizes the fact that they can be used with any dimension or detail object.

Note: Only dimension objects can be merged to synchronize queries from multiple data sources in

end-user querying tools.

Objects In Business Objects products, an object is a named component in a universe that represents a

column or function in a database.

In Universe Designer, objects appear as icons in the Universe pane. Each object represents a

meaningful entity, fact, or calculation used in an end user‟s business environment. The objects

that you create in the Universe pane in Universe Designer are the objects that end users see

and use in the Business Objects end-user querying tools.

For example, in the Web Intelligence Rich Client Query Panel, users drag objects from the Data

tab into the Result Objects pane to run queries and create reports that display the data returned

by the query.

Each object maps to a column or function in the target database, and when an object is selected

in the Query Panel, the object infers a SELECT statement. When multiple objects are combined,



a SELECT statement is run on the database which includes the SQL inferred by each object and

a default WHERE clause.

As a universe designer, you use Universe Designer to create the objects that end users select

to build and run their queries.

You can also create objects for use only in Universe Designer, so that they are hidden in the

Business Objects end-user querying tools.



Creating classes and objects After defining classes and objects, the next step is to understand how to employ these elements.


• Create a class

• Create objects

• Create classes and objects automatically

• Create classes and objects by copy and paste from another universe

• Edit object parameters

• Check integrity

• Test the objects in Web Intelligence Rich Client

Creating classes

There are two ways to create a class in the Universe pane:

• Manually defining a class.

• Automatically by dragging a table from the Structure pane into the Universe pane.

To create a class 1. Click the existing class below which you want the new class to appear.

Note: If this is the first class you are creating, ignore this step.

Note: If you create a class when an object within a class is highlighted, you will create a

subclass within that class.

2. There are three ways you can insert a class:

• Click the Insert Class button from the Editing toolbar.

• Select Insert ➤ Class.

• Right-click in the Universe pane and choose Class from the right-click menu. 3. The Edit Properties dialog box displays.

4. In the Class Name field, enter a name.

5. In the Description field, enter a description of the class content. Use business language that

is meaningful to the users in your description for when they review it. Avoid technical

database language.



6. Click OK.

To manually create an object 1. Click the class in which you want the new object to be placed.

2. There are three ways you can insert an object:

• Click the Insert Object button from the Editing toolbar.

• Select Insert ➤ Object from the menu bar.

• Right-click the class and choose Object from the right-click menu.

The Edit Properties dialog box for the object appears.

3. In the Definition tab.



Ensure that object names are always expressed in the end user business vocabulary. This

name may be different from the actual column names that the object is associated with in

the database schema.

4. Type a SELECT statement in the Select box, or click the >> button to use the SQL editor.

5. Click the Properties tab and select object properties.

6. Click OK.

Automatically creating classes and objects from a table You can also create classes and objects simply by dragging the entire table from the Structure

pane into the Universe pane in Universe Designer. This is particularly useful if you are sure

that you want all the columns in the table to correspond to objects in the universe.

Note: The class is automatically populated with a dimension object for every column in the table.

It is not advisable to do this because you are creating a universe based on the database structure,

not on the requirements of the users.

You can create an object automatically by selecting a column in a table in the Structure pane

and dragging it to the Universe pane. An object is created under the nearest class to the point

where you drop the column. The default name for the object is the column name.

You should edit the new object properties to ensure that it is appropriately named, and is

relevant to end-user needs. Whenever you create an object automatically, edit the properties

of the object to:

• Change the name where appropriate.

• Enter a description.

• Change the object qualification from the default where necessary.

• Alter or remove the associated list of values settings where appropriate.

• Change other settings as required.

To automatically create an object from a column

1. Click a table column in the Structure pane.

2. Drag the column across to the Universe pane and drop the table at the desired position in

the class hierarchy. The column must be dropped under an existing class.

A new object appears in the hierarchy.

Defining a new object as a detail object

The Properties tab in the Edit Properties dialog box allows you to define the object qualification.

An object can be qualified as a dimension, detail, or measure object.



A detail object provides descriptive data about a dimension, and is always attached to a

dimension. It maps to one or more columns or functions in the database that provide detailed

information related to a dimension.

To define an object as a detail object 1. Double-click an object.

The Edit Properties dialog box for the object appears.

2. Click the Properties tab.

The Properties tab of the Edit Properties dialog box appears. 3. In the Qualification zone, select the Detail button.

The Associated Dimension field appears in the Qualification zone.

4. Click the Associated Dimension field, and from the drop-down list of available dimension

objects, select the one with which this detail object is to be associated.

5. Click OK to confirm the change.

Working with classes and subclasses A subclass is a class within a class. You can use subclasses to help organize groups of objects

that are related. A subclass can itself contain other subclasses or objects.

Note: It is recommended that you do not create too many levels of subclasses (more than three).

Too many levels make it difficult for users to find the objects they need.



To create a subclass 1. Right-click the class in which you want to create a subclass.

The drop-down menu appears.

2. Choose Subclass.

The Edit Properties dialog box displays. 3. In the Class Name field enter the name of the subclass.

4. Click OK.

The Universe pane should look similar to:

To delete a class or a subclass 1. There are two ways to delete a class, or subclass:

• Click the class, or subclass that requires deletion. Press the Delete key.

• Right-click the selected class, or subclass. Select the Clear option from the drop-down

menu.

Editing the object properties The following example shows the properties of the dimension object, called Client Name.



As the object is currently defined, there is no SELECT statement defined to reference the Client

table. You need to edit the definition of the SELECT statement so the Client Name object returns

the complete client name using the appropriate columns from the Client table.

Note: The example above shows a concatenation of two columns. Depending on the RDBMS used

the syntax can vary. Consult the documentation provided by your database vendor to see what

types of concatenation functions are supported.



To edit the object definition 1. Double-click the object that you want to edit.

2. In the Definition tab, type in the Name field if you want to edit the object name.

3. Click the Type arrow, and from the drop-down list, select the appropriate data type for the

database column, or columns that the object references.

4. Click the Description text box and type help text for the end user.

This text appears in Business Objects end-user querying tools when a user selects the object

to build a query. The text describes the data returned when the user adds this object to a

query.

5. Click the Select text box and enter the SELECT statement that will be inferred when a user

builds a query using this object.

This can be done in one of two ways:

• Type the SELECT syntax in the Select field to define the columns that will be referenced.

• Click the >> button to open the Edit Select Statement dialog box as displayed below.

The Edit Select Statement dialog box appears.

It is normally best to use the latter method because it enables you to specify most of the

SELECT syntax from pick lists in the lower half of the screen by double-clicking the item

required. This minimizes typing and averts syntax errors due to typing mistakes.

6. Create the SELECT statement so the object references the appropriate table columns.



Note: You can use the fields below the text box to select the columns, operators or functions

you need to use to enter the required SQL syntax.

7. Click the Parse button to validate the statement syntax.

8. Click OK to close the Edit Select Statement dialog box.

The Edit Select Statement dialog box closes and the Definition tab of the Edit Properties

dialog box displays the SQL statement in the Select text box.

Edit Properties: Properties

The Properties tab in the Edit Properties dialog box allows users to:

1. Select one of the object types in the Qualification zone.

Note: By default, the object type selected will be either a dimension or measure dependent

on the data type chosen on the Definitions tab.

Dimension=Character, Date or Number

Measure=Selected by default when there is an aggregate function in the SELECT clause

Note: The Detail qualification check box will be grayed out if no dimension objects exist to

which to attach a detail object.

2. Select the appropriate options in the Associate a List of Values zone.

What is a list of values? When you create an object, Universe Designer automatically associates a list of values (LOV)

with the object. The LOV is not created until a user or the universe designer chooses to display

a list of values for the object in the Query Panel. A SELECT Distinct query is then run against

the column or columns inferred by the object.

The returned data is stored in a file with an .lov extension in the universe subfolder created

under the same folder that stores the universe file. The .lov file is then used as the source for

values for the list. This allows the SELECT Distinct query to be run only once for an object.

When do you use a list of values? A list of values should only be used with an object if it will provide something useful for the

user. LOVs are very useful where there is a limited set of distinct values for the database

columns underlying the object.

Note: If the object is likely to refer to a large number of distinct rows in the database, it is

advisable not to associate an LOV or change its configuration to avoid performance issues.

Setting LOV options In the Associate a List of Values zone, the Display button allows you to view all the values in

the database returned by this object.



To restrict the object so that some of the values are not returned when an end user uses this

object in a query, you can click the Edit button to create a filter (or condition) in the Query

Panel that appears.

Edit Properties: Advanced The Advanced tab allows you to set the security access level of the object and how it can be

used in a query or in a report. You can select a security level which restricts use of the object

to users with the appropriate security level.

In the Security Access Level zone you can assign the following security access levels:

• Public

• Controlled

• Restricted

• Confidential

• Private

If you assign Public then all users can see and use the object. If you assign Restricted, then

only users with the user profile of Restricted or higher can see and use the object.

In the Can be used in zone, select one of the following options to define how this object can

be used in a query:

• The Result check box - use this object to return results in a query.

• The Condition check box - use this object to apply a condition or query filter in a query.

• The Sort check box - specify the object in the ORDER BY clause of a SELECT statement.



Note: This option can increase the processing speed of a query. However, in certain edited

LOV situations, it is not useful to sort at query level because block-level sorting overrides

any row order of data that is stored in the microcube.

Edit Properties: Keys The Keys tab allows you to define index awareness for an object. Index awareness is the ability

to take advantage of the indexes on key columns in the database to speed data retrieval.

The objects that you create in Universe Designer are based on database columns that are

meaningful to an end user. For example, a Customer object retrieves the field that contains the

customer name. In this situation, the customer table typically has a primary key that is not

meaningful to the end user, but which is very important for database performance. When you

set up index awareness in Universe Designer, you tell Universe Designer which database

columns are primary and foreign keys. This can have a dramatic effect on query performance.

In the example below, primary and foreign keys have been defined on the Client Country

object. The complete WHERE clause for the primary key is:

COUNTRY.COUNTRY_ID = CLIENT.COUNTRY_ID

If you then use Country and the Client Name object in a query, the query will not need to

reference the Country table in the database; the Country data will be taken from the Client

table directly.



Edit Properties: Source Information For universes generated from Data Integrator, technical descriptions and formulas used to

calculate target tables from source tables are displayed in this tab.

You can specify the following types of information in the Source Information tab:

• Technical information: Technical descriptions that are available in universes generated from

Data Integrator.

• Mapping information: The mapping applied within Data Integrator between the source

tables and the target tables. The goal is not to provide the expression of the mapping, but

to display it as a descriptive comment to inform the user of the source columns used in the

object definition.

• Data Lineage information: List of source columns involved in a target column. This

information facilitates the impact analysis through Data Integrator and Web Intelligence

reports.

It is possible to copy objects from one universe to another. This is useful if you want to create

objects that are similar to those already existing in another universe. You can copy those

objects or classes of objects and edit them as required.

Note: When you copy an object from one universe into another, be sure to validate the

object definition against the new universe structure and data source connection.



Copying and pasting objects It is possible to copy objects from one universe to another. This is useful if you want to create

objects that are similar to those already existing in another universe. You can copy those objects

or classes of objects and edit them as required.

Note: When you copy an object from one universe into another, be sure to validate the object

definition against the new universe structure and data source connection.

To copy and paste objects 1. Open the universe from where you want to copy objects.

2. Select the object(s) you want to copy.

3. Click copy from the standard toolbar.

4. Open the universe to which you want to copy the objects.

5. Click paste from the standard toolbar.

Find and replace The Find and Replace functions can be very useful when editing. You can use the Find function

to locate character strings in objects and their definitions.

You can also use the Find function in conjunction with the Replace function to edit strings.

To find a string 1. Ensure the Universe pane of the Universe Designer window is active.

Note: If the Structure pane of the universe is active, the Find function searches for table

names containing the specified string.

2. Click Find from the standard toolbar.

The Find/Replace dialog box opens.



3. Enter the character string for which to search.

4. Select the check box options as required.

5. Click Find Next. The appropriate object or part of the object definition will be displayed

and the string will be highlighted.

6. To move to the next instance of the string, click Find Next or click the Find Next icon.

To replace as you find 1. In the Find/Replace dialog box, select the Replace tab.

2.

Enter the string to search for in the Find What field and the string with which it is to be

substituted in the Replace field.

3. Select the check box as required.

4. Click Find Next.

5. Click Replace and then move to the next instance of the string by either clicking Find Next

or the standard toolbar option.

Checking object integrity Always check the integrity of your universe after defining classes and objects.

Use the Check Integrity option to detect any errors in the SQL syntaxes used in the created

objects.

Note: Ensure that the Check Cardinalities box is cleared. With a large database, this will save time

running the integrity check.

To check object integrity 1. Click the Check Integrity button.



The Integrity Check dialog box displays.

2. Select the Parse Objects check box.

3. Click OK.

4. Universe Designer checks the universe and displays the Integrity Check Results dialog

box.

5. Identify the reason for any reported errors and resolve them.

Viewing parent tables You can view the table in the Structure pane that is used in an object definition from the

Universe pane. This can be useful to quickly identify a table used by an object when object

names do not easily indicate a specific table.

To view associated tables of an object 1. Right-click the object.

2. Select the View Associated Table option.

The associated tables of the object will be highlighted in the Structure pane and the list

mode display (if open).

To view associated objects

1. Right-click any table.

2. Select the View Associated Objects option.

3. The associated objects of the selected table will be highlighted in the Universe pane.



Testing objects As you create objects in the universe, test them in Business Objects end-user querying tools by

building and running queries. There are three things you need to test:

• Do the objects exist? If not, you may have forgotten to save and export your universe since

the object you are testing was created.

• Does the SQL appear correct?

• Are the results of the query correct?

Remember that you must also test the joins already created in the structure.

Activity: Creating and testing classes and objects Objective

• Create and test classes and objects.

Instructions In this workshop you will create classes, subclasses and dimension and detail objects in the

Motors universe and then test the universe‟s objects and joins.

1. Create the following class:

• Client 2. Create the following class and subclass:

• Car

• Sale Prices (subclass of Car) 3. Create a Client Name dimension object manually with the settings:

• Type = Character

• Description = Last name, First name

• SELECT =

CLIENT.CLIENT_LASTNAME + ', ' +

CLIENT.CLIENT_FIRSTNAME

• Associate an LOV

4. Create a Client ID detail object automatically with the settings:

• Type = Number

• Description = Unique Client ID Number

• SELECT =

CLIENT.CLIENT_ID

• No Associated LOV

5. Check the integrity of the objects.

6. Create a Showroom class.



7. Create objects for each of the classes as identified in the tables below. Some of the properties

for each object have been specified for you. However, you will have to determine the data

type, qualification, and whether or not an LOV should be associated with each object.



Car class

Object Name SELECT Statement Object Description

Maker

MAKER.MAKER_NAME Car Manufacturer

Category of Car

STYLE.STYLE_NAME

The style group into which

a car fits (for example,

coupe, 4x4)

Model

MODEL.MODEL_NAME +' ' +

MODEL.MODEL_TRIM +' ' +

MODEL.MODEL_ENGINE

Model name, trim, and

engine size

Sale Prices class (a subclass of Car)

Object Name

Price Range

Model Price

SELECT Statement

SALES_PRICE_RANGE.PRICE_RANGE

MODEL.MODEL_PRICE

Object Description

Description of price range

banding Manufacturer recommended

retail price

Showroom class

Object Name

Showroom Town

SELECT Statement

SHOWROOM.SHOWROOM_TOWN

Object Description

Town in which

showroom exists

Showroom SHOWROOM.SHOWROOM_NAME Name of showroom

Showroom Address

Client class

SHOWROOM.SHOWROOM_ADDRESS Address of showroom

Object Name

Country

Region

SELECT Statement

COUNTRY.COUNTRY_NAME

REGION.REGION_NAME

Object Description

Country in which client

resides

Region of country in which

client resides

Area

Client Town

CLIENT.CLIENT_AREA

CLIENT.CLIENT_TOWN

Area of Region in which

client resides (for example,

county or state)

Town or city in which client

resides



Object Name

Client Address

SELECT Statement CLIENT.CLIENT_ADDRESS

Object Description

Address of client

Area Code CLIENT.CLIENT_AREA_CODE Postal or Zip Code

Phone Number CLIENT.CLIENT_PHONE_NO Phone number of client

Client ID CLIENT.CLIENT_ID Unique Client ID Number

8. Modify the properties of the following objects so that they are qualified as detail objects,

and associated with the Client Name dimension object:

• Client Address

• Area Code

• Phone Number 9. Modify the properties of the Showroom Address object so that it is qualified as a detail

object, and associated with the Showroom dimension object.

10. Create a class called Sales and two subclasses in the Sales class:

• Sales Details

• Sales Dates

Sales Details class (a subclass of Sales)


Invoice ID Number SALE.SALE_ID Unique Invoice ID Number

Sales Dates class (a subclass of Sales)


Sale Date SALE.SALE_DATE Date of sale

11. Drag the FINANCE_PERIOD table from the Structure pane and drop it in the Universe

pane.

Note: Delete the FP_Start and FP_End objects that are automatically created.

12. Edit the objects that have been created automatically in the new Finance class, according to

the table below.



Financial Period class


Financial Year FINANCE_PERIOD.FP_YEAR For example, FY03-04

Financial Quarter FINANCE_PERIOD.FP_QUARTER For example, Q1

Financial Month FINANCE_PERIOD.FP_MONTH For example, Month 01

13. Make sure you have defined each object using the appropriate object type.

The Universe pane in Universe Designer appears like this:

14. Save the universe.

15. Check the integrity of the objects, and make any alterations required.

Note: Test the validity of the joins also.

16. Test the universe by building queries in Web Intelligence Rich Client using the new objects.



17. Launch Web Intelligence Rich Client via Start ➤ Programs ➤ BusinessObjects XI 3.0 ➤

BusinessObjects Enterprise ➤ Web Intelligence Rich Client.

18. Log onto Web Intelligence Rich Client with the User name administrator.

19. Select the create a new document based on a data source icon.

Select Browse for more data sources.

20. In the Data source selection menu select Universe, and click Next.

21. Select the Motors universe, and click OK. 22. Build a new query using the objects you have created. Drag and drop the objects into the

Result Objects pane.

23. Click Run Query to view the final results displayed in the report.



Quiz: Creating dimension objects 1. Which of the three types of objects contain aggregate functions that map to statistics in the

database?

2. When you are testing objects, what are the three things for which you need to test? 3. If each object maps to a column or function in a target database, when used in a query, what

kind of statement does the object infer?



Lesson summary


• Define classes and objects

• Create classes and objects

Creating Measure Objects—Learner’s Guide 121


Lesson 5

Creating Measure Objects

Lesson introduction This lesson describes how to create measure objects and test that they produce the correct

results when used in queries.


• Explain measure object concepts

• Create measure objects

• Create delegated measure objects



Measure object concepts After completing this unit, you will be able to:

• Define measure objects

• Determine levels of aggregation

Defining measure objects A measure object returns numeric information. Measure objects are very flexible because they

are semantically dynamic. This means that the values they return in a query will vary depending

on the dimension and detail objects that are used with them.

You can see from the illustration that two separate queries, using the same Sales Revenue

measure object, but different dimension objects, results in the measure returning different

values.

You create a measure object by using an aggregate function in the SELECT definition of the

object. The five basic aggregate functions are:

• Sum

• Count

• Average

• Maximum

• Minimum

A measure object returns numeric data from the database that aggregates up or down according

to the dimension objects in the query. The most regularly used aggregates are listed above.

However, there are others that can be used. The full set of aggregate functions is held in the

Number Functions pick list of the Edit Select Statement dialog box.

How a measure infers SQL When a query uses a measure object with a dimension or detail object, the query definition

automatically infers a GROUP BY clause in the SELECT statement.



Inference of the GROUP BY clause is dependent on the SQL rule: When the SELECT clause line

contains an aggregate, everything outside of that aggregate in the clause must also appear in

the GROUP BY clause.

That is why dimension and detail objects must not contain aggregates. Any dimension or detail

that is used in the same query as a measure object will always be included in an inferred GROUP

BY clause.

When a query includes only a measure, the SQL inferred is the same as when the query uses

a dimension object:

• The SELECT clause shows the object selected in the query with the syntax including the

aggregate function.

• The FROM clause shows the tables involved in the measure object syntax.

• The WHERE clause identifies the joins among the tables involved.

The query result shows one row of the total revenue value.

In this example, the query includes only the Sales Revenue measure so the inference engine does not include a GROUP BY clause in the SQL statement.

When a query uses at least one dimension or detail object and a measure, the inference engine

includes a GROUP BY clause with all the objects except the measure in the SQL Statement:

• The SELECT clause shows the object(s) and measure selected in the query with the syntax

including the aggregate function.

• The GROUP BY clause includes all the objects except the aggregate. In this example, the query includes the Sales Revenue measure and the Country object so the

inferred SQL statement includes a GROUP BY clause with the Country.



In this example, the query includes two dimensions (Country and Region) so the inference

engine includes both dimensions in the GROUP BY clause. As a result, the values returned for

the Sales Revenue measure object are aggregated to a lower level, the Region. This mechanism

in the inference engine allows the measure objects to adapt dynamically to other, associated

objects.

The Query Process How do the Business Objects end-user querying tools process the measure object in a query,

and how do the values get projected?

There are two levels of aggregation in the query process:

• Aggregation at SELECT level

• Aggregation at projection level



Aggregation at SELECT level Aggregation at SELECT level occurs first in the query process:

• The user creates a query.

• Web Intelligence Rich Client defines the SQL from the query and sends a SELECT statement

to the target database.

• The data is returned to the microcube. The first level of aggregation now takes place in the

microcube.

• The results are projected in the query. The microcube projects the aggregated data onto the

report, the SQL statement is inferred against the database, and the results are returned to

the microcube.

Aggregation at projection level

When you run a query, the resultset of the SELECT statement is stored in the microcube. All

data then held in the microcube is projected into a block (the table or chart in the report).

Therefore, because data is projected from the lowest level held in the microcube, no projection

aggregation takes place.



However, when you edit the table, for example, by removing a column, and therefore project

only partial data from the microcube, aggregation is required to show measure values at a

higher level. The data in the microcube remains unchanged.

For instance, if you do not project the region data into the block, the four rows related to USA

need to be reduced to one to show the overall Sales Revenue for that country. In this instance,

a sum aggregation is required.

When projecting all variables in the microcube, no aggregation takes place.

When projecting only some variables from the microcube, aggregation occurs.

Projection aggregation is separate from SELECT aggregation and depends on how you define

the measure object properties when you create the measure object using Universe Designer.

Setting selection and projection aggregates Statistically, only certain SELECT and projection aggregates are compatible.

SELECT Aggregate Recommended Projection Aggregate

• Sum

• Count

• Average

• Maximum

• Minimum

• Sum

• Sum

• None

• Maximum

• Minimum

For the reports to present statistically correct results for a measure object both at query and

projection level, the SELECT and projection aggregates need to complement each other.

However, as a universe designer, if you configure a measure differently, the Business Objects

end-user querying tools will not stop you.

Note: With the exception of Average, the correct projected aggregate is selected by default. When

you set the SELECT syntax to Average, for example Avg(SALES.SALES_TOTAL), the projection

aggregation for this object would automatically be placed as a SUM. This would need to be changed

manually to NONE.



Creating measure objects After completing this unit, you will be able to:


• Test measure objects in Web Intelligence Rich Client

Measure objects You create measure objects in the same way that you create a dimension or detail object. They

can be created using the automatic or manual method.

It is recommended that you group measure objects together in separate classes from dimension

and detail objects, if they are generic. In other words, if they can be used in the same query as

any dimension and detail object in the universe, then they are considered generic, and you

must group them in separate classes.

If they are only compatible with certain objects, however, then you may want to place them in

the same class as those objects, to indicate this fact to the report designers.

It is important to remember the following when you create measure objects:

In the Definition tab • The Data Type field must be set to Number.

• The Select field must include an aggregate function. Tip: It is best to use the Select Edit dialog box to insert the SELECT clause content of a measure

as you can then use the Function and Columns pick lists.

Note: When an aggregate function is used in the Select Edit dialog box, the qualification is

automatically set to Measure type.

In the Properties tab • The qualification must be set as a Measure type.

• In the Function field, make sure the function you use is compatible with the aggregate used

in the SELECT statement.

• A measure object should not have a list of values associated with it. Therefore, the Associate

a List of Values check box should be unchecked.



Testing measure objects When you test a measure, you must be far more rigorous in your checks than with a dimension

or detail object. This is because you have to check that the values of the measure aggregate

correctly both at SELECT and projection level.

The three elements to testing a dimension or a detail object are:

1. Check that the objects exist. 2. Check the inferred SQL.

3. Check the query results.

For measure objects, the additional elements are:

• Repeat with the other dimensions.

• Make a query with a minimum of two dimensions and a measure.

• To validate the accuracy of the measure aggregate, it is recommended that you test it with

at least three separate queries.

Testing measures at SELECT level To test the inferred SELECT statements for a measure object, you must make at least two separate

queries using different dimension objects to produce different levels of aggregation. Three or

more queries are preferable.

In each instance, you must check the following:

• The inferred SQL of the query



In particular, you should check the GROUP BY clause has been inferred correctly.

Note: If it has not been inferred at all, it is likely that you have set a calculation and not an

aggregate in the Select field of the measure object properties.

• The results of the query

Check that the query produces the correct results.

Testing measures at projection level To test for projected aggregation, you need to build a query containing at least two dimension

objects, as well as the measure object you are testing. This allows you to project from other

than the lowest level of data held in the microcube and therefore test aggregation.

Activity: Creating and testing measure objects Objective

• Create and test measure objects.

Instructions 1. Create the following subclass in the Sales class:

• Sales Figures

2. Create a Sales Revenue measure object with the settings:

• Type = Number

• Description = Total Sale Invoice Revenue

• Select statement =

SUM(SALE_MODEL.SALE_QTY * MODEL.MODEL_PRICE *

((100 - SALE.SALE_SALE_DISCOUNT) / 100))

• Function = SUM

• No associated LOV



3. Save and export the universe.

This allows you to test the Sales Revenue object in Web Intelligence Rich Client. 4. Log onto Web Intelligence Rich Client.

You will test the Sales Revenue object by running three queries. 5. Create a new query based on the universe you just exported, containing the Sales Revenue

object.

Note the value returned. 6. Test the Sales Revenue measure object by creating a second query, using the following steps:

a. Edit the query created in the previous step, and click Add Query.

b. Select the Motors.unv.

c. Create a new query with Country and Sales Revenue.

Check the SQL and note the GROUP BY clause. It should contain the SQL for the Country

object.

d. Click Run Queries.

Note: You will be prompted to select a way to display the new query. You can leave the

default option to add a new tab to the report or you can select the option to display the

table in the current report.

e. Apply a SUM calculation to the Sales Revenue column in the new projected block. Does

the sum match the value shown in the first table? Note the value of the Sales Revenue

in a row of the block (for example, USA).

7. Test the Sales Revenue measure object by creating a third query, using the following steps:

a. Edit the second query and then click Add Query.

b. Create a new query with Country, Region, and Sales Revenue.

c. Check the SQL and note the GROUP BY clause. It should now contain the SQL for the

Country and Region objects. Click Run Queries.

d. Apply a break to the Country column and apply the sum calculation to the Sales Revenue

column of the new projected block. Does the Country group sum match the value of the

noted block row in the second table (for example, USA)?

e. Edit the query. Change the projection to the block from the microcube by removing the

Region column from the block. Does it aggregate to Country level correctly?

f. Edit the query again. Change the projection to the block from the microcube by removing

the Country column from the block. Does it aggregate to the total Sales Revenue level

correctly?

g. Edit the query again. Add the Showroom and Maker objects.

h. Using drag and drop, insert two new tables, one to show Showroom and Sales Revenue,

and the other to show Maker and Sales Revenue, and apply a sum to both tables. Note

the total values remain the same. The final version of the report should look similar to

this:



8. In Universe Designer, create the following measure objects in the Sales Figures subclass

and test them.

The SQL code for the SELECT properties of each object has been specified for you. However,

you will have to determine the appropriate projection function aggregate.

Object Name Select Statement Object Description

Cost of Car Sales

Number of Cars Sold

SUM(SALE_MODEL.SALE_QTY * MODEL.MODEL_COST)

SUM(SALE_MODEL.SALE_QTY)

Total Cost of Car Sales

Total Number of Cars

Sold

9. Create the measure objects listed below.

• In the Car class and Sale Prices subclass: Lowest Priced Value based on Manufacturers

recommended retail price.

• In the Car class and Sale Prices subclass : Highest Priced Value based on Manufacturers

recommended retail price.

• In the Client class: Number of Clients. 10. Save and export the universe.

11. Test the new objects in Web Intelligence Rich Client.



Delegated Measures The XI 3.0 release of Universe Designer allows designers to create measures whose calculation

is delegated to the database. These are called "delegated smart measures".


• Explain what the delegated measure is and how it works

• Understand how you benefit from using delegated measures

• Know how to use delegated measures appropriately

• Apply best practices when using delegated measures

What is a delegated measure?

A delegated measure is a measure that delegates its aggregation calculation to the database.

The universe designer defines a delegated measure in the universe to make it available to report

users for ad hoc reporting or for viewing reports built on that universe.

A universe designer can create a delegated measure when conventional Web Intelligence or

Web Intelligence Rich Client aggregation does not provide an accurate result for the measure,

such as for:

• Complex averages, such as Weighted averages (an average of a percentage).

• Ratios.

• Other measures that do not aggregate along all the dimensions in a report.

• OLAP sources where measure aggregations are already available in the OLAP cube.

The delegated measure is then available to report designers in Web Intelligence and Web

Intelligence Rich Client.

Delegated measures are available for all relational and OLAP data sources.

The benefits of delegated measure The delegated measure represents an extension of Web Intelligence and Web Intelligence Rich

Client calculations by supporting aggregation within the database and makes non-additive

measures available within the universe.

You benefit from delegated measures because they:

• Increase Web Intelligence and Web Intelligence Rich Client querying efficiency.

• Make non-additive measures available within the universe.

• Use database-specific syntax to improve performance and provide optimization on the

internal architecture of all vendors.

• Extend support of calculations beyond Web Intelligence and Web Intelligence Rich Client

documents.



How does the delegated measure work? By default, Web Intelligence and Web Intelligence Rich Client calculate measures based on the

objects used within the query. The dimensions used in the query are called a grouping set.

The delegated measure calculates the aggregation of the measure for any subset of dimensions

required in the report.

For example, a query that retrieves the dimensions Country, Region, Maker, Year, Number of

Cars Sold and Average Sales Total would, by default, calculate the Number of Cars Sold and

Average Sales Total for that grouping set.

However, when you format your report, if you want to present the Number of Cars Sold and

Average Sales Total for Region and Maker, Web Intelligence does not know how to calculate

the correct Average Sales Total for these smaller entities.

The delegated measure, on the other hand, calculates the measures for all subsets of the

dimensions in the report. Thus, it would calculate Number of Cars Sold and Average Sales

Total per:

• Country

• Country and Year

• Country, Region, and Year

• Country, Region, Maker, and Year

What happens when changes are made to the report? When the report changes, the delegated measure updates the grouping set accordingly.

• When users add to the grouping set, the value #TOREFRESH appears to indicate that the

value is missing and they need to refresh the report to see the measure.

• When users save their report, it removes unused grouping sets.

Using a delegated measure as a weighted average

A report designer wants to calculate the average sales total per region, and also for all regions.

The universe designer has created a measure called Average Sales Total that calculates the

average of the sales totals.

When the user runs this in a Web Intelligence Rich Client query, together with Region, the

average sales total per each region is calculated.

The user then wants to calculate the average sales total level for all regions, and adds an average

calculation on the Average Sales Total column.



A new row appears at the bottom of the table and this row displays the average sales total for

all regions.

This appears accurate, but it is not. Web Intelligence Rich Client is adding up the values shown

in the Average Sales Total column and then dividing them up by six, since there are six regions

available. The values in the Average Sales Total column are already calculated averages, so

Web Intelligence is actually calculating the average of averages.

What is required here is a weighted average, as some regions have more car sales revenue returns

than others. The sales total value returned by those regions with more sales returns needs to

count more heavily than those regions with fewer returns.

When adding the Number of Cars sold figure to the query, you see here that the number of

cars sold per region varies considerably. Sixty-eight cars were sold in the West Coast, while

only thirteen in the East Coast.

When Web Intelligence Rich Client calculates the overall average sales total, it cannot take into

account the fact that the West Coast should have more weight in the calculation of the average.



Web Intelligence Rich Client does not have access to the detailed data, just to the regional

average value, returned by the Average Sales Total measure.

To calculate a weighted average, you need to create a delegated measure in the universe, which

will delegate this calculation to the database.

To do this, you must modify the universe using BusinessObjects Universe Designer. In properties

of the Average Sale Total measure, setting the function to Database delegated will delegate

this calculation to the database and effectively calculate a weighted average.

Running the same query using the Average Sales Total measure with the function set to Database

delegated, will result in the correct average total:



Best practices for using delegated measures Keep in mind the following best practices for effective use of delegated measures:

• Use a delegated measure when report users manipulate the measures in reports. When they

only need to refresh, view and print their reports, the calculation may be simpler to perform

in the report.

• Use a delegated measure to replace multiple query aggregates.

• Use a delegated measure on calculations that could give inaccurate results when calculated

in the report (such as a complex average).

• Use a delegated measure for measures requiring division.

• This ensures report designers can quickly recognize a delegated measure when they glide

their mouse over it in a query, when you create the delegated measure in the universe make

sure that in the Edit Properties dialog box for the measure, on the Definition tab, you enter

identifying text in the Description field.

Activity: Creating and using a delegated measure Objectives

• Create a delegated measure in Universe Designer.

• Use a delegated measure in Web Intelligence Rich Client.

Instructions 1. In Universe Designer, open the Motors universe.

2. In the Sales Figures class, create a new measure called Average Sales Total :

SELECT syntax:

avg(SALE.SALES_TOTAL)

In the Properties tab, set the aggregation function to Average. 3. Save the universe and log onto Web Intelligence Rich Client.

4. Create a new query using the Region and the Average Sales Total objects. Click Run Query.

5. Select the Average Sales Total column and select the average function from the toolbar.

Activate the sum drop-down list, and select average.

Is the result correct?

6. Return to Universe Designer and copy the Average Sales Total and paste it in the same

class. Name the copied object Delegated Sales Total Average.

7. In the Properties tab, set the aggregation function to Database delegated.

Save the universe.

8. Return to Web Intelligence Rich Client.

9. Add Region, the Average Sales Total, and the Delegated Sales Total Average objects to

the Query Panel.

Click Run Query.



10. Add an average to the Average Sales Total column, as done in step 4.

11. Drag the Delegated Sales Total measure object from the Data tab and position it in the cell

at the bottom of the Delegated Sales Total column. Drop the Delegated Sales Total measure

object in the cell at the bottom of this column.

Note that the cell now displays a text string: #TOREFRESH.

This indicates that the average will not be calculated by Web Intelligence Rich Client, but

it must be calculated by the database.

You need to refresh the document to retrieve the calculated results from the database. 12. Click Refresh Data.

You see here that the average calculated by the database does not return the same value as

the value calculated by Web Intelligence Rich Client.

Because the database has access to the detailed data concerning all satisfaction levels in

these regions, the result is based on a weighted average. The database is able to take into

account the difference in numbers of customers per region.



Quiz: Creating measure objects 1. Measure objects are very flexible because they are semantically dynamic. What does this

mean?

2. Measure objects are created in the same way as a dimension or detail object. However, the

object properties differ in two ways. What are they?



Lesson summary After completing this lesson, you are now able to:

• Explain measure object concepts


• Create delegated measure objects

Using Lists of Values—Learner’s Guide 135


Lesson 6

Using Lists of Values

Lesson introduction This lesson explains how you can add, modify, or remove a list of values (LOV) for an object.

It also introduces how to create a cascading list of values in Designer and how to use them in

Web Intelligence Rich Client.


• Create a list of values

• Work with LOVs in Universe Designer

• Create a cascading LOV



Creating a list of values A list of values is a list that contains the distinct data values associated with an object.


• Explain what a list of values (LOV) is

• Use a list of values in Web Intelligence Rich Client

What is a list of values? When you create a dimension or detail object in Universe Designer, it is automatically assigned

an associated list of values, or LOV. This list does not physically exist when you create an object,

but by default the object has the ability to query the database to return a list of its values when

used to build a query.

Lists of values are based on the results of a SELECT Distinct query on the column or columns

held in the Select statement in the object‟s Edit Properties dialog box. If you select the Export

with Universe option in the Associate a List of Values pane of the Properties tab, the list of

values is converted to XML when you export the universe, and then stored in a .unw file in the

Central Management Server (CMS).

The first time a list of values is used to filter results returned by a query, the LOV is stored in

an encrypted file on the local file server in the sessions folder.

As you create objects in the universe, use the following questions as a guide to help you decide

whether to associate an LOV to an object or not:

• Do the users need to see a list of values for this object? Are they likely to want to apply

query filters or conditions on this object?

• Is the data dynamic or static? Will the data be updated frequently?

• How long will it take to run the SELECT Distinct query?

• What does the list need to include?

Using a list of values (LOV)

When users build queries, they can define query filters to restrict the amount of data returned

by a specific object used in the query. To do this, they view the list of values for that object in

order to specify which value(s) will be returned. The LOV for the object appears in the Filter

or Editor, which helps the user choose the terms for the filter.

For example, a manufacturer object with the SELECT clause for the manufacturer name column

will have an LOV that contains all the available distinct car manufacturer‟s names. A user who

wants to limit the query to a single manufacturer could select that name for the query filter by

choosing it from the LOV.



Working with LOVs in Universe Designer A list of values is a list that contains the distinct data values associated with an object.


• Associate an LOV with an object

• View the contents of an LOV

• Set options for generating an LOV

• Modify the contents of an LOV

• Create a hierarchical view of an LOV

Associating an LOV with an object By default, an LOV is attached to every dimension and detail object that is created in Universe

Designer. When you create a dimension or detail object in Universe Designer, it is automatically

assigned an associated list of values, or LOV. This list does not physically exist when you create

an object, but by default the object has the ability to query the database to return a list of its

values when used to build a query.

There are three things to keep in mind, as a universe designer, when deciding whether or not

to associate an LOV to an object:

• An LOV is based on a SELECT Distinct query that is fired at the target database. This could

have potential performance implications for the efficiency of Business Objects end-user

querying tools.

• The only purpose for creating an LOV is to assist the end user in choosing an operand value

for a query filter.

• The LOV only holds values that exist within the database.

It is therefore recommended that you do not provide an LOV for the following types of objects:

• All measure objects.

• Any object where the LOV consists of a large number of values.

• Any object where the list on its own would be meaningless.

To view an object’s default LOV properties 1. Double-click the object to open the Edit Properties dialog box for the object.




3. If you want to turn off the LOV for this object, click the Associate a List of Values check

box to clear it.

To view the contents of an LOV in Universe Designer 1. Double-click the relevant object to open the Edit Properties dialog box.


3. In the Associate a List of Values zone, click the Display button.

A SELECT Distinct query is fired at the target database and the LOV displays. 4. Click the Cancel button to close the window.

To create a file to hold the contents of the LOV query in Universe Designer, use the same

procedure, but instead of clicking Cancel at step 4, click OK. In that case, the list is saved as

an .LOV file in the universe subfolder on the file system.

The default location is the Universe subfolder of the default installation folder:

C:\Documents and Settings\<user_name>\Application Data\

Business Objects\Business Objects 12.0\Universes\@<server_name>\<universe_name>

The name of the LOV file is the same name as shown in the List Name field, in the Properties

tab.

As a designer, you can edit the list name to call the file anything you want (over 100 characters

long), provided that the file ends in an .LOV extension. Clicking the Restore Default button

changes the name back to the default file name.



Setting options for generating LOVs By default, the first time that an LOV is used in a user login session, the system fires a query

at the target database and uses the results to populate the list. Thereafter, the .LOV file from

this query is referred to each time the LOV is used.

However, you can alter the strategy for refreshing the list by selecting options from the Associate

a List of Values zone, in the Edit Properties dialog box.

Note: The next section describes the following List of Values options:

• Automatic refresh before use option

• Export with universe option

• Delegate search option

Automatic refresh before use If you select this check box, the system sends the SELECT Distinct query to the target database

every time the user selects the LOV. This refreshes the contents of the list much more frequently

than the default strategy, where the list is refreshed only the first time it is used in a user login

session.

It is recommended that you select the Automatic refresh before use check box if the contents

of the list are dynamic and frequently changing. If the contents of the list are stable and

unchanging, you can increase speed and efficiency by clearing this check box.

Export with universe If you select the Export with universe check box, the list of values is converted to XML when

the universe is exported, and stored in a .unw file. This file is stored in the BusinessObjects

Central Management Server (CMS).

Delegate search The Delegated list of values (LOV) search allows you to delegate the search of values in an

LOV to the database.

This feature:

• Prevents the LOV from loading automatically

• Restricts the data set returned

• Improves performance by limiting the load time



Instead, the report user can perform a search for a pattern within the database.

This option can be helpful when using an SAP BW data source. An SAP BW query can contain

more than ten variables, which means that ten or more lists of values can be loaded. Loading

and refreshing lists of values can have an important impact on performance.

The delegate search option on the list of values properties presents the user with an empty list

of values at query run time. The user enters search criteria to limit the number of values returned

in the list of values.

Note: The delegated search is not supported for cascading lists of values.

Modifying the contents of the LOV In Universe Designer, you can modify the contents of the list in two ways:

• Remove values from the list by creating a filter.

• Add data to the list by adding columns to the list. The remaining two options, Allow users to edit this list of values and Hierarchical Display,

are not available for users creating reports with Web Intelligence and Web Intelligence Rich

Client.

To apply a condition to an LOV 1. In Universe Designer, in the object‟s Edit Properties tab (in the Associate a List of Values

zone), click Edit to the left of the Display button.

The Universe Designer Query Panel displays, showing the default query for the LOV. The

active object is listed in the Result Objects.

2. Drag an object that you want to serve as a condition on the list of values for the active object

over to the Conditions pane.

3. Double-click an operator in the Operators pane.

4. Double-click an operand in the Operand pane.

5. Select or type values as required.

6. Click Run to save the condition and close the Universe Designer Query Panel.

7. Click Display to view the restricted list of values.

If a blank list appears, click Refresh. The values appear in the list.

8. Click OK to accept the modified list.

The .LOV file in the universe subfolder updates with the modified list. This is the LOV that

the end users see when they use the edited object in a query.



Editing the LOVs for the entire universe If you want to view all the objects in the universe that have LOVs associated with them, and

possibly edit some of these LOVs at the same time, you can edit the lists from the Universe

Designer Tools menu.

To edit the LOVs from the Tools menu 1. From the Tools menu in Universe Designer, select List of Values.

2. Select Edit a List of Values from the drop-down menu.

The List of Values dialog appears displaying all the objects in this universe that have an

LOV associated with them. From here, you can select any of these objects to display, edit,

purge and refresh their LOV.

3. Click the +box next to each class name displayed to see the objects in this universe that have

an LOV associated with them.

4. Select an object from the list.

5. Click Display.

The list of values for the selected object displays. 6. Click OK to close the List of Values dialog box.

The Tools ➤ List of Values ➤ Edit List of Values option is useful if you want to edit all

the LOVs in the universe at the same time, instead of displaying the Edit Properties dialog

box for each object separately.



Adding data to the list by adding columns The second way you can modify the LOV is to add more data to the list by adding columns to

it. This helps end users to find the value they want. It is also an appropriate method for an LOV

that contains a lot of values.

To add additional columns to an LOV 1. Double-click on an object to open the Edit Properties tab.

2. Click on the Properties tab.

3. Select Edit (in the Associate a List of Values zone).

The Universe Designer Query Panel displays. 4. Drag the objects you want to place in the hierarchy into the Result Objects pane to the right

of the existing object and place the respective sorts on them.

5. Click Run to save the LOV query and close the Universe Designer Query Panel.

6. In the Properties tab of the object‟s Edit Properties dialog box (in the Associate a List of

Values zone), click the Display button to see the LOV.

Note: If the list is blank, click the Refresh button to update the list.



Creating a cascading LOV A cascading LOV is a feature in Universe Designer that allows you to associate an LOV to a

series of objects defined in a hierarchy. When a user applies a prompted query filter to one of

the objects used in the cascading LOV, Web Intelligence or Web Intelligence Rich Client prompts

the user to select a value for each level of the hierarchy.

This feature only applies to Web Intelligence XI R2 ,Web Intelligence XI 3.0, and Web Intelligence

Rich Client XI 3.0.

Note: You remove a cascading LOV in the same way that you remove an ordinary LOV, by

editing the object properties and deleting the condition in the object definition.


• Set up a cascading LOV

• Use the cascading LOV in Web Intelligence Rich Client

Setting up a cascading LOV A cascading LOV is a sequence of lists of values associated with a hierarchy of objects in a

universe. As universe Universe Designer, you define prompts for each hierarchy level and

when the user adds one of the objects to a query, the query prompts the user to select a value

for each level.

Universe designers build the prompt(s) in the object definition, and report designers and power

users use it when they create and refresh reports using queries.



A universe designer defines the universe so that the user is always required to answer a series

of prompts to specify the values in a hierarchy of dimensions to be displayed in the report.

Only the data concerning the selected values is returned to the microcube.

Users can create a query that builds one of the objects into a prompted query filter. The Prompts

dialog box displays the list of values for all the objects you placed in the cascading LOV in

Universe Designer, in reverse order. To build a cascading LOV on an object

1. From the Tools menu in Universe Designer, select List of Values.

2. Select Create cascading Lists of Values from the drop-down menu.

The Create Cascading List of Values dialog box appears.

3. Open the appropriate class and double-click the object to move it into the Cascading List

of Values list.

By default, text appears in the Prompt Text zone to set the text that users will see if this

object is used in a prompted query filter after you add the next object.

4. Double-click additional objects that need to appear in hierarchical order in the cascading

list of values.

Edit the prompt text if required.

5. Verify that the Hierarchical View check box is selected.

6. Click Generate LOVs to create the list of values.



If LOVs already exist for the selected objects, you will be prompted with a message asking

whether you want to overwrite the existing values.

7. Click OK.

The Create Cascading List of Values dialog box closes.

8. Save and export the universe.

To test the cascading LOV in Web Intelligence Rich Client Now that you have assigned LOVs to objects that are grouped together in a hierarchy as a

cascading LOV, you can create a query that builds one of the objects into a prompted query

filter.

1. In Web Intelligence Rich Client, build a query and create a prompt on one of the objects in

the cascading LOV.

2. Click Run Query.

The Prompts dialog box appears. The Prompts dialog box displays the list of values for all

the objects you placed in the cascading LOV in Universe Designer, in reverse order.

Note: If you are sure you know the exact value that interests you, you can always type in

the “Type a value” text box.

3. Scroll down the list of values and click the + box to expand that folder.

4. Expand the further + boxes to select the lowest level value for your query.

The little arrow displayed next to the prompt text at the top of the Prompts dialog box

changes to a green check mark and the value you have chosen appears in the prompt.

5. Click Run Query to create the report.

The report displays the selected values.

Activity: Using a cascading LOV in Web Intelligence Rich Client Objective

• Associate a Cascading LOV to an object.

Instructions 1. In Universe Designer, create a cascading LOV using the objects in the Car class.


3. Build a query in Web Intelligence Rich Client that shows the number of cars sold per

showroom and prompts the users to select the Category of Car that they want to see in the

report.

Note: At the end of this activity, please remove the Cascading List of Values using the

following steps:



• In Universe Designer, change the object definition to associate a standard List of Values

for all objects in the Car class.

• Save the universe.



Quiz: Using lists of values 1. By default what values are contained in a list of values (LOV)?

2. What are three things that a universe designer should keep in mind when deciding whether

to associate an LOV with an object?

3. For what types of objects is it recommended not to provide an LOV?




• Create a list of values

• Work with LOVs in Universe Designer

• Create a cascading LOV

Resolving Loops in a Universe—Learner’s Guide 149


Lesson 7

Resolving Loops in a Universe

Lesson introduction This lesson describes loops, a particular type of join issue that can arise as you create joins

between tables in your schema. It explains how you can detect and resolve loops to ensure that

the join paths taken by queries run on the universe return correct results.


• Understand loops

• Resolve loops using shortcut joins

• Resolve loops using aliases

• Resolve loops using contexts



Understanding loops A loop is a join path issue that arises from the way that tables are related in a relational database.

Loops can produce instances where a query returns too few rows of data.


• Understand the causes of loops

• Detect loops in a universe structure

Recognizing loops

A loop exists when the joins between tables form a closed path.

For example, in the table layout above, the designer has added joins between the tables

Showroom and Country to create two linked sets of information.

• One set links the car sale details, the client, the client‟s region and the client‟s country of

residence.

• The other set links the car sale details, the showroom, and the country where the showroom

is located.

Together, these joins form a loop.

Problems caused by loops Suppose users of the Motors universe want to produce reports showing the revenue generated

by car sales to clients, including both the location of the showroom where the cars are sold and

the address (including country) of the clients.



The designer adds the tables needed to provide this information and creates the joins as shown

in the previous example. The designer has also created objects for the Showroom Country,

Client Country, and Sales Revenue.

If the loop was allowed to remain and a query could be run using the Showroom Country,

Client Country and Sales Revenue objects, the report results will be incorrect. The report would

suggest that only clients from the US bought cars in the US showrooms, and only clients from

the UK bought cars in the UK showrooms. However, the report would not show any clients

from any other countries. When you know that there are clients from other countries, this result

indicates that there is a problem with the report.

Loops in a universe schema and not in the database In a database, multiple paths between tables can be valid and implemented to meet specific

user requirements. When each path is included individually in a query, it returns a distinct set

of results.

However, a schema that you design in Universe Designer often needs to allow queries that

include more than one path, which a relational database may not be designed to handle. As a

result, the information returned can be incorrect.

The rows that are returned are an intersection of the results for the path, so fewer rows are

returned than expected. It is often difficult to determine the problem when you examine the

results.

What is the loop doing? The joins in the Structure pane are used to create the WHERE clause in the inferred SQL of a

query. Joins restrict the data that is returned by the query. In a loop, the joins will apply more

restrictions than the designer intended, and the data returned will be incorrect.

This is an example of a WHERE clause created by a loop:

WHERE

{COUNTRY.COUNTRY_ID=SHOWROOM.COUNTRY_ID} AND {COUNTRY.COUNTRY_ID=REGION.COUNTRY_ID } AND {REGION.REGION_ID=CLIENT.REGION_ID } AND {CLIENT.CLIENT_ID=SALE.CLIENT_ID } AND {SHOWROOM.SHOWROOM_ID=SALE.SHOWROOM_ID } AND {SALE.SALE_ID=SALE_MODEL.SALE_ID } AND {SALE.SALE_TYPE= 'S' }

Notice that the two joins at the top of the SQL statement are both applying a restriction to the

Country table, which is serving two purposes:

• It is being used as the Lookup for the Showroom Country

• It is also the Lookup for the Client Country This creates a restriction so that data is returned only when the Showroom Country is the same

as the Client Country. Consequently, the report shows only the revenue generated by US clients

in the US showrooms and by UK clients in the UK showrooms. In summary, while the above

loop does infer legitimate SQL, the results will not include all intended values. Therefore, a



query on a universe involving such a loop will return misleading data. To avoid this, the loop

must be resolved.

Resolving loops Loops are an inherent problem when writing SQL statements. There are various techniques

within SQL that you can apply to resolve loops.

How Universe Designer deals with loops There are automatic methods built into Universe Designer that can be used to identify and

resolve almost all loop problems. The two main methods of resolving loops are:

• Aliases

• Contexts Loops can be resolved by creating aliases and contexts manually. However, depending on the

complexity of a universe, this can be a cumbersome task. There is functionality built into

Universe Designer that allows for automatic detection and resolution of loops. This functionality

can only be reliable if cardinality has been defined correctly for each join in the universe.

Furthermore, due to performance implications, it is recommended that all cardinality be set

manually at the time each join is created.



Resolving loops using aliases One way to solve a loop in the universe structure is to create an alias table.


• Describe aliases


• Resolve self-join loops using aliases

About aliases An alias breaks a loop by using the same table twice in the same query for a different purpose.

The alias is identical to the base table but with a different name. The data in the alias is exactly

the same as the original table, but the different name tricks SQL into using the same database

table for two different purposes.

The Country table has already been identified as a shared lookup table because it is serving

two purposes in the query you are trying to run (providing data for the Client Country and

also for the Showroom Country). In the example above, you can see the Country table joined

to the Region table for the Client side of the query. The Country table also is the Showroom

table for the Showroom side of the query.

Note: Another way of spotting the problem table in a loop is that it will have only the one end of

the one-to-many joins going into it. Check the other tables in the loop. If you find no others with

only one-end joins, the loop can be resolved using an alias, assuming there are no other tables joined

to country.

To resolve the loop, you need to use the same table (the Country table) twice in the same query

when it is being used for different purposes. However, you cannot do this in SQL unless you

create an Alias table.

You can resolve the loop satisfactorily by creating only one alias table in the example we have

been using. The Region join uses the original Country table, while the Showroom join uses the

alias table. However, you could create a separate alias table for each join in the original table.

In the past, this was necessary for some relational databases. Today, it is not necessary. However,

some universe designers prefer to alias both tables.

Detecting loops and inserting aliases

The Universe Designer module has automatic tools that detect loops and create aliases for you.

You can use the Detect Loops or Detect Aliases toolbar icons, to automatically detect and

indicate the tables causing loops in the active universe. Detect Aliases proposes candidate tables

that you can edit, and insert in the schema.

Note: Before using Detect Aliases, verify that all the tables in schema are linked by joins, and

that all cardinalities are set.



To detect loops using the automatic detection tool 1. Click the Detect Loop button.

The system highlights the loop in the Structure pane, and displays the Loop Detection

dialog box.

2. The Loop 1/1 indicates how many loops have been detected. If there are others, you can

use the forward and back arrow buttons to check each loop. The message beneath the buttons

indicates (in this case) that the loop can be resolved with an alias.

3. Click Insert Alias in the Loop Detection dialog box.

Universe Designer automatically creates an alias for the required table. You may need to

move the new alias table so that you can see the Structure pane.

Note: The original table name will show up in brackets in the Alias table header.

4. Close the Loop Detection dialog box.

The Structure pane will look similar to this:



In the example diagram, the Country_Showroom alias table has been created in the Structure

pane, the join between this Alias table and the Showroom table has been made automatically,

and the loop has been broken.

Note: When the problem table has two purposes, Universe Designer might nominate either of the

two as the candidate for the Alias table.

To insert an alias automatically Universe Designer has an automatic tool that detects the tables that could be aliased to resolve

loops.

1. Click the Detect Aliases button.

The system displays an Alias Detection message similar to the following:

If you have not yet set cardinalities, this message reminds you that you must do so first. If

cardinalities have already been set, the reason for the message may be a self-restricting join

within the universe structure. Cardinality is not relevant for these types of joins and so

designers tend not to set cardinality for them. However, to avoid the message, you could

make self-restricting joins one-to-one.

2. Click OK.

The Candidate Alias dialog box displays. 3. Select a table name and click Rename.

The Rename Table dialog box displays.

4. Enter the new name for the alias and click OK.

The Rename Table dialog box closes and the new alias name is shown in the right panel. 5. To create the alias table, click Create.

Universe Designer displays a confirmation request. 6. Click OK to create the alias table.

Note: If there are several candidates for aliases, you can then repeat the process for the next

table. When there is only one candidate, the Candidate Alias dialog box closes.



Tip: Be careful not to delete the original table. Once you have created one or more alias

tables, it‟s a good idea to click beside the original table in the Structure pane and type Aliased

table Do not remove, for example, to remind you not to delete it.

To insert an alias manually Instead of using the Loop Detection or Alias Detection tools, you can create the alias manually.

1. Select the table for which you want an alias by clicking the table header.

2. Insert an alias using one of the following methods:

• Click the Insert Alias button.

• Right-click the table and select Alias from the right-click menu.

3. Enter the new name for the alias table and click OK.

This creates an alias table for the selected table.

Note: The original table name appears in brackets in the Alias table header.

4. Remove the appropriate join from the original table.

5. Reset the join to the alias table.

6. Set the cardinality for the join.

The Structure pane should now look the same as when using the first method, the Loop

Detection tool.

Redefining objects

When you create an alias table, check that any existing objects that are defined from the original

table still refer to the right table. They may need to be defined from the alias table to infer the

correct SQL and get the correct result.

Finding objects defined from a table In a simple universe, it is not difficult to find the objects that have been defined from a table.

There is a utility in Universe Designer that allows you to easily determine all existing objects

that point to a single table in the structure of the universe.

Universe Designer provides an option to assist in finding the relevant objects.

1. Right-click the header of the original table in the Structure pane. 2. Choose View associated objects from the right-click menu. This highlights all the objects

that were defined from the original table in the Universe pane. Redefine the highlighted

objects to make sure they point to the correct table.

3. Double-click the affected object to open the Object Properties dialog box. 4. Redefine the SELECT statement to use the alias table instead of the original table.



5. Click OK and then save the universe.

Listing and renaming aliases

You can list aliases and rename them. To invoke the aliases list:

1. Select the List of Aliases option from the Tools drop-down list.

The List of Aliases panel appears.

To rename an alias from the List of Aliases panel To rename aliases from the list of aliases:

1. Click the alias you want to rename.

2. Edit the alias name in the New Name field and click OK.

Note: The alias name changes in the universe structure as well as any object referencing

the alias and context lists.

Choosing which alias method to use

Method Advantages Disadvantages

Detect loops

can view loops before

applying them

may show other loops to be

resolved by contexts

Detect aliases

Insert alias

finds all candidate aliases

exclusively

choose table to alias,

minimizing object redefinition

no visual check prior to

acceptance

must understand how to

identify the need for candidate

analysis Whichever method you choose, you must always redefine objects that now use the Alias table.

Resolving self-join loops using aliases A self-join is a join from one column of a table to another column of the same table.

A classic example of when such a join is required is in a situation whereby you want to report

on the hierarchical structure of an organization via a Personnel database. In such a situation,



it is most probable that all employee records are held in a single table, irrespective of status.

Hence, a self-join is required to report on the hierarchical relationship between those employees.

For example, in the Motors database there is an employees table that contains columns as shown

below:

Each employee is uniquely identified by the Emp_Id field, and each employee has a manager,

who is identified by the Emp_Mgr_Id field. However, the managers are themselves employees,

and the table therefore contains a hierarchical structure.

If you want to add a join to link each employee with their respective manager, the obvious way

is to link the Emp_Mgr_Id field to the Emp_Id field, as in this example:

The code used to identify the manager (Emp_Mgr_Id ) is itself an employee code. You can

therefore use it to look up the Emp_Id codes in the Employee table and identify the manager‟s

name.

This is effectively a loop, as the path forms a closed circuit. However, you cannot resolve it by

using the usual method of detecting the cardinalities and then detecting aliases. This is because

the cardinality detection tool cannot work on a self-join. Moreover, a structure expressed this

way will not infer the correct SQL.

To resolve a self-join with an alias 1. Right-click the table header and choose Alias from the right-click menu.

2. Enter an appropriate alias table name.



3. Click OK.

4. Draw the join between the original table and its alias.

5. Double-click the join.

The Edit Join dialog box opens.

6. Set the cardinality for the join.

7. When the self-join has been resolved, you can create separate objects for both tables.



Resolving loops using shortcut joins Another way to solve a loop in the universe structure is to use a shortcut join.


• Describe how shortcut joins can make a query more efficient


Using a shortcut join A shortcut join is a join that links two tables together but bypasses intervening tables that exist

in the universe. This is used when designing universes where it is possible in certain

circumstances to make the inferred SQL more efficient.

For example, in the Motors universe, the geographical information relating to clients comes

from the Client, Region, and Country tables:

If an end user runs a query including Country and Client (but not Region) objects, you will

find that the inferred SQL includes the joins to the Region table. This is necessary because the

Region table forms the link between the Client and Country tables. However, the additional

lookup decreases the efficiency of the SQL.

You can overcome this inefficiency by making a join directly from the Client table to the Country

table. Now if a user builds a query just using Country and Client, the query will not have to

refer to the Region table.

You now have a loop. In this case, you do not have a multipurpose lookup table scenario, and

should therefore not alias.

Instead you would convert the created join to a shortcut join to break the loop.



To convert a standard join to a shortcut join 1. Double-click the join that you want to convert to a shortcut join.

The Edit Join dialog box appears. 2. Click the Shortcut join check box just below the Cardinality zone.

3. Click OK to close the dialog box.

The join has been redefined as a shortcut join, which appears in the Structure pane.

If you were to try detecting loops, none would be detected. The shortcut join, in the above

example, is telling the SQL only to use this join if the Region table is not included in the

query. Therefore, there is no loop, and the efficiency of the SQL has been improved.

Shortcut joins are not automatically detected for contexts. If you want to include them in a

context you have to manually edit the context. However, this is not always desirable.

Ideally, shortcut joins should bypass contexts when specific queries do not require one or

more contexts to return the results, and therefore should be left as standalone or isolated

joins. The efficiency gains of a shortcut join are based on the fact that it spans across contexts.

In the Motors universe, a shortcut join can be the ideal way of joining Showroom to Maker

in order to produce a report for managers, wishing to see which showrooms have which

franchises. This shortcut join would not use the Rental or Sales contexts. Instead it would

go directly from Showroom to Maker, as the shortcut join takes precedence over any other

join.

However applying a shortcut join here is not possible due to the keys set up in the tables.

A linking table between Showroom and Maker, together with a new context, will be required

to return the same results.

Activity: Resolving loops with aliases

Objectives

• Resolve loops by creating alias tables

• Test your results in Web Intelligence Rich Client



Instructions In this activity you will add new tables, insert new joins, and set cardinality, that will create

loops in the Motors universe. You will then resolve the loops and test them.

1. Insert the following join and set its cardinality.

• COUNTRY.COUNTRY_ID=SHOWROOM.COUNTRY_ID

2. Use the Detect Loop toolbar button to test for loops in your universe. To solve the loops

that you have detected by creating alias tables, press the Insert Aliases button in the Loop

Detection dialog box, or use the Insert Alias toolbar button and create two alias tables

called:

• COUNTRY_SHOWROOM

• COUNTRY_REGION

3. Disconnect the original COUNTRY table from the other tables and use the alias tables to

redefine the joins as follows:

• COUNTRY_SHOWROOM.COUNTRY_ID=SHOWROOM.COUNTRY_ID

• COUNTRY_REGION.COUNTRY_ID=REGION.COUNTRY_ID

• COUNTRY_REGION.COUNTRY_ID=CLIENT.COUNTRY_ID

4. Set the new join cardinalities. In the third join, be sure to select the Shortcut join check box.

5. Create a Country object in the Showroom class with the settings:

• Name = Showroom Country


• Description = Country in which showroom exists

• SELECT =

COUNTRY_SHOWROOM.COUNTRY_NAME

• Associate an LOV

6. Edit the Country object in the Client class as follows:

• Name = Client Country

• SELECT =

COUNTRY_REGION.COUNTRY_NAME

7. Check integrity by selecting the Check Integrity button in the toolbar.

The check integrity tool finds divergences because the COUNTRY table is now isolated.

Ignore this message and don‟t delete the original table.


9. Test your changes in Web Intelligence Rich Client by building a query containing Showroom

Country, Client Country, and Sales Revenue objects.

10. Edit the query and remove the Client Country, and Sales Revenue objects. Run the query

with just the Showroom Country object.



11. In Universe Designer, create an additional alias of the COUNTRY table, called

COUNTRY_MAKER.

12. Insert the following join:

• COUNTRY_MAKER.COUNTRY_ID=MAKER.COUNTRY_ID

Make sure that the join cardinality is set to one-to-many (1-N). 13. Create a Maker Country object in the Car class.

14. Test your changes in Web Intelligence Rich Client by building a query containing Maker

Country, Maker, and Model objects.



Resolving loops using contexts Another way to solve a loop in the universe structure is to create contexts.


• Describe contexts


About contexts A context resolves a loop by defining a set of joins that define one specific path through tables

in a loop. It ensures that joins are not included from different paths within the same SQL query.

You often use contexts in schema that contain multiple fact tables that share lookup tables.

An example of this situation is the Sale table in the Motors universe. The Sale table contains

rows of data for cars both sold and rented. The Sale_Type column is used as a flag to indicate the type of transaction (S = car sale, R = car rental). Without the self restricting join, the resultset

of the query would produce rows where the Sale_Type column is equal to either „S‟ or „R‟.

Previously, you defined this self-restricting join to „S‟, so that any object based on the table or

joins passing through that table would produce query results covering only car sales.

In order to retrieve data concerning rental sales as well, you create an alias of the Sale table

called Rental, set the self-restricting join to „R‟ and create an alias table of the Sale_Model table

called Rental_Model. Creating the aliases tables, however, will create a loop because the query

will not know which table to go through to get to the Model table, Sale or the alias Rental.

You can solve this type of loop by creating two contexts which will define the correct route

through the universe structure. These routes link tables together in the structure.

What is a context? A context is a list of joins that define a path for a query. The tables involved in the joins are

included in the context.

Any objects derived from tables included in a context are compatible with each other. When a

query is made with objects related to separate contexts, more than one SELECT statement is

inferred and run. The results of the queries are then merged in the microcube. This avoids

incorrect results that might arise due to a loop or other situation with alternative routes.

Alternative routes can exist without a loop in the universe structure.

Detecting and creating contexts • A separate context is identified for each table with only the many end of joins attached.

• The joins in a context are identified by working back from the table with only the many end

of joins attached - many-to-one, many-to-one.



Identifying the joins that make up a context Universe Designer detects contexts by identifying tables that have only the many ends of joins

attached. It does this progressively throughout the structure.

No joins flowing back from one-to-many are included.

To help to see the flow of contexts within a structure, you can arrange the tables so that all the

joins flow as many-to-one from left to right across the structure.

Included in the context are all the tables that can be reached by following the flow from

many-to-one (N-1). Tables that can only be reached by flowing back from one-to-many (1-N)

are not included in the context.

Note: If contexts are an important part of your universe structure, it can be very helpful to

arrange your tables in this way, so that you can easily see the individual contexts.

When it is not appropriate to resolve a loop by using an alias to break the loop, the loop must

be left in place. However, this results in an error message when running an end-user query.

This is because there are two alternate routes around the structure. Contexts are used to specify

those alternate routes and ensure that a single inferred SELECT statement only includes reference

to columns from tables in one of those routes.

In the Sales and Rental example, you can follow two different paths from the Client table to

the Model table:

• By way of Rental and Rental_Model:



• By way of Sale and Sale_Model:

Each context represents what may be inferred in a single SELECT statement.

Any query that infers some SQL code exclusive to one context and some exclusive to the other

will infer two separate SELECT statements.



This loop can be resolved by two candidate contexts:

Rental_Model Context Sale_Model Context COUNTRY.COUNTRY_ID=REGION.COUNTRY_ID COUNTRY.COUNTRY_ID=REGION.COUNTRY_ID

REGION.REGION_ID=CLIENT.REGION_ID REGION.REGION_ID=CLIENT.REGION_ID

CLIENT.CLIENT.ID=RENTAL.CLIENT_ID CLIENT.CLIENT.ID=SALE.CLIENT_ID

RENTAL.SALE_ID=RENTAL_MODEL.SALE_ID SALE.SALE_ID=SALE_MODEL.SALE_ID

RENTAL_MODEL.MODEL_ID=MODEL.MODEL_ID SALE_MODEL.MODEL_ID=MODEL.MODEL_ID

MODEL.MODEL_DAYRENT between

RENTAL_PRICE_RANGE.RENT_RANGE_MIN and

RENTAL_PRICE_RANGE.RENT_RANGE_MAX

MODEL.MODEL_PRICE between

SALES_PRICE_RANGE.PRICE_RANGE_MIN and

SALES_PRICE_RANGE.PRICE_RANGE_MAX

Note: The name of the context is normally defined by the table with only the many (N) end of

joins attached to it.

You then create different sets of objects from the tables in the different contexts. As a result,

users can run either Sales queries or Rentals queries, dependent on the objects they select.

Note: Every join (except shortcut joins) must exist in at least one context.

Detecting and creating contexts The table below shows the toolbar buttons you can use to detect and create contexts.

Detect loops

Detect contexts

Insert contexts

Loop detection tool suggests candidates for

both aliases and contexts.

Detect Contexts detects and proposes a list of

contexts to create.

Insert Contexts inserts a context manually.



To detect contexts using the Loop Detection tool 1. Click the Loop Detection button in the Editing toolbar.

The system displays the Loop Detection dialog box.

The first loop is highlighted in the Structure pane, and the message tells you that this loop

is not covered by any context. If other loops exist, click the forward arrow button to cycle

through the loops. Each loop is highlighted in turn, and a method of resolution is

recommended.

2. Click the Candidate Context button to see what the tool suggests.

The Candidate Contexts dialog box displays.

3. Highlight the candidate context you want to add and click the Add button.

The context moves across to the Accepted Contexts field. You can click the Rename button

to give each context a more meaningful name.

Note: You may choose to leave the original context name in brackets. This can be useful in

order to remind you that you have changed the joins in the context, while still allowing you

to view the original definition.

4. Repeat the process until you have accepted all the candidate contexts.

Note: Each candidate context is highlighted in the structure as you highlight it in the

Candidate Contexts field. This enables you to check the context before accepting it.

The Candidate Contexts dialog box closes, and the List Mode window opens in the upper

part of the Structure pane.

5. Click OK.



6. Close the Loop Detection dialog box.

The List Mode window shows the created contexts.

The Joins pane indicates the joins that are involved in the currently highlighted context.

The Structure pane highlights the tables that are involved.

7. When you have created the contexts you require to resolve the loops, save the universe.

To detect contexts using the detect contexts tool

1. Select Tools ➤ Automated Detection ➤ Detect Contexts , or click the Detect Contexts

button.

The system may display this message:

You may have just set the cardinalities, but you can still get this message because of

self-restricting joins. The system does not set cardinality on these, and therefore displays

this message. Click OK to continue because you have set the cardinality for all of the joins.

2. Click OK.

The system displays the Candidate Contexts dialog box. 3. Highlight the candidate context you want to add and click the Add button.

You move contexts across to the Accepted Contexts field. Rename them, if required, in the

same way as when using the Loop Detection tool.

4. Repeat the process until you have accepted all the candidate contexts.

5. Click OK and save the universe.



To insert contexts manually 1. Click the Insert Contexts button.

The New Context dialog box appears. 2. Define a name to identify the context in the Context Name field.

3. Select the joins that define the path for the context by clicking the individual joins in the

Current context join list. To remove a join from the selected list, click it again to remove

the highlight.

Note: From the List Mode window, you can open the Edit Context dialog box to add joins

by double-clicking the context in the Contexts pane.

4. When you have made a selection of joins, click the Check button to have Universe Designer

check whether there are any loops in the joins you have selected.

5. In the Description field, enter the text that displays in the user module Help field.

6. Click OK to create the context and close the dialog box.

Creating objects for each context When all the contexts are in place, you can create objects.

Some objects refer to tables that are included in only one of the contexts. In this example, such

objects include Sales Revenue or Rental Revenue. Other objects refer to tables which appear in

both contexts. In this example, such objects include Client Name.

Editing a context Sometimes, a user creates a query using objects that reference tables from opposite ends of two

contexts, for example, a query using Client Name and Model.

The Client and Model tables are on opposite sides of the Rental and Sales contexts.

As a result, there are two potential routes for the inference engine to use in the SELECT statement

so, when the end users run the query, they receive a prompt message to choose one of those

contexts.

As the term “context” is not meaningful to end users, you need to ensure that the context names

and the Help descriptions clearly indicate how the choice of context influences the results.

To edit the name and help description 1. Open the List Mode window by clicking the View List Mode button on the standard toolbar.

2. In the Contexts pane, double-click the context you want to edit.

The Edit Context dialog box displays.



The Context Name shows the name you accepted (or altered) when you created the context.

The Join List shows all the joins that are included in the context path. The highlighted joins

are included.

3. Scroll down the list of highlighted joins to verify that all required joins are included. You

can add additional joins, or remove unnecessary joins.

4. Click the Description field and enter a suitable explanation of the context‟s purpose.

5. Click OK to close the Edit Context dialog box.

6. Click the View List Mode button to close the List Mode window.


The description that you entered appears in the Context Selection Help dialog box in

Business Objects end-user querying tools, and the process of selecting a context is made

easier for end users.

Testing contexts Any end-user query that generates a SELECT statement which spans across the loop will fail

without contexts in place. If contexts are in place, the end-user query tool generates the SELECT

statement(s) in one of three ways. To test contexts, make at least three queries, one to test each

form of SQL generation when applying contexts. The three query types are:

• Inferred query

• Incompatible objects query

• Ambiguous query

Inferred query A query is run without prompting an end user to choose a context. The query contains enough

information for the correct context to be inferred. For example, a user runs a query using the

Showroom, Model and Sales Revenue objects.

When these queries are run, the data is returned without prompting the user to select a context.

The Sales Revenue object is a sum on the Sale_Model table, which is part of the Sales context.

The query infers that the Sales context is the one to use for the query.

Incompatible objects query Objects that reference tables with joins belonging to two different contexts are included in a

single query. The tool creates one SELECT statement for each context, executes the queries, and

then unites the results together so that the report data can be presented in a single table.

For example, if you run a query containing the Showroom, Model objects with both Sales

Revenue and Rental Revenue objects, no single context contains all the joins necessary to include

the Showroom, Sale, Sale_Model, Rental, and Rental_Model tables to which the three objects

refer. It therefore generates two SELECT statements in the query and merges the results in a

single microcube report.

Note: For an incompatible objects query to work, you need two contexts.



Ambiguous query An end user is prompted to choose between one query path or another. This occurs when a

query includes objects that, when used together, do not give enough information to determine

one context or the other.

When a query is ambiguous, the user is prompted by a dialog box in the Query Panel to select

the appropriate context. When the user selects a context, the corresponding tables and joins

are inserted into the SQL query.

For example, if you run a query containing only the Showroom and Model objects, more than

one context contains all the joins necessary to include the Showroom and Model tables to which

the two objects refer.

The user is prompted to identify which context to use by displaying the Context Selection

dialog box.

When the user selects one of the contexts and clicks OK, a SELECT statement is inferred using

the join path for the context chosen.

Note: For a user to select more than one context when running an ambiguous query, the Allow

selection of multiple contexts option in the SQL tab of the Universe Parameters dialog box in

the Universe Designer module must be selected.

Updating contexts Contexts are not updated automatically when the universe structure is changed. If you add or

remove any tables or joins to the structure, you will have to update all the contexts.

If you have made only a simple change to the structure, you can update the joins that are

included in each context manually using the Edit Context dialog box. However, if you have



made significant changes to the universe structure, it can be safer to remove the current contexts

and recreate them.

Recommended sequence It is always best to create all your alias tables first, and then create your contexts, because of

the requirement to update contexts. Otherwise, your alias tables will not be included in your

previously created contexts.

For loop resolution, therefore, the sequence is as follows:

1. Set cardinality on all joins. 2. Use Detect Aliases to detect all the loops that can be resolved with alias tables.

3. Insert all the required alias tables and their associated joins. Remember to set cardinality on

any new joins.

4. Use Detect Contexts to detect all the contexts that can be used to resolve the remaining

loops that could not be resolved with an alias.

5. Accept the candidate contexts, or create your own contexts manually. The need to follow this sequence highlights the main drawback of using the Loop Detection

tool. If you detect all loops, and then follow the Loop Detection dialog box suggestions for

resolving them in the order that they are presented, you will not necessarily resolve all the alias

table loops first, followed by all the context loops. It is therefore better to use the alias detection

tool first, and then the context detection tool.

Remember also that you will have to redefine any objects that are based on tables for which

you have created aliases. The overall sequence in universe design is as follows:

1. Add tables to the universe. 2. Insert joins.

3. Detect and resolve loops.

4. Create all the classes and objects.

Note: If you want to test your loop resolution in a query, you may need to create some basic

objects to allow you to run some simple queries. If you do this, always bear in mind the need

to redefine them when you have finished resolving loops.

Activity: Resolving loops using contexts Objective

• Resolve loops by using contexts.

Instructions In this workshop you will add new tables, insert new joins, and set cardinality, that will create

loops in the Motors universe. You will then resolve the loops using contexts, and test them.



1. In Universe Designer, create the following aliased tables:

• RENTAL (alias of SALE)

• RENTAL_MODEL (alias of SALE_MODEL)

2. Insert the table.

• RENTAL_PRICE_RANGE

3. Insert the following joins and set their cardinality.

Joins

CLIENT.CLIENT_ID=RENTAL.CLIENT_ID

RENTAL.SALE_ID=RENTAL_MODEL.SALE_ID

RENTAL.SALE_TYPE='R'

RENTAL.SALE_DATE between FINANCE_PERIOD.FP_START

and FINANCE_PERIOD.FP_END

RENTAL_MODEL.MODEL_ID=MODEL.MODEL_ID

SHOWROOM.SHOWROOM_ID=RENTAL.SHOWROOM_ID

RENTAL_MODEL.COLOUR_ID=COLOUR.COLOUR_ID




4. View loops using the loop detection tool.

Tip: You should find 10 loops.

5. Resolve the loops by using the context detection tool.

6. Edit the RENTAL_MODEL context as follows:

• Change the name of the context to RENTALS.

• As a description for the context enter: "Returns information on cars rented".

• Remove the following join from the context list:

MODEL.MODEL_PRICE between

SALES_PRICE_RANGE.PRICE_RANGE_MIN and

SALES_PRICE_RANGE.PRICE_RANGE_MAX

• Add the following self-restricting join to the context:


7. Edit the SALE_MODEL context as follows:



• Change the name of the context to SALES.

• As a description for the context enter: "Returns information on cars sold".

• Remove the following join from the context list:




• Add the following self-restricting join to the context:

SALE.SALE_TYPE='S'

8. Create a class called Rentals above the Sales class.

9. Create the following subclasses in the Rentals class:

• Rental Details

• Rental Dates

• Rental Figures 10. Create the following four objects in the appropriate subclass of the Rentals class:

Object Name

SELECT Statement Object

Description

Invoice ID Number

RENTAL.SALE_ID

Unique

Invoice ID

Number

Rental Date

RENTAL.SALE_DATE First day of

Rental

Return Date

Rental Revenue

RENTAL.SALE_DATE +

RENTAL.SALE_RENTAL_PERIOD

SUM(RENTAL.SALE_RENTAL_PERIOD*

RENTAL_MODEL.SALE_QTY*

MODEL.MODEL_DAYRENT*

((100 - RENTAL.SALE_SALE_DISCOUNT)/100))

Date rental

car has

been/ is to

be returned

Total

Rental

Invoice

Value 11. Create a subclass called Day Rental Charges in the Car class. Then populate the subclass

with the following objects.



Object Name

Day Rental Range

SELECT Statement RENTAL_PRICE_RANGE.RENT_RANGE

Object Description

Description of Rental Charge

banding

Model Day Rental

Charge

MODEL.MODEL_DAYRENT

Standard Day Rental Charge

12. Save the universe, then test the contexts used to resolve the loops by building the following

queries in Web Intelligence Rich Client:

• Showroom dimension and Sales Revenue measure objects. The inferred SELECT statement

for this query should use the SALES context.

• Showroom dimension and Rental Revenue measure objects. The inferred SELECT

statement for this query should use the RENTALS context.

• Showroom dimension, Sales Revenue and Rental Revenue measure objects. This query

should infer two SELECT statements, one for each context.

• Showroom, Model, and Maker dimension objects. With this query, a dialog box should

appear asking which context to use.

13. Insert the table named FRANCHISE in the universe structure. Insert the joins specified

below and set cardinalities.

• SHOWROOM.SHOWROOM_ID=FRANCHISE.SHOWROOM_ID

• FRANCHISE.MAKER_ID=MAKER.MAKER_ID

14. Detect contexts using the method of your choice.

Tip: In this instance, it is unnecessary to remove existing contexts and redetect them as they

are not affected by the FRANCHISE table and its joins.

15. Create the following object in the Showroom class, and then use it in a query to test that the

context has resolved the loop correctly.


Franchises

MAKER.MAKER_NAME

Car manufacturers with

which the showroom has a

contracted dealership. 16. Check the integrity of the Motors universe with all options except Cardinality checked.

Resolve any relevant divergence.

17. Save the Motors universe and close it.

18. Open the Staff universe. You want to report on Managers and their staff.

19. Create a class called Employees.

20. Create an alias table of the EMPLOYEE table and rename it MANAGERS.



Join the tables as shown below:

21. Create a Staff dimension object based on the EMPLOYEE table. Concatenate the Employee

Last Name and First Name.

22. Create a Managers dimension object based on the alias MANAGERS table. Concatenate the

Managers Last Name and First Name.

Tip: To get the query to infer the correct SQL, you will need to resolve the self-join in the

universe structure.

23. Check the integrity of the Staff universe with all except the cardinality options checked.

Resolve any relevant divergence.

Tip: You should not find any divergences.

24. Save the Staff universe.



Quiz: Resolving loops in a universe 1. What is the first step in resolving loops?

2. What causes a loop?

3. What are the two main methods of resolving loops?

4. What are the three types of queries you can use to test your contexts?




• Understand loops




Resolving SQL Traps—Learner’s Guide 181


Lesson 8

Resolving SQL Traps

Lesson introduction This lesson deals with two common SQL Traps: Chasm and Fan. Chasm traps and fan traps

are problems inherent in SQL that are caused by the order in which the elements of the SELECT

statement are processed.


• Understand SQL traps and universes

• Resolve fan traps

• Resolve chasm traps



Understanding SQL traps and universes In order to avoid common SQL traps in your universe, it is important to understand how

aggregates in queries may result in incorrect data.


• Explain how SQL traps can cause queries to return inaccurate results

About SQL traps Chasm traps and fan traps are problems inherent in SQL that are caused by the order in which

the elements of the SELECT statement are processed.

In SQL, a SELECT statement processes the SELECT, FROM, and WHERE clauses first (with the exception

of any aggregates). In doing so, it creates a product of all the tables in the FROM clause on the

basis of the joins and restrictions specified in the WHERE clause. This can be thought of as a

virtual table. Normally this does not cause a problem, but if an aggregate is applied then it

may, in particular circumstances, result in wrong output being generated. This is particularly

worrying because SQL does not produce an error message, it just projects the results.

Unlike loops that return fewer rows than expected, chasm traps and fan traps return too many

rows.

Fortunately, there are ways of identifying situations in which chasm traps and fan traps can

occur, and there are methods of resolving these situations.



Detecting and resolving chasm traps This unit explains how chasm traps can occur in the universe structure and how to resolve

them.


• Explain what a chasm trap is

• Detect chasm traps in a universe structure


Chasm traps A chasm trap is a common problem in relational database schemas in which a join path returns

more data than expected.

A chasm trap is a type of join path between three tables when two many-to-one joins converge

on a single table, and there is no context in place that separates the converging join paths.

You only get incorrect results when the following circumstances all exist simultaneously:

1. There is a “many-to-one-to-many” relationship between three tables in the universe structure. 2. The query includes objects based on the two “many” tables.

3. There are multiple rows returned for a single dimension value.

For example, in this diagram there is no loop, but the flow around the three tables is

many-to-one-to-many.

Note: A chasm trap is not dependent on the object types. The query could be made up of only

dimensions, only details, or only measures, or any combination of the three types with the “many”

tables for a chasm to occur.

When a query that uses objects Y and Z is run, the inferred SQL includes tables B, C, and A

that have a “many-one-many” relationship respectively. The chasm trap causes a query to

return every possible combination of rows for one measure with every possible combination

of rows for the other measure. This results in the values for each object being multiplied by the

other. The effect is similar to a Cartesian product but is known as a chasm trap.

The chasm trap is resolved by executing separate SELECT statements for object Y and object Z.



Detecting chasm traps Unlike loops, chasm traps are not detected automatically by Designer. However, you can detect

them in one of the following ways:

• Analyze the one-to-many (1-N) join paths in your schema to detect chasm traps graphically.

• Select Tools ➤ Detect Contexts or click the Detect Contexts button to automatically detect

and propose candidate contexts in your schema.

Detect Contexts examines the many-to-one (N-1) joins in the schema and proposes contexts

to separate the queries run on the table. This is the most effective way to ensure that your

schema does not have a chasm trap.

• Add additional dimension or detail objects to display more information in the report. If

there is a chasm trap, aggregated values will be doubled, alerting you to the problem.

You can use Detect Contexts to detect and propose candidate contexts, and then examine

the table where any two contexts diverge. The point where two contexts intersect is the

source of a chasm trap.

Any two tables that have multiple rows converging to a single row in the table with the

“one” relationship may potentially cause a chasm trap.

The chasm trap scenario

This section demonstrates a chasm trap in the Motors universe, and proposes two solutions to

the problem.

In the diagram below, the Sale, Client and Rental (Sale) tables are joined by a

“many-to-one-to-many” relationship.



The following objects in Motors reference the tables above:

In this scenario, the universe designer has not selected the “Multiple SQL statements for each

measure” option in the Universe Parameters SQL tab.

A user creates a series of queries using these objects and gets inaccurate results.



The first two queries return the correct data, but combining Sales Revenue and Rental Revenue

in the third query returns inaccurate results.

To understand what is happening here, you need to examine the rows that are returned by the

queries to make the aggregated figures. In this example, you can do this by adding the Sale

Date and Rental Date objects to the queries to return individual transaction details.

Notice that there are two sale transactions in the first table. There are also two rental transactions

in the second table.

If you add the dates to the combined query as in the third table, you can see why the sale and

rental revenues have doubled.

The query returns every possible combination of sale rows with every possible combination of

rental rows. Hence, the sale transactions each appear twice as do the rental transactions, and as

a result of this the aggregates have been multiplied by the number of related rows on the

alternative „many‟ table.

Where you have a many-one-many relationship for tables in the FROM clause, the resulting

logical table produces something akin to a Cartesian product. Only then is aggregation applied.

This is the reason for the chasm effect.

The problem with chasm traps is that, unless you look at the detail rows, there is nothing to

alert you to the situation.

Resolving chasm traps To resolve a chasm trap, you need to make two separate queries and then combine the results.

Depending on the type of objects defined for the fact tables and the type of end-user

environment, you can use the following methods to resolve a chasm trap:

• Modify the SQL parameters for the universe so you can generate separate SQL queries for

each measure.

This method is not recommended as it only works with measures and will result in certain

inefficiencies in processing. It does not generate separate queries for dimension or detail

objects.

• Create a context for each fact table.



This solution works in all cases and will not result in inefficiencies.

Using multiple SQL statements for each measure to resolve chasm

traps

If you have only measure objects defined for both fact tables, then you can use the Universe

Parameters option Multiple SQL statements for each measure. This forces the generation of

separate SQL queries for each measure that is used in the query. It does not work for queries

that do not contain measures.

With the option Multiple SQL statements for each measure selected, Universe Designer will

now make separate SQL SELECT statements for each measure object in the query.

The results in the report are now correct, as the query has automatically generated two SQL

statements.

Using this option will resolve the chasm trap problem. However, there are drawbacks to using

this method to resolve chasm traps.



To activate multiple SQL statements for each measure to resolve

chasm traps

1. Select File ➤ Parameters from the menu bar or click the Parameter button.

The Universe Parameters dialog box appears.

2. Click the SQL tab.

3. Click the Multiple SQL Statements for Each Measure check box in the Multiple Paths zone

to select this option.

4. Click OK.


6. In Web Intelligence Rich Client, create a new query using a dimension object, and two

measure objects from the “many-to-one-to-many” table relationship.

7. Run the query.

The results in the report are now correct, as the query has automatically generated two SQL

statements. 8. Access the SQL that is generated in the SQL Viewer by clicking the Edit Query button on

the toolbar to open the Report Panel.

9. Click on the View SQL button.

This displays the separate SQL Statements.



Drawbacks to the multiple SQL statements for each measure

method

Using the Multiple SQL statements for each measure option will resolve the chasm trap problem.

There are, however, two main drawbacks to using this method.

The results can be confusing The SQL Parameter used specifies: “Multiple SQL statements for each measure”. One of the

drawbacks is that it does not run separate SELECT statements if the query contains only

dimension objects.

The report contains a single block with the results displayed as a Cartesian product.

It is not that there is anything inaccurate about the dates, but the multiple occurrences will be

confusing to users.

The query is inefficient Another drawback is that any query including multiple measures will infer a separate SELECT

statement for each measure irrespective of whether it is required or not.



To find a complete solution to chasm traps, you must use contexts.

Using contexts to resolve chasm traps You can define a context for each table at the many end of the joins. In this example you could

define a context from Client to Sale and from Client to Rental.



When you run a query that includes objects from both contexts, this creates two SELECT

statements that are synchronized at run-time in Business Objects end-user query tools to prevent

the creation of a Cartesian product.

Creating contexts will always solve a chasm trap in a universe. When you have a

many-to-one-to-many situation, always use a context.

To use contexts to resolve a chasm trap 1. Identify the potential chasm trap by analyzing the many-to-one-to-many join path relations

in the schema.

2. Select Tools ➤ Automated Detection ➤ Detect Contexts from the menu bar or click the

Detect Contexts button.

The Candidate Contexts dialog box appears. 3. Select a proposed context in the Candidate Contexts list box and click Add to add it to the

Accept Contexts list box. Click OK.

4. Repeat for other listed contexts.

The new contexts are listed in the Contexts pane of the List View window.

5. Select File ➤ Parameters from the menu bar or click the Parameters button.

The Universe Parameters dialog box appears. 6. Click the SQL tab.

7. Select the Multiple SQL for each Context check box to clear the option.

8. Click OK.

When you run queries on the tables in the chasm trap, the query separates the SQL into

what is compatible for separate SELECT statements.

Activity: Resolving chasm traps

Objective

• Detect contexts to resolve a chasm trap in the universe structure.

Instructions 1. Create a new universe called Chasm.unv.

Use the Motors_conn connection to connect to the Motors database.

2. Select File ➤ Parameters from the menu bar or click the Parameter button and select the

SQL tab.

3. Clear the Multiple SQL statements for each measure option by clearing the check box.

4. Add the following tables:



• CLIENT

• SALE

• RENTAL (as an alias of the SALE table)

5. Create the following joins and set the cardinality:

Join Cardinality

CLIENT.CLIENT_ID=SALE.CLIENT_ID 1:N

CLIENT.CLIENT_ID=RENTAL.CLIENT_ID 1:N

SALE.SALE_TYPE='S' 1:1

RENTAL.SALE_TYPE='R' 1:1

6. Create two classes: one called Chasm Objects, and the other called Measures.

7. Add the following objects with the following syntax:

Object SELECT Qualification

Client Name CLIENT.CLIENT_LASTNAME

+ ' , ' + CLIENT.CLIENT_FIRSTNAME

Dimension

Sale Date SALE.SALE_DATE Dimension

Rental Date RENTAL.SALE_DATE Dimension

Sales Revenue Sum(SALE.SALE_TOTAL) Measure

Rental Revenue Sum(RENTAL.SALE_TOTAL) Measure

8. Perform an integrity check on:

• Check Universe Structure

• Parse Objects

• Parse Joins


10. In Web Intelligence Rich Client, create a new document with two “control” queries to display

the correct sales and rental figures for Paul Brendt in the Chasm universe.

• In the first query, use the Sale Revenue, and Client Name objects.



Select the Client Name object, and click the Apply a Quick Filter button. From the List

of Values, select Brendt, Paul.

• In the second query, use the Rental Revenue, and Client Name objects.

Select the Client Name object, and click the Apply a Quick Filter button. From the List

of Values, select Brendt, Paul.

11. Click Run Queries and view the results in the report.

• What is the sale amount now?

• What is the rental amount? 12. In the same report add a new table by clicking the Edit Query button. Click Add Query,

and create a new query using the Sale Revenue, Rental Revenue, and Client Name objects.

Select the Client Name object, and click the Apply a Quick Filter button. From the List of

Values, select Brendt, Paul.

13. Click View SQL to check the SQL statement generated.

14. Click Run Queries and select the Insert a table in the current report option.

• What is the sale amount in the new table?

• What is the rental amount in the new table?

• What happened to your figures? 15. Log out of Web Intelligence Rich Client.

16. In Universe Designer, edit the universe by clicking File ➤ Parameters ➤ SQL tab, and select

the Multiple SQL statements for each measure option.


18. In Web Intelligence Rich Client, create a new document using the Sale Revenue , Rental

Revenue, and Client Name objects. Select the Client Name object, and click the Apply a

Quick Filter button. From the List of Values, select Brendt, Paul. Click View SQL to check

the SQL statement generated.

• What is the sale amount?

• What is the rental amount in the new table?

• What happened to your figures? 19. Edit the query by clicking the Edit Query button on the toolbar.

20. Remove the Sales Revenue, and the Rental Revenue objects. Drag the Sale Date, and Rental

Date objects into the Report Panel. Click Run Query.

• What happens to the SQL and to the results?

21. Log out of Web Intelligence Rich Client.

22. In Universe Designer, edit the universe by clicking File ➤ Parameters ➤ SQL tab and

clear the Multiple SQL statements for each measure option again (clear the check box).

23. Insert the following contexts:



Context

Joins

Sale CLIENT.CLIENT_ID=SALE.CLIENT_ID

SALE.SALE_TYPE='S'

Rental CLIENT.CLIENT_ID=RENTAL.CLIENT_ID



25. In Web Intelligence Rich Client, create a new query with the Client Name, Sales Revenue,

and Rental Revenue objects. Select the Client Name object and click the Apply a Quick

Filter button. From the List of Values, select Brendt, Paul.


• What is the rental amount?

• What happened to your figures?



Detecting and resolving fan traps This unit explains how fan traps can occur in the universe structure and how to resolve them.


• Explain what a fan trap is

• Detect fan traps in the universe structure


Fan traps Fan traps occur when there is a “one-to-many” join to a table that “fans out” into another

“one-to-many” join to another table.

This is a common structure and will not normally result in a fan trap. You only get incorrect

results from the fan trap when the query includes a measure object on the middle table (B) of

the table path and an object (of any kind) from the subsequent table (C). The trap only occurs

where (due to the database design) a column in table B holds data values which are already a

sum of those values held at table C. The results are normally noticeably wrong.

When a query is run using objects Y and Z, the inferred SQL includes tables B and C which

have a „one-to-many‟ relationship. This results in a value for the Y object being multiplied by

the number of values of the Z object related to that Y object value. Like the chasm trap, the

effect is similar to a Cartesian product.

Like the chasm trap, the fan trap can be resolved by executing a separate SELECT statement for

object Y and object Z. The alternate solution is to avoid it in the first place.

You cannot automatically detect fan traps. You need to visually examine the direction of the

cardinalities displayed in the table schema.

If you have two tables that are referenced by measure objects and are joined in a series of

“many-to-one” joins, then you may have a potential fan trap.



The fan trap scenario This section demonstrates a fan trap in the Motors universe, and proposes solutions to the

problem.

In the diagram below, the Client and Sale tables are joined by a “many-to-one-to-many”

relationship, as are the Sale and Sale_Model tables.

The fan trap problem becomes apparent in a query that aggregates both an object based on the

Sale_Total column in the Sale table, and an object based on the Sale_Qty column in the

Sale_Model table.



What happens in the fan trap When you run the Test 1 query to report the Sales Revenue for a client, the measure is correctly

aggregated. This is a simple aggregate from one table in the fan trap structure. However, if

you also wanted to know the number of vehicles the client has purchased, and you included

the Number of Cars Sold object in the query, you get an inflated value returned for Sales

Revenue.

To understand what is happening, you need to look at the rows that are returned. Since two

different Model ID numbers are involved in the Sale Quantity (Number of Cars Sold), there

are two rows returned.

As with chasm traps, a single SELECT statement joins each Model ID row with the same Sales

Revenue row, which gives you the doubled figure.

There is nothing to alert you to the situation, unless you look at the detail rows.

Where you have a one-many-many relationship for tables in the FROM clause the resulting logical

table produces something akin to a Cartesian product. Only then is aggregation applied. This

is the reason for the fan effect.

Resolving fan traps The recommended ways to solve a fan trap problem are:

• Alter the SQL parameters for the universe.

• Use a combination of aliases and contexts.

• Avoid the fan trap scenario.

Alter the SQL parameters for the universe This method is not recommended as it only works for measure objects and may result in

inefficiencies in processing the query. This resolution works the same for chasm and fan traps.

Use a combination of aliases and contexts There are two possible situations which may require different solutions.

If you have... Then...

• Three tables in a one-to-many

relationship

• A dimension coming from

the first table and measures

Create an alias for the table (on the many end of the join)

containing the initial aggregation, joining it back to the

non-aggregation table (on the one end of the join). Use the

Detect Contexts tool to detect and propose a context for the

alias table and a context for the original table.



If you have...

coming from the two

subsequent tables

Then...

This is the most effective way to solve the fan trap problem

because it works with measure and dimension objects and

does not cause inefficiencies.

• Two tables in a one-to-many

relationship

• A dimension and a measure

coming from the first table

and a measure coming from

the subsequent table(s)

Create an alias for the table containing the initial aggregation,

joining it back to the original table and then use the Detect

Contexts tool to detect and propose a context for the alias

table and a context for the original table.

Both of these methods solve the fan trap problem because

they will work with both measure and dimension objects

and do not cause inefficiencies. You will explore both in the

following sections.

Note: However, to be more efficient still, using the two-table scenario,

you could also use the @aggregate_aware function.

Avoid the fan trap scenario You can avoid the scenario in the first place by relating all measure objects in the universe to

the same table in the universe structure. Avoid placing a measure on anything other than the

last table in a table path, which is the table with the “many” cardinality attached to it.

Using aliases and contexts to resolve fan traps You create an alias table for the table producing the aggregation and then detect and implement

contexts to separate the query. This procedure is demonstrated in the diagram below:

In this scenario your schema would look similar to:



The SELECT clause of the Sales Revenue object needs to be edited, so that it refers to the alias

table rather than the original Sale table.

As with resolving a chasm trap problem, two contexts need to be created. In this example, a

context for Sale, and a context for Sale_Model need to be defined. This allows for the results

to be merged into a single microcube to produce the correct results.

Moreover, if you make a query which includes a dimension object on the lower table in the

„one-many-many‟ path, you will not suffer the fan trap, even when that dimension object

contains the same value for all rows related to the measure value. The fact that the measure

and dimension objects are in separate contexts forces two separate SELECT statements, thus

avoiding the problem.

To use aliases and contexts to resolve a fan trap 1. Identify the potential fan trap by analyzing the one-to-many-to-one-to-many join path

relations in the schema.

2. Create an alias for the table that is producing the multiplied aggregation.

3. Create a join between the new alias table, and the table that holds the dimension information.

4. Set cardinality.

5. Set contexts.

6. Change the SELECT clause of the measure object so that it refers to the alias table rather than

the original table.



7. Create a query using a measure object from the alias table and another measure from the

subsequent table in the table path of the universe structure.

This results in two SELECT statements and the data is merged into a single microcube to

produce the correct results.

Solving a fan trap with two tables in a one-to-many relationship

The structure shown here involves two tables instead of three. In this example, both a dimension

and measure object are from the same table, and another measure is from a table in a

one-to-many relationship further along the universe structure.

To resolve this type of fan trap, you can:

1. Create an alias of table A.

2. Create a join from the alias An to table A and set cardinalities.

3. Set contexts B and A.

4. Edit object Y so that it refers to columns in the alias An rather than table A.

In the universe structure shown below, you have created an alias table of the Sale table and

created a join between the alias and the original table. This is to separate the dimension in Sale

from the measure, which will now refer to Sale_Alias.



To use aliases in a fan trap involving only two tables 1. Create an alias of the table that contains both dimension and measure values.

2. Create a join between the new alias table, and the original table.

3. Force the cardinality for this join to N:1.

4. Set contexts.

5. Change the SELECT clause of the measure object so that it refers to the new alias table rather

than the original table.


7. In Web Intelligence Rich Client, test the solution using a dimension object from the original

table, a measure object from the alias table, and a measure from the second table in the

schema.

When you look at the SQL in the SQL Viewer, there will be two SELECT statements.

Note: Aggregate awareness provides another solution to this problem.

Avoiding fan traps altogether In certain situations, it is possible to avoid the fan trap completely, as shown in the diagram

below.

To avoid the trap, the database column in table B to which the Y measure object relates must

represent a preaggregation of more detailed data in table C. If this is the case, you can change



the code of the Y measure object so that it refers to table C. Hence, there is no longer a

„one-to-many‟ relationship incurred.

This is the method used to avoid the fan trap in the Motors universe, when the Sales Revenue

and Number of Cars Sold measure objects are included in the same query.

In the Motors universe you have created during this course, the Sales Revenue measure is not

based on the total figure in the SALES table but on a number of columns from the Sale,

Sale_Model and Model tables which are held in the database at the same level of granularity

as the number of cars sold. Hence, no fan trap exists and the correct result will be obtained.

Note: Another method of resolving a less common form of fan trap is by using Aggregate Awareness.



Activity: Resolving fan traps Objective

• Detect contexts to resolve a fan trap in the universe structure.

Instructions 1. Create a universe called Fans.unv.

Use the Motors_conn connection to connect to the Motors database.

2. Select File ➤ Parameters from the menu bar or click the Parameter button and select the

SQL tab.

3. Clear the Multiple SQL statements for each measure option by clearing the check box.

4. Add the following tables:

• CLIENT

• SALE

• SALE_MODEL

5. Create the following joins and set the cardinality:

Join Cardinality

CLIENT.CLIENT_ID=SALE.CLIENT_ID 1:N

SALE.SALE_ID=SALE_MODEL.SALE_ID 1:N

SALE.SALE_TYPE='S'

6. Create a class called Fan Objects.

7. Add the following objects with the following syntax:

1:1




Client Name

CLIENT.CLIENT_LASTNAME

+ ' , ' + CLIENT.CLIENT_FIRSTNAME

Dimension

Model ID SALE_MODEL.MODEL_ID Dimension

Sale Quantity Sum(SALE_MODEL.SALE_QTY) Measure

Sales Revenue Sum(SALE.SALE_TOTAL) Measure

8. Perform an integrity check on:

• Check Universe Structure

• Parse Objects

• Parse Joins 9. Save the universe.

10. In Web Intelligence Rich Client, create a new document using the Sales Revenue and Client

Name objects. Select the Client Name object and click the Apply a Quick Filter button.

From the List of Values, select Crandall, Sean.

11. Click Run Query and view the results in the report.

• What is the sale amount? 12. Edit the query and add the Sale Quantity object.

• What is the sale amount now?

• What is the sale quantity? 13. Log out of Web Intelligence Rich Client.

14. In Universe Designer, edit the universe by clicking File ➤ Parameters ➤ SQL tab and select

the Multiple SQL statements for each measure option.


16. In Web Intelligence Rich Client, create a new document using the Sales Revenue, Sale

Quantity, and Client Name objects. Select the Client Name object and click the Apply a

Quick Filter button. From the List of Values, select Crandall, Sean.



• What is the sale quantity? 18. Edit the query and add the Model ID object.

• What is the total sale amount?

• What is the total sale quantity?

• How many different models were purchased?

• What happened to your figures?



Tip: To retrieve the sum value, highlight the relevant measure column without highlighting

the header, and select the Insert Sum toolbar icon.

19. Log out of Web Intelligence Rich Client.

20. In Universe Designer, edit the universe by clicking File ➤ Parameters ➤ SQL tab and clear

the Multiple SQL statements for each measure option by clearing the check box. Select the

Multiple SQL statements for each context option if it is not already selected.

21. Add an alias to the SALES table (SALES2).

22. Create the following joins:

Join Cardinality

CLIENT.CLIENT_ID=SALE2.CLIENT_ID 1:N

SALE2.SALE_TYPE='S' 1:1

Note: Force the cardinality on CLIENT.CLIENT_ID=SALE2.CLIENT_ID join to 1:N.

23. Use the Detect Contexts button to detect contexts.

Be sure you have the following contexts. You may have to edit the context by removing or

adding joins.

Context Joins

Sale Model

CLIENT.CLIENT_ID=SALE.CLIENT_ID

SALE.SALE_ID=SALE_MODEL.SALE_ID

SALE.SALE_TYPE='S'

Sale2 CLIENT.CLIENT_ID=SALE2.CLIENT_ID

SALE2.SALE_TYPE='S'

24. Modify the definition of the object that is performing multiple aggregations so that it points

to the alias table:


Sale Revenue Sum(SALE2.SALE_TOTAL) Measure 25. Save the universe.

26. In Web Intelligence Rich Client, create a new document using the Sales Revenue, Sale

Quantity, and Client Name objects. Select the Client Name object and click the Apply a

Quick Filter button. From the List of Values, select Crandall, Sean.




o What is the total sale amount?

o What is the total sale quantity?

o How many different models were purchased?

o What happened to your figures?



Quiz: Resolving SQL traps 1. A chasm trap can occur when:

2. Describe two ways to resolve chasm traps.

3. Describe three ways to resolve fan traps.




• Understand SQL traps and universes



Applying Restrictions on Objects—Learner’s Guide 209


Lesson 9

Applying Restrictions on Objects

Lesson introduction This lesson will help you understand and use restrictions, which are conditions in SQL that set

criteria to limit the data returned by a query.


• Restrict the data returned by objects



Restricting the data returned by objects A restriction is a condition in SQL that sets criteria to limit the data returned by a query.

You define restrictions on objects to limit the data available to users. Your reasons for limiting

user access to data depend on the data requirements of the target user. A user may not need

access to all the values returned by an object. You might also want to restrict user access to

certain values for security reasons.


• Define data restrictions

• Apply data restrictions to objects

• Apply data restrictions using condition objects

• Apply restrictions to tables

• Apply data restrictions using the Tables button

• Apply each type of restriction

Defining data restrictions The WHERE clause in an SQL statement restricts the number of rows that are returned by the

query.

So far in your universe design work, the WHERE clauses have only been populated by the joins

you made between the tables in the Structure pane.

The joins restrict the resultsets, usually based on equality between tables and prevent Cartesian

products.

You can also use the WHERE clause to further restrict the data that is returned in a query in

circumstances where you may want to limit certain users to query on a subset of the data.

For example, the report below is an unrestricted block containing data for Clients from all

Countries:



The WHERE clause for the query is created from the SQL inferred from the joins made in the

Structure pane:

WHERE (COUNTRY_REGION.COUNTRY_ID=REGION.COUNTRY_ID)

AND (REGION.REGION_ID=CLIENT.REGION_ID)

AND (SALE_MODEL.MODEL_ID=MODEL.MODEL_ID)

AND (SALE.SALE_ID=SALE_MODEL.SALE_ID)

AND (CLIENT.CLIENT_ID=SALE.CLIENT_ID)

AND (SALE.SALE_TYPE='S')

AND (SALE.SALE_DATE between FINANCE_PERIOD.FP_START

and FINANCE_PERIOD.FP_END)

Compare this with the following report, which is a restricted block containing data only for

clients from the United Kingdom:

The WHERE clause for the query now has an extra line at the bottom. This is the restriction added

by the designer that limits the return of data to UK Clients:

WHERE (COUNTRY_REGION.COUNTRY_ID=REGION.COUNTRY_ID)

AND (REGION.REGION_ID=CLIENT.REGION_ID)

AND (SALE_MODEL.MODEL_ID=MODEL.MODEL_ID)

AND (SALE.SALE_ID=SALE_MODEL.SALE_ID)

AND (CLIENT.CLIENT_ID=SALE.CLIENT_ID)

AND (SALE.SALE_TYPE='S')

AND (SALE.SALE_DATE between FINANCE_PERIOD.FP_START

and FINANCE_PERIOD.FP_END) AND (COUNTRY_REGION.COUNTRY_NAME = ‘United Kingdom’

Methods of restricting data in end-user modules Within the design of a universe, you can either:

• Force restrictions, which the end user cannot override: Object, Table, Conditional SELECT,

Additional Joins

• Provide optional restrictions, which the end user can choose to apply: Condition Objects Remember that users can apply conditions themselves by way of the Report Panel. Therefore,

avoid creating optional restrictions that are of a simple nature, as the end user should be capable

of creating such conditions for themselves on a query-by-query basis.

There are often problems associated with inferred restrictions, as will become evident during

this module. You are therefore advised only to force restrictions where they are absolutely

necessary.



To ensure that a restriction is always inferred when a particular object is used in an end-user

query, place the restriction in the Where box of the Definition tab in the Edit Properties dialog

box related to the object. You can do this when you create the object or you can add it later.

To apply a restriction to an object 1. Open the Edit Properties dialog box for the object and select the Definition tab.

2. Enter the restriction directly in the Where field, or via the Edit Where Clause dialog box

by selecting the >> button.

3. Click OK.

When you have created or edited your object to include a restriction, you should test it by

running a new query using a BusinessObjects end-user query tool. Always view the inferred

SQL to check whether the SELECT statement includes the restriction in the WHERE clause and

has the desired effect. Remember to save your universe before doing this.

The inferred SQL displays the restriction. The last line of the WHERE clause is taken from the

object restriction.

Drawbacks to applying restrictions to objects

Only create restrictions against objects when it is absolutely necessary.

For example, consider the situation where users of Motors need to make queries of only those

cars that can be rented. The only distinguishing factor in the underlying Motors database

between cars that can be rented and those that are stocked for sale is that the

Model.Model_Dayrent column contains data for rental cars and is null for sale-only cars. To

create an object to list cars for rental, the object would have to include the restriction:

Model.Model_Dayrent is not null.

If it is not necessary, do not create the restriction.

To see why, consider the implications of creating a UK Clients object as illustrated:



The drawbacks are as follows:

• You would get a confusing proliferation of objects for end users because you would then

need a French Clients object, a German Clients object, and so on.

• As these objects would all represent alternate restrictions, you would not be able to construct

a logical default hierarchy, which end users make use of when drilling down.

• Although the UK Clients example is fairly clear, in many cases the restriction will not be

obvious to the user simply from the name of the object: the details of the WHERE clause are

not shown in the end-user interface.

• If two or more similarly restricted objects are included in the same query, the conflict between

the WHERE clauses will cause no data to be returned.

Consider the situation if a user wanted data for UK Clients and US Clients. You might think

that including both the UK Clients and US Clients objects would meet that need. However,

the inferred SQL for the query would include the following two lines:

AND (CLIENT_COUNTRY.COUNTRY_NAME = ‘United Kingdom’)

AND (CLIENT.COUNTRY.COUNTRY_NAME = ‘USA’)

As no country satisfies both these conditions, no data is returned.

An alternative to applying restrictions to objects

There is an alternative to applying restrictions to objects without using WHERE clauses. You will

still have multiple objects, but you will avoid the conflicts that affect the return of data in

queries.

This method involves using a conditional SELECT clause for the object instead of a WHERE clause.



For example, if you want to force users to select financial results by year, you could create a

series of Sales Revenue objects (one for each year). Each object would be edited, starting from

the standard sum aggregate used in the basic Sales Revenue SELECT statement:

You would apply the condition for each year using the database function that applies IF THEN

ELSE logic.

For Sales Revenue 2003, the SELECT statement would look like this:

Note: The Else value 0 is optional.

For Sales Revenue 2004, the SELECT statement would look like this:

Note: Many databases support the CASE function. Consult the documentation provided by your

database vendor to see what types of conditional functions are supported.

After you have created or edited the objects, test them individually and together in a single

query. When you view the SQL to check whether the inferred SELECT statement includes the

conditional SELECT syntaxes, the SQL appears as follows:

When the query is run, the report looks similar to this:



The conditional SELECT statements have removed the problem of the conflicting WHERE clauses.

The data correctly shows the 2003 and 2004 Sales Revenue for each client.

Restrictions using condition objects A condition object, or predefined query filter, is a preset restriction created in Universe Designer

that a user can choose whether or not to apply to a query.

When users create queries they can create their own query filters to limit the data returned by

the query. They can also use the predefined query filters that the universe designer may have

built into the universe to make it easier for them to restrict the data.

In Web Intelligence Rich Client, the predefined query filter built into the universe can be viewed

in the Report Manager Data tab, identified as predefined query filters.

For example, if the designer has created condition objects for French Clients and UK Clients,

the Predefined Conditions tab would contain these condition objects:

When you have created a condition object in Universe Designer, test it in Web Intelligence Rich

Client by making a query that uses the filter. View the SQL to check that the inferred SELECT

statement includes the restriction in the WHERE clause and has the desired effect.

The advantages of using condition objects • Useful for complex or frequently used conditions

• Gives users the choice of applying the condition

• No need for multiple objects



• Condition objects do not change the user view of the dimension objects in the Classes and

Objects tab in the Web Intelligence Rich Client Report Panel

To create a condition object

1. In Universe Designer, select the Filter option button at the bottom of the Universe pane.

The Universe pane changes to show the Condition Object View.

Note: Objects are not shown in the Condition Object View, but classes are. You add a

condition object to a particular class. Also, be aware that deleting a class in the Condition

Object View will delete that class from the whole universe, not just from this view.

2. Click the class in which you want to place the condition object.

3. There are two ways you can insert a condition:

• Select the Insert Condition on the Editing toolbar.

• Right-click the class and choose Condition from the drop-down menu.

This opens the Edit Properties dialog box for condition objects.

4. In the Name field, enter a name for the condition object.

5. In the Description field, enter a help message for users describing the condition and any

effect it will have on queries they make.

6. Enter the condition directly in the Where field or via the Edit Where Clause dialog box by

selecting the >> button.

7. Click OK.


The new predefined condition object built into the universe can be viewed in Web Intelligence

Rich Client in the Report Panel Data tab.

Applying restrictions using the tables button If a table in your database has a flag that is used to switch between two or more domains, you

can use this to apply restrictions at the table level.

For example, the Sale table in the Motors database has a column called Sale_Type, which is

used to distinguish between sales transactions and rentals transactions. The flag is set to S for

sales or R for rentals.

If you do not apply any restriction to this table, users running queries for sales (with appropriate

objects) will get a resulting report that includes data on rentals as well as sales. Therefore, the

results will be wrong.

You can apply a restriction to this table using a self-restricting join.

The self-restricting join appears as a stub join in the Structure pane:



The expression in the Edit Join dialog box is set as follows:

With this restriction in place, the data returned will be restricted to sales data, no matter where

the table is used in the inferred SQL.

For example, if the Sale table appears only in the FROM clause of the SQL, the restriction will

still be applied in the WHERE clause.

This is the main advantage of applying restrictions at the table level.

A lookup table in a database can be used to provide a description for more than one dimension

from a database.

For example, in the Motors database, the Country table contains a single list of countries, but

these include the country from which clients come, the country where a car showroom is located,

and the country where a car maker is located.

As a designer, you can create objects from the Country table for use in the Client class (for the

Client Country), in the Car class (for the car Maker Country), and in the Showroom class (for

the Showroom Country). We have done this in previous lessons and avoided loops by creating

the appropriate alias tables.

If a user ran a query to answer the question: “Which countries do our showrooms exist in?”,

you might think that a simple query using only the Showroom Country object in the Showroom

class would provide the answer. However, in the current universe, such a query would actually

infer SQL that returns all countries held in the Showroom_Country table.

SELECT

SHOWROOM_COUNTRY.COUNTRY_NAME

FROM

SHOWROOM_COUNTRY

To solve this problem, the Showroom Country object in the Showroom class must be restricted

so that it returns only country data relating to showrooms.

This is done by specifying that whenever the Showroom Country object is used in a query, the

Showroom table must also be inferred in the FROM clause of the SELECT statement. Providing

that the Showroom_Country table is joined to the Showroom table (by intervening tables) using



only equi-joins, the object is then guaranteed to only return countries in which showrooms

exist.

To restrict data by adding tables to the object definition 1. Double-click the object you want to restrict.

The Edit Properties dialog box for the selected object displays. 2. Click the Tables button.

The Tables dialog box appears. 3. Scroll down the list of tables until you can see the table that is already highlighted.

4. Hold down the Ctrl key and click an additional table to force joins between the selected

tables.

5. Click OK to close the Tables dialog box.

6. Click Apply in the Edit Properties dialog box.

7. Click OK.

Applying each type of restriction Apply restrictions to objects when you need to force a restriction on users. However, the forced

restriction is not automatically inferred whenever the table is included in the SQL. Be aware

of the drawbacks of multiple objects and conflicting restrictions. Use conditional SELECT

statements instead.

Use condition objects when you want to assist users by providing optional filters, and when it

is important to avoid multiple objects and changes to the Classes and Objects view.

Use self-restricting joins to apply restrictions to tables when you want the restriction to apply,

irrespective of where the table is used in the SQL. This method is ideal when a table uses a flag

to switch between two or more domains.

Use additional joins when a lookup table serves more than one purpose in the universe. This

method ensures that the user gets the correct answer to the question behind the query.

Activity: Applying restrictions Objective

• Apply enforced restrictions to objects and tables and create optional restrictions using

condition objects.

Instructions The sales staff of Prestige Motors needs to drill from Day Rental Range through Model Day

Rental Charge to Model for Rental to deal with queries from potential customers.



1. Create a Model for Rental dimension object in the Day Rental Charges subclass.

This object will have the same SELECT properties as the Model object. 2. Add a WHERE restriction to the Model for Rental object so that only models available for rent

are returned. The restriction is:

MODEL.MODEL_DAYRENT IS NOT NULL

3. Create a US Clients dimension object in the Client class below the Client Name object with

the settings:


• Description = Returns only data for clients in the USA

• Select syntax:

CLIENT.CLIENT_LASTNAME

+ ', ' + CLIENT.CLIENT_FIRSTNAME

• Where syntax:

COUNTRY_REGION.COUNTRY_NAME = 'USA'

4. Create another object in the Client class for UK Clients.

5. Save the universe, then test the two new Client objects in Web Intelligence Rich Client:

• Build a query containing UK Clients, US Clients, and Sales Revenue objects

The query returns no data because of the conflict of restrictions.

6. In Universe Designer, create a new subclass below the Sales class called Annual Revenue.

Populate it with separate Sales Revenue measure objects for the calendar years 2003 and

2004 as indicated below. Use the CASE function to do this.

• 2003 Sales Revenue

• 2004 Sales Revenue 7. In the Annual Revenue subclass create two separate Sales Revenue measure objects related

to financial years FY03-04 and FY04-05 as indicated below. Use the CASE function to do this.

• Sales Revenue for FY03-04

• Sales Revenue for FY04-05

8. Save the universe, then test the two new calendar year Sales Revenue objects in Web

Intelligence Rich Client:

• Build a query containing Showroom, 2003 Sales Revenue, and 2004 Sales Revenue objects.

• Replace 2003 Sales Revenue and 2004 Sales Revenue objects with the objects related to

financial years FY03-04 and FY04-05, instead of calendar years.

9. Remove the US and UK objects in the Client class that you just created, and create the

following condition objects instead:

• A condition object for US Clients

• A condition object for European Clients (excluding UK; UK clients are part of the Other

Clients condition object)

• A condition object for Other Clients



10. Save the universe and test each restriction by building a query in Web Intelligence Rich

Client.

11. Run a query using Showroom Country to see the list of countries that have showrooms.

12. In Universe Designer, edit the properties of the Showroom country object by adding the

Showroom table to the list of tables associated with the object. Use the Tables button in the

Edit Properties, Definition tab of the object to do this.


14. In Web Intelligence Rich Client, run the above query again and compare the results.

15. In Universe Designer, ensure that the Client Country object will only return the countries

in which clients exist, whichever query is run. Do this by adding the Client table to the list

of tables associated with the object.

16. Edit the Maker Country object in the same way, to ensure that it only returns the countries

in which car makers exist.

17. Edit the Franchise object so that it automatically infers the FRANCHISE context instead of

prompting the user to choose among the SALES, RENTALS and FRANCHISE contexts. This

allows end users to report on the franchises and their location regardless of sales or rentals

information.

Use the Tables button to highlight the MAKER and FRANCHISE tables.

18. Check the integrity of the universe.




Quiz: Applying restrictions on objects 1. What is a restriction?

2. Explain two drawbacks of using restrictions at the object level.

3. When should you use self-restricting joins?



Lesson summary


• Restrict the data returned by objects

Using @functions with Objects—Learner’s Guide 223


Lesson 10

Using @functions with Objects

Lesson introduction This lesson will help you use the @functions to provide more flexible methods for specifying

the SQL for an object.


• Use @functions



Using @functions The @functions are located in the Functions panel of the Edit Select Statement and in the Edit

Where Clause dialog boxes for objects.


• Define @functions

• Use the @prompt function

• Use the @select function

• Use the @where function

• Describe the @aggregate_aware function

Defining @functions In the Edit Properties dialog box of an object, if you look in the Functions panel of either the

Edit Select Statement dialog box or the Edit Where Clause dialog box, you will find a list of

@functions.

The most commonly used @functions are:

• @prompt(,,,,)

• @select()

• @where()

• @aggregate_aware(,)

These functions can be applied in the Select and/or Where dialog boxes of objects.

@function Can be used in...

@prompt Both Select and Where clauses

@select

Only to be used in Select clauses

@where

Only to be used in Where clauses

@aggregate_aware

Only to be used in Select clauses

The @functions are used to provide flexible methods of specifying SQL.

@prompt The @prompt function is used by the designer to force the end user to enter a value for a

restriction when a query is run which includes the object in which the @Prompt is specified.

This is done by placing a restriction based on the @prompt in the Where field of the Edit

Properties dialog box of an object. When the user runs a query including that object, a prompt

dialog box appears requesting a value to be entered.

It can be useful when you want to force a restriction in the inferred SQL but do not want to

preset the value of the condition. For example:



In the example, the object Model for Rental is to be used by a salesman to list the models that

can be rented. However, different models are rented from different showrooms. Hence, you

would want to restrict the returned list to cars rented from a single showroom. If you hard

coded the restriction, you would need a separate object for each showroom in the universe.

Using the @prompt, you need only one.

@prompt syntax The @prompt syntax consists of five parameters, separated by commas:

• Prompt

• Data type (A, N, or D)

• LOV pointer or hard-coded list

• Mono or multi

• Free or constrained

• Primary key

• Persistent or not persistent

• 'Default value':'key value'

The first two parameters are mandatory, and the remaining parameters are optional.

Note: The first three parameters must be inside single quotes.

The last three parameters; primary key, persistent/not persistent, and 'default value: key value',

are newly added in BusinessObjects XI 3.0.

The full syntax of the @prompt function is as follows:

@prompt('message','type',[lov],

mono/multi,free/constrained/primary_key,



persistent/not_persistent, [{'default

value':'default key' [,'default

value':'default key',...]})

For example:

SHOWROOM.SHOWROOM_Name =

@prompt('Enter Showroom Name','A', 'Showroom\Showroom', Mono, Constrained)

Prompt This is the text, or question, that appears in the prompt dialog box when the query is run. The

text must be enclosed in single quotes.

Data type Data type refers to a character to specify the type of data that will be returned:

„A‟ for alphanumeric

„N‟ for numeric

„D‟ for date

The specified character must be enclosed in single quotes.

List of values (optional) There are two methods of specifying a list of values:

• A hard-coded list:

Each value is separately enclosed in single quotes and separated by a comma and the whole

list is enclosed in curly brackets. For example:

{'Australia', 'France', 'Japan',

'United Kingdom', 'USA'}

• A pointer to a list of values from an existing object:

This can be invoked by double-clicking the object whose list of values you want to use in

the Classes and Objects pick list. This gives the class name and the object name, separated

by a back-slash. It must be enclosed in single quotes. For example:

'Client\Country'

Mono or multi (optional) • Mono: Allows the user to select or enter a single value from the list of values.

• Multi: Allows the user to select or enter multiple values from the list of values.

Free or constrained (optional) • Free: Users can enter a value of their own, or pick one from the list of values.

• Constrained: Users can only choose a value from the list of values.



Primary key Use the primary key parameter with "free" or "constrained". The user enters a value or selects

from the list of values. If the primary key parameter is present, the entered or displayed value

is not used to generate the query. The associated key value from the index awareness column

is used.

Persistent or not persistent • Persistent: When refreshing a document, the last values used in the prompt is displayed by

default.

• Not persistent: When refreshing a document, no values used is displayed in the prompt by

default.

'Default value':'key value' The default values parameter is used to define default values presented to the user.

You can define multiple default values. The syntax for each default value is: „value‟:‟key‟. The

colon (:) is the separator between the value and the key.

When refreshing a document these values are displayed by default but if the persistent option

is set, then the last values used in the prompt are used instead of the default values.

If you specify the primary key parameter in the prompt definition, then you must provide the

key value(s).

@prompt('Enter value(s) for City:',

'A','City Class\City',Multi,Constrained, Persistent,User:0,KEY_'N')

@prompt('Enter value(s) for Client Name: ',

'A','Client\Client Name',Multi,primary_key, {‘Baker’:’1’,‘Brendt’:’2’})

@select The @select function is a pointer to the Select dialog box properties of another object. It is used

by placing the @select in the Select field of the Edit Properties dialog box of an object, using

the following syntax:

@select(path of existing object)

You specify the path in the form Class_Name\Object_Name.

The purpose of the @select function is to allow you to reuse existing code, giving the advantage

of having to specify SQL code only once. Specifying SQL only once has two key advantages:

• You need to maintain only one instance of the SQL code.

• It ensures consistency of the code.

For example:



This shows how the @select works. The code in the SELECT properties of the Model object is:

MODEL.MODEL_NAME+' '

+ MODEL.MODEL_TRIM+' '+MODEL.MODEL_ENGINE

If you wish to create a new object called Model for Rental with the same code, rather than

creating the same code twice, you can refer to the original Model object via the @select function:

@select(Car\Model)



The benefit is that a dynamic link is created between the objects. When changes occur in the

SELECT statement of the original object, the changes are reflected in the SELECT statement of

any other objects that refer to it via the @select function. Therefore, when you change the code,

you only change it once in the original object.

@where The @where function is a pointer to the Where dialog box properties of another object.

It is used by placing the @where in the Where field of the Edit Properties dialog box of an object,

using the following syntax:

@where(path of existing object)

For example:



This shows how the @where works. The code in the Where properties of the Model for Rental

object is:


AND SHOWROOM.SHOWROOM_NAME = @prompt('Enter Showroom Name', 'A','Showroom\Showroom',mono,constrained)

If you wish to create a new object called Showroom Rental Model that has to contain the same

WHERE syntax, rather than creating the same code twice, you can refer to the original Model for

Rental object via the @where function:

@where(Day Rental Charges\Model for Rental)



The benefit is that a dynamic link is created between the objects. When changes occur in the

WHERE statement of the original object, the changes are reflected in the WHERE statement of any

other objects that refer to it via the @where function. Therefore, when you need to change the

syntax, you only change it once in the original object.

Note: You can use the @where function in a condition object to point to an object, but not the other

way around.

As with @select, its purpose is to allow you to reuse existing code, and it has the same

advantages:

• You need to maintain only one instance of the SQL code.

• It ensures consistency of the code.

There are further benefits for using the @where function. If there are a number of objects and/or

condition objects that require the same restrictions to be placed upon them, you could use a

WHERE restriction object strategy to make the most efficient use of that restriction‟s code.



The idea behind the strategy is that you create a new and separate object for every restriction

required, in a separate class to the “normal” object classes. Then, within the original objects,

whenever a restriction is required, you point to the appropriate WHERE restriction object using

the @where function.

In the previous example, you can see that two Where clause restriction objects have been created

that contain only a name and Where clause restriction, as follows:

Rental model


Showroom choice

SHOWROOM.SHOWROOM_NAME

= @prompt ('Enter Showroom Name','A', 'Showroom\Showroom',mono,constrained)

Note that each of the Where clause restriction objects do not have SELECT properties specified.

The @where pointer can now be used to specify the restrictions required for the object called

Model for Rental without the need to double up on the WHERE syntax.

Also, by specifying each restriction in a separate Where clause restriction object, the strategy

has enabled you to build up the multiple restrictions on the object one step at a time. This is

particularly useful when creating complex restrictions on an object.

Moreover, the individual restrictions can be used for other objects and condition objects. In the

example above, the Where clause restriction object called Showroom Choice has also been used

for the Showroom condition object.

For this strategy to work, you need to be able to hide the class containing all the Where clause

restriction objects from end users.

The Where clause restriction object strategy has a number of advantages:

• Maintenance is easy because only a single instance of each restriction is required.

• The restrictions are easy to find. They are all under a single class. Restrictions can be mixed

and matched without the need for repetition.

To hide the class containing all the Where clause restriction objects

from end users

1. Click the class or object you want to hide.

2. There are different ways to hide classes and objects:

• Select the Show or Hide Item button on the Edit menu.

• Right-click the object or class and select Hide Item(s) from the drop-down menu.

• Use Ctrl+Shift+H.

Hidden classes and objects appear in italics in the Universe Designer Universe pane.

They are not shown at all in Business Objects end-user querying tools.



@aggregate_aware Some databases contain Summary Tables. These tables are created by the Database Administrator

(DBA) and contain figures such as revenue aggregated to a high level (year, for example) rather

than to the fact/event level. The summary tables are usually populated and updated regularly

by an automated program that runs SQL against the fact or event data at transaction level.

This means that there are two methods that you can use to return aggregated data:

• Run a SELECT statement for the fact or event data

• Run a SELECT statement for the summary data Where possible, it is best to choose the latter method as the statement will process quicker.

In Universe Designer, you can use a function called @aggregate_aware in the SELECT statement

for an object, so that both methods are referenced. This function directs a query to run against

aggregate tables whenever possible. If the data in the aggregate table is not calculated at the

level of granularity required to run the query, the object will direct the query to run against

the tables containing the non-aggregated data.

A universe that has one or more objects with alternate definitions based on aggregate tables is

said to be aggregate aware. These definitions correspond to levels of aggregation. For example,

an object called Profit can be aggregated by month, by quarter, or by year.

The reliability and usefulness of aggregate awareness in a universe depends on the accuracy

of the aggregate tables. They must be refreshed at the same time as all fact tables.

When you apply the @aggregate_aware function, be aware of the available levels, and be clear

about the descending order of aggregation.

Each aggregation level SELECT statement is separated by a comma, and the entire expression

is enclosed in brackets. The final SELECT statement must be valid for all queries.

@aggregate_aware(<SELECT statement for highest agg level>,

<SELECT statement for second highest agg level>, ..

<SELECT statement for second lowest agg level>, <original SELECT statement for basic agg calculation>)

Note: Setting up aggregate awareness in a universe is a four-part process. For more information,

refer to the BusinessObjects XI 3.0: Designer’s Guide.

Activity: Using @functions Objective

• Apply @functions to objects and condition objects.

Continue to work with the Model for Rental dimension object that you created in the Day

Rental Charges subclass. This object returns all models available for rental. This is to be used

by sales staff and requires further restriction to a specific showroom.

Instructions 1. Use the @prompt function to achieve this. The parameters for the @prompt are:



• Prompt = 'Enter showroom name'

• Data type = 'A'

• LOV = 'Showroom\Showroom'

• Mono

• Constrained 2. The SELECT properties of the Model and Model for Rental objects are the same. Use the

@select in the Model for Rental object to point to the SELECT properties of the Model object.

3. Create a new condition object called Showroom Rental Model in the Showroom class. The

Where clause restrictions for this condition already exist in the Model for Rental object. Use

the @where function in the condition object to point to the where properties of the Model for

Rental object.

4. Create a new class called Where Restriction Objects.

5. Create two new objects to go into the Where Restriction Objects Class as follows:

• Rental Model containing the restriction:


• Showroom Choice containing the restriction:

SHOWROOM.SHOWROOM_NAME = @prompt

('Enter showroom name', 'A', 'Showroom\Showroom', mono, constrained)

6. Hide the Where Restriction Objects Class.

7. Edit the following object and condition object so that the WHERE clause of each contains no

SQL code, but instead uses @where functions to point to the Where clause restriction objects.

• Model for Rental object inherits the Rental Model object‟s WHERE clause.

• Showroom Rental Model condition object inherits the Showroom Choice object‟s WHERE

clause.

8. The SELECT properties of the Rental Date and Return Date objects contain RENTAL.SALE_DATE.

Use the @select in the Return Date object to point to the SELECT properties of the Rental

Date object to avoid duplication of SQL code.

9. Create a Maker Choice condition object under the Car class that, when used in a query,

produces a prompt dialog box requesting the user to enter a single manufacturer.

10. Check the integrity of the universe.

Note: The Integrity Check dialog box alerts you regarding the two hidden objects.


Note: Remember to test your solution in Web Intelligence Rich Client.



Quiz: Using @functions with objects 1. What parameter does the @select require?

2. True or False. You can use the @where function in a condition object to point to an object,

but not the other way round.

3. What function is used to create an interactive object that causes a message to appear at query

runtime, that asks the user for specific input?

a. @where

b. @prompt

c. @select

d. @aggregate_aware

4. In the @prompt two parameters are mandatory and three are optional. What parameters are

optional?



Lesson summary


• Use @functions

Using Hierarchies—Learner’s Guide 237


Lesson 11

Using Hierarchies

Lesson introduction Hierarchies allow you to organize dimension objects so that users can perform multi-dimensional

analysis using drill mode in end-user queries.


• Understand hierarchies and universes

• Work with hierarchies



Understanding hierarchies and universes Hierarchies in universes allow users to create reports that are enabled for multi-dimensional

analysis with drill mode.


• Explain how hierarchies allow users to drill down to different levels of detail using drill

mode in end-user queries.

Hierarchies A hierarchy is an ordered series of related dimension objects that are used for multi-dimensional

analysis. For example, a geographical hierarchy could group together dimension objects such

as Country, Region and City.

Multi-dimensional analysis is a technique for manipulating data so that it can be viewed from

different perspectives and at different levels of detail. In Business Objects end-user querying

tools, users can analyze data at different levels of detail using a feature known as drill mode.

The example below shows a hierarchy of the dimension objects Country, Region and City.

At the highest level, the user will see a Country. At the next level down, the Country is broken

down into more detail: the regions. At the next lower level, the regions are broken down into

more detail: the cities. A user can then analyze a measure object, such as Sales Revenue, against

any of the levels in the hierarchy.

Natural hierarchies

A natural hierarchy is one that follows a naturally occurring pattern from the most general at

the highest level to the most detailed at the lowest level. Examples of natural hierarchies can

be found in the geographical definitions of places and in the measurement of time:

• Country, Region, State, City, District, Street

• Year, Quarter, Month, Week, Day

Logical hierarchies BusinessObjects hierarchies are not restricted to natural hierarchies. You can construct a

hierarchy from any related group of dimension objects that will create a sensible analysis path.

The relationship between the dimension objects in a hierarchy normally will be one-to-many

as you descend through the levels.

Using Hierarchies--Learner·s Guide 239


For example,one Country has many Towns; one Town has many Showrooms;one Showroom

has many Franchises.

, Showroom Country )

,Showroom Town )

,Showroom )

, Franchises -



Working with hierarchies After completing this unit, you will be able to:

• View default hierarchies in a universe

• Set the scope of analysis in a Web Intelligence Rich Client document using a default hierarchy

• Create a custom hierarchy

• Create time hierarchies

Default hierarchies A default hierarchy contains all the dimension objects in a class in the order they are presented

in that class. It is based on the order of the objects within the class.

As the name suggests, a default hierarchy is automatically inferred by Business Objects end-user

querying tools whenever you have at least one dimension object in a class.

It is therefore important to organize dimension objects hierarchically in a class.

In this example, you can see that the dimension objects in each class follow an order from the

most general to the most specific.

Using this method of organizing your dimension objects in their classes is the key to setting

up usable default hierarchies.



To view the Default Hierarchies 1. There are two methods to view the default hierarchies:

• Select Tools ➤ Hierarchies from the menu bar.

• Click the Hierarchies toolbar button.

This opens the Hierarchies Editor dialog box:

You cannot add or remove objects from classes in the Hierarchies Editor.

You can use the Hierarchies Editor to create Custom Hierarchies.

2. Click the + box next to any class if you want to see the dimension objects organized in these

hierarchies.

3. Click Cancel to close the Hierarchies Editor dialog box.

To test a default hierarchy As with other components of a universe, hierarchies can be tested in Web Intelligence Rich

Client, to check that they function as expected.

1. In Web Intelligence Rich Client, create a new document. Select the relevant universe.

2. In the Query Panel, select an object that is the highest level of one of the hierarchies, and

move it into the Result Objects pane.

3. Select a suitable measure object, and double-click it to add it to the Result Objects pane.

4. Click the Show/Hide Scope of Analysis pane button on the Web Intelligence Rich Client

Query Panel toolbar.



This opens the Scope of Analysis pane.

The Scope of Analysis pane allows users to set up the query for drill analysis. All the

dimensions selected for the query are highlighted here, within their default hierarchies. In

order to allow users to drill down the hierarchy from one level to another, without having

to modify the query, you can set the scope of analysis before the query is actually executed.

Note: You can manually drag the objects you want to drill down to in this pane. In this

case, the Custom value appears in the Scope of Analysis level drop-down list.

5. To define default levels of scope of analysis, select the level drop-down list in the Scope of

Analysis, and click the arrow to select the scope of analysis levels.

The levels you define in the scope of analysis will determine how many objects from the

hierarchy will be included in the query, and therefore how many levels of detailed data will

be returned to the Web Intelligence Rich Client document.

6. Select the required level from the drop-down list.

The Scope of Analysis pane will contain further dimensions, indicating the level down

option you have just selected.

This means that they will be included in the query, and the measure relevant to these two

objects will be calculated and stored in the document‟s microcube.

7. Click Run Query to execute the query.

Values returned by the two dimension objects will not immediately be projected in the table

that is displayed, but the objects can be seen listed in the Data tab of the Report Manager

on the side.

As soon as a user decides to switch to drill mode, the data will be available for drill analysis. 8. Click the Drill button in the Reporting toolbar to display the report in drill mode.



Note: The report tab at the bottom of the Rich Client main window now shows the name

Report 1 with a drill mode icon.

9. Move the mouse pointer over a value in the dimension object column.

A flag appears indicating the next level of data available from the hierarchy.

10. Double-click to drill down. The data in the measure column is aggregated to reflect next

level drill-down figures.

11. Drill down and up as you wish to explore the data available in the document‟s microcube.

Custom hierarchies A custom hierarchy combines objects from default hierarchies to build a custom analysis path.



Default hierarchies are based on the order of the dimension objects in their classes. These default

hierarchies may not provide the drill paths that users need to analyze their data. They may

need to follow drill paths that contain dimension objects from more than one class.

For example, if users of the Motors universe wanted to look at Sales Revenue from the point

of view of Client/Area and Financial Period, they would not be able to do this using the default

hierarchies.

As universe designer, you can build a permanent custom hierarchy as part of the universe. As

a result, the hierarchy is available across documents to all users.

In the analysis phase of the universe development process, the designer identifies those custom

hierarchies that are to be used regularly and creates them in Universe Designer as permanent

custom hierarchies.

To create a custom hierarchy 1. There are two methods to create a custom hierarchy:



This opens the Hierarchies Editor dialog box: 2. Click New.

A new folder appears in the Custom Hierarchies pane. 3. Type a name for the custom hierarchy as the folder name, and press Enter.

4. In the left panel of the Hierarchies Editor dialog box, click the + box of the default hierarchies

that contain the dimension objects you want to include in the custom hierarchy.

The default hierarchy dimension objects appear. 5. There are several methods to add the dimension objects to the custom hierarchy:

• Select the object that you want to appear in the custom hierarchy, and click Add.

• Select multiple objects by holding the Ctrl key down, and click Add.

• Drag and drop the required objects to the new custom hierarchy folder.

The selected objects appear in the custom hierarchy.

Note: The dimension objects may not be in the order you require. You can move the objects

up and down the list by clicking them and then clicking the Move Up or Move Down

buttons. Alternately, you can use the drag-and-drop technique.

6. Click OK to save the changes to the hierarchies and close the Hierarchies Editor dialog box.




The effect of custom hierarchies on default hierarchies In Web Intelligence Rich Client, if you switch the Query Panel's Data tab to Display by

hierarchies mode, before you create any Custom Hierarchies in Universe Designer, you will

see that the list of hierarchies is shown in the same order as the objects in the Display by objects

mode: both show a full list of default hierarchies.

However, when you create a Custom Hierarchy, the Display by hierarchies mode lists only

the custom hierarchies while the Display by objects mode shows all objects made available to

the user.

At first, this appears to be a problem. However, the effect of creating a custom hierarchy is

actually very useful because it provides a mechanism for selectively producing hierarchies for

end users.

Because a default hierarchy is always created for any class where a dimension object exists, it

may be that there are some default hierarchies that you do not want users to use as drill paths.

This mechanism can be used to exclude such default hierarchies.

Once you decide to create custom hierarchies, you must copy any of the defaults that you want

to keep over to the right-hand side list box. Even if you do not want to create new ones, to

exclude the default hierarchies that you do not want users to use as drill paths, you must copy

the useful ones over.



In order to make any change at all in the hierarchies, you either start over by creating new

custom hierarchies or you copy only the useful default hierarchies into the Custom Hierarchies

list box.

To selectively make default hierarchies available to users This topic discusses how to add selected default hierarchies to the list of custom hierarchies in

Universe Designer.

1. There are two methods to create a custom hierarchy:



This opens the Hierarchies Editor dialog box. 2. Drag and drop only the default hierarchy folders you want the users to use as drill paths

from the left panel of the Hierarchies Editor dialog box to the right panel.

Note: When more than one hierarchy starts with the same dimension object path but diverges

at a lower level of the hierarchy, the default path in the user module will be the one that is

higher in the list (if dimensions from both hierarchies are included in the query). You can

alter this default priority by changing the order of the hierarchies in the Custom Hierarchies

pane. You can do this using the Move Up and Move Down buttons, or using the

drag-and-drop technique.

Note: When you add default hierarchies to the Custom Hierarchies list, it is good practice

to position the true custom hierarchy, if any, at the bottom of the list.

3. Click OK to save the changes to the hierarchies and close the Hierarchies Editor dialog box.




Time hierarchies One of the most common requirements for data analysis is to provide facilities for analysis

against different time periods.

Time is a special case because all the information for the dimension objects that make up the

hierarchy can come from a single column in a database. In most other cases, each dimension

object infers a separate database column.

This is achieved by using SQL date scalar functions to extract the day, month, year, and possibly

quarter from a single database column of a date type.

When you create a Time Hierarchy, you are still creating a Default Hierarchy, in which the

levels depend on the order of the Dimension objects. You create the standard time structure

by ordering the objects Year, Quarter, Month, and Week. The only difference with Time

Hierarchies is the way in which you create the objects.

Creating time hierarchies There are three methods of creating a time hierarchy. Each method has advantages and

disadvantages for both the designer and the user. The three methods are:

• Automatic time hierarchies

• Using database functions

• Table-based time hierarchies

To create an automatic time hierarchy

Using this method, Universe Designer automatically creates the dimension object definitions

needed for a time hierarchy from a single Date Seed object.

Automatic time hierarchies can only be applied to objects with Date type.

1. Double-click a date object to open the Edit Properties dialog box.

Note that the Type field is set to Date. 2. Click the Properties tab. With the field type set to Date, the Automatic Time Hierarchy

button is shown in the Qualification pane.



3. Click the Automatic Time Hierarchy button to open the Automatic Time Hierarchy dialog

box.

4. Select the check boxes for the time-related dimension objects you want to create and edit

the names of the dimension objects, if required.

5. Click OK to close the Automatic Time Hierarchy dialog box.

6. If necessary, alter other object properties as required.

7. Click OK to close the Edit Properties dialog box.

In the Universe pane, the original date object has a plus next to it, indicating that other

objects are attached to it. These are the automatically created time dimension objects.



8. Click the + box to view and check the objects attached to the date object.

Note: You can see that the arrangement of the objects is not as you might expect. The original

date object is at the top of the hierarchy, and the other time objects appear to be subsidiary

objects to it. From this, it is apparent that there are two further disadvantages to this method

of creating time dimension objects. First, when a user sees a + box against an object, they

will think that detail objects are attached to it. Second, the objects are not ordered

hierarchically in the class, and, as a consequence, this might lead to confusion as to which

is the highest-level object in the class.

9. Double-click one of the automatically created time dimension objects (year, quarter, or

month) to view the Edit Properties dialog box for the object.

Note: The object properties cannot be edited. This is another disadvantage. However, you

can also see one of the key advantages of using this method to create time dimension objects:

the SQL inferred includes the scalar function used to extract the correct element of the date.

10. Click OK to close the Edit Properties dialog box.

11. Click the Hierarchies toolbar button to open the Hierarchies Editor dialog box.



Notice that in the Default Hierarchies list, there are two new default hierarchy classes, an

empty one bearing the name of the original class, and another bearing the name of the class

appended with the name of the original date object.

12. Click the + box next to the class/object-named default hierarchy.

You can see that the time hierarchy objects are correctly ordered despite the order of the

dimension objects in the class.

13. Close the Hierarchies Editor dialog box.


Testing automatic time hierarchies Automatic time hierarchies are tested in the same way as any other hierarchy. However, there

is one thing to note about such a test.

When you drill down to the bottom of the time hierarchy, the Quarters and the Months are

identified simply as numbers, 1 to 4 for the Quarters and 1 to 12 for the Months.

This can be confusing or unsatisfactory to end users. A better idea is to precede the numbers

with a character string such as Quarter or Month. However, as you have already seen, it is

impossible to edit a time dimension object that is created using the automated method.

Advantages and disadvantages of automatic time hierarchies

This section lists the advantages and disadvantages for using automatic time hierarchies.

Advantages

• It is a fairly quick and easy way to set up a time hierarchy.

• Automatically creates the SQL SELECT statement using the appropriate scalar functions for

the RDBMS of the target database.

Disadvantages • Does not give the designer any control over the layout of the dimension objects in the

Universe pane.

• Does not give the designer any control over the format of the data in the query report.



• The layout of the dimension objects in the universe can be confusing to users, who normally

expect to see detail objects under dimension objects.

• The format of the report can be confusing to users.

• An LOV can only be applied to the date seed object, not to individual time dimension objects. All the negative points listed above can be avoided if another method of creating time dimension

objects is used.

Time hierarchies based on database functions You can use the scalar date functions to create time dimension objects manually.

Note: However, the set of scalar functions used to extract elements of a database varies with each

RDBMS.

To create a time hierarchy using database functions 1. Create a new class or subclass with an appropriate name.

Repeat the remainder of this procedure to create each time object required within the class

that is based on the date scalar functions.

2. Drag the database column from the Structure pane table that contains the date required

and drop it on the newly created class.

3. Double-click the object to open the Edit Properties dialog box.

4. Edit the properties of the object so that it will infer an element of the date as required.

• Change the object name to reflect the scalar function used.

• Change the Type if required, depending on the scalar function used.

• Change the SELECT statement to the relevant scalar function, string conversion, and

required concatenated string value, depending on the RDBMS used.

• Clear the Associate list of values, if not required. 5. Click OK to close the Edit Properties dialog box.

6. Repeat steps 2 to 5 for each of the other time objects required within the class based on scalar

functions.

Tip: As you are creating a very similar time object to the previous one, it can be more

efficient to edit a copy of the previous object, rather than creating a new one as suggested

in step 2.

7. The Universe pane now contains a class or subclass as in the following example:



A default time hierarchy will now be inferred from the class.

Note: A time hierarchy created using this method is tested the same way as any other hierarchy.

Advantages and disadvantages of database function time

hierarchies

This section lists the advantages and disadvantages for database function time hierarchies.

Advantages • The layout of the dimension object within the class is as a user would expect.

• Each of the objects can be edited individually.

• A separate LOV can be associated with each time dimension object as required.

• The name of the hierarchy and the order of the objects mirror the class exactly.

Disadvantages • It takes longer to create the objects of the time hierarchy than when using the Automatic

Time Hierarchy method.

• The person designing the universe needs to know the relevant scalar functions and how to

use them.

Tip: If you do not know the relevant scalar functions, you could initially create the time objects

within a class using the Automatic Time Hierarchy method. Then you could note the scalar

functions automatically inferred, remove the automatically created objects, and recreate them

using the database function method.

Table-based time hierarchies The Automatic Time Hierarchy and Database Functions methods of creating a time hierarchy

are appropriate when you want to create calendar-based time dimension objects. However,

they are inappropriate when you want to create time dimension objects based on different time

periods.



Another way of creating time dimension objects is to add a time-range table to the database

with columns and data as in the following example. This table can then be added to the structure

and its columns used to create time dimension objects. This is a good way of coping with

financial periods that do not coincide with the calendar year.

To create a table-based time hierarchy 1. Add the time period table to the universe structure.

2. Insert a theta join between the start and end range columns of the time period table and an

appropriate date column of another table.

An example of this is shown below:

3. Create a new class with an appropriate name.

4. Create the time objects required. In each instance, you will not need to use scalar functions.

The SELECT statement of each object needs only to infer a database column name. Hence, it

would be more efficient to use the automated method of creating objects (drag and drop).

When the objects have been created, the class appears as in the example below:



A default time hierarchy will now be inferred from the class.


Note: A time hierarchy created using this method is tested in the same way as any other hierarchy.

Advantages and disadvantages of table-based time hierarchies

This section lists the advantages and disadvantages of table-based time hierarchies .

Advantages

• It is a good method of creating time dimension objects for time periods other than calendar

periods.

• The layout of the dimensions within the class is as a user would expect.

• Each of the objects can be edited individually.

• A separate LOV can be associated with each time dimension object, as required.

• The name of the hierarchy and the order of objects mirror the class exactly.

Disadvantages • The additional join reduces the efficiency of an inferred SQL statement.

Activity: Using hierarchies

Objective

• Infer default hierarchies and create custom hierarchies for the Motors universe.

Note: Switch back to default hierarchies if you have followed along during this lesson.

Instructions

1. To view all hierarchies, click the hierarchy button. Remove all custom hierarchies in the

Custom section.

2. Check that the hierarchical order of the dimension objects in the Client class is based on

geography.

The geographic hierarchy is: Country -> Region -> Area -> Town.

3. Save the universe, and then test the default hierarchy in Web Intelligence Rich Client.

4. Create a Sale Year, Sale Quarter, and Sale Month dimension object using the Automatic

Time Hierarchy method.



5. Save the universe again, and then test the resulting hierarchy in Web Intelligence Rich Client.

When you run the query, view the SQL and note the scalar function used. 6. Create a Rental Year, Rental Quarter, and Rental Month dimension object manually in the

Rental Dates subclass.

Ensure that the quarter and month dimension object values are formatted to show a full

month value or are preceded by a character string such as Q and Calendar Year respectively.

7. Check that the order of the dimension objects in the Financial Period class is based on time.

8. Save the universe again, and then test the resulting hierarchies in Web Intelligence Rich

Client.

9. Prestige Motors wants to analyze clients geographically (by Country, Region, and Town)

but then further analyze the breakdown of client expenditure by financial year.

Create a custom hierarchy to allow users to do this by including the Country, Region, Town

and Financial Year objects in the hierarchy.

10. Make the following default hierarchies available to the user:

• Car

• Day Rental Charges

• Showroom

• Financial Period

• Rental Dates

• Sale Dates

11. Save the universe again, and then test the resulting hierarchy in Web Intelligence Rich Client.

12. Sales people want to drill down to a model using a specific drill path. In the bottom of your

custom hierarchy list, create a hierarchy to allow this drill path using the following objects:

• Showroom Country

• Showroom Name

• Maker

• Model 13. Save the universe again, and then test the resulting hierarchy in Web Intelligence Rich Client.



Quiz: Using hierarchies 1. A hierarchy is the hierarchy based on the order of the objects within the

class.

○ a) Default

○ b) Custom 2. What are two advantages of Automatic Time Hierarchies?

Using Hierarchies-Learner's Guide 257


Lesson summary


• Understand hierarchies and universes

• W ark with hierarchies

Derived Tables and Indexes—Learner’s Guide 259


Lesson 12

Derived Tables and Indexes

Lesson introduction A derived table is a dynamic, virtual table that you create within the universe structure. It

allows you to transfer more of the processing load from the report server to the database and

improve query execution performance.

Index awareness is the ability to take advantage of the database indexes on key columns to

speed data retrieval. The objects that you create in the universe are based on database columns

that are meaningful to an end user.


• Use derived tables

• Apply index awareness



Using derived tables This unit explains what derived tables are and how you create them as dynamic, virtual tables

in the universe.


• Understand the advantage of adding derived tables to your universe structure

• Insert a derived table in the universe

What is a derived table? A derived table is a dynamic, virtual table that you create within the universe structure. It

consists of a set of SQL statements that you create in Universe Designer, and that you can then

use as a logical table to create objects.

In the derived table‟s SQL set, you can put a SELECT statement in place of a table name in the

FROM clause. The SQL set can also contain embedded prompts, and you can create joins between

the virtual derived table and the physical tables, just as you can with other tables.

Derived tables are similar to views in the database, but as they are defined in the universe, they

give universe designers more flexibility. You can see a derived table as a query that can be

referenced as a table. The table definition SQL is inserted into an end-user query at run time.

Note: As it is a query and not a physical table, it is important to understand that the same

performance issues that can affect queries can also affect derived tables.

Derived tables can be used to merge data together from different tables, when universe designers

are unable to conform the underlying data source, and want to normalize or denormalize the

universe schema.

Adding derived tables Derived tables appear in your Universe Designer schema in exactly the same way as normal

database tables, but the workflow for creating them is different.

To create a derived table

1. Select Insert ➤ Derived Tables.

The Derived Tables dialog box displays. 2. Type the table name in the Table Name dialog box.

3. Build the table SQL in the box beneath the Table Name box.

You can type the SQL directly or use the Tables and Columns, Operators and Functions

boxes to build it.



Note: When using an aggregation function, or any other SQL function in the SQL syntax,

it is important to alias the column that contains the calculation. Universe Designer uses

these aliases as the column names in the derived table.

4. Click Check Syntax to parse and validate your SQL.

5. Click OK.

The derived table appears in the schema next to the physical database tables.

6. Join the table to a table in the existing schema.

If contexts have been applied to the schema, make sure the newly inserted join is included

in at least one context.

7. Build objects based on the derived table columns in exactly the same way you do with

regular tables.


To edit a derived table 1. Right-click the table in the Universe Designer schema and select Edit Derived Table from

the shortcut menu.

2. Edit the derived table, and then click OK.


Derived tables as lookup for multiple contexts Derived tables can be useful to combine data from two separate fact tables. If fact tables are

spread across two separate contexts, combining measures from each of these tables results in

separate SQL statements.

In the Motors schema there is have a context for Sales and a context for Rentals. End users may

wish to see Clients with both Rental Total and Sales Total data.

You can combine the data in a derived table and by basing the Sales and Rental total objects

on the new derived table. Users avoid having to select measures from multiple contexts.



Nested derived tables

The XI 3.0 release of Universe Designer allows designers to build nested derived tables.

Sometimes the definition of derived tables can become very complex, and complex derived

tables may generate ineffective SQL.

The nested derived table feature simply means that you can include an existing derived table

in the definition of another new derived table. This makes it easier for designers to define the

SQL. The query execution is more efficient because the SQL statements are combined and sent

to the database as a single statement.

With this feature, designers are able to create a single derived table and use it multiple times

in other tables as a nested derived table.

The behavior of a nested derived table is exactly the same as a simple derived table. Technically,

there is no limit to the number of derived tables that can be nested, but only 20 levels are

supported.

The nested derived table feature is particularly useful if you want to use a very complex SQL

statement more than once in a universe. It allows you to reuse existing definitions. It can also

be useful if you want to improve the performance of an existing derived table, for example by

using a filter.

Creating nested derived tables In addition to defining derived tables, the Derived Table Editor in Designer allows you define

nested derived tables from existing derived tables.

• The new function @DerivedTable(Derived_table_name) is added to the functions catalog

to ease building the SQL Defintion and is available in the Derived Table Editor.

• A new function displays the existing derived tables in a new list in order to select derived

tables you want to use in the current edited definition. This new list is only displayed when

Derived tables exist in the universe.

The following Derived Table Editor functions work for both derived tables and nested derived

tables:

• The check integrity function detects impacts on derived tables when a referenced derived

table is removed.

• Check for circular references

• Check for @DerivedTable() within object definitions (SELECT and WHERE ), which are not

allowed.

To create a nested derived table You create a nested derived table in the same way that you create a derived table. You can add

and rename a nested derived table in the same way you add and rename a derived table.

To create a nested derived table:

1. Open your universe in Universe Designer.



2. Right-click in the universe Structure pane and select Derived Table in the context menu.

The Derived Tables editor opens and the center pane at the bottom of the Derived Tables

editor lists the available derived tables.

3. Type the name of your nested derived table.

4. Add the required SQL syntax for the nested derived table using one of the following methods:

• Type the SQL expression. You can type the entire text or use the editor assistants.

• Double-click on the objects (tables, derived tables, columns, functions). When clickin on

an existing deriverd table name the @DerivedTable function is inserted automatically.

• Use the @DerivedTable function with the syntax: @DerivedTable(Derived_table_name)

to choose a derived table.

5. Click Check Syntax to check the syntax of your derived table and correct any potential

errors, then validate your nested derived table.

The nested derived table is added to the universe.

6. Click OK to validate your nested derived table.

The nested derived table appears in the universe Structure pane. Derived tables and nested

derived tables are lighter in color than tables that represent actual database tables.

Note: To display the table values, right-click the different tables.

You have created your nested derived table in your universe.



Activity: Adding derived tables Objectives

• Create a derived table that shows the number of transactions per customer.

• Create a nested derived table.

Instructions 1. Using Motors, insert a derived table to show the number of transactions per customer.

2. Name the newly derived table Best_Cust.

3. Create the SQL statement so that it looks like this:

SELECT CLIENT.CLIENT_ID, COUNT(SALE.SALE_ID) AS Number_of_transactions

FROM CLIENT, SALE WHERE CLIENT.CLIENT_ID=SALE.CLIENT_ID GROUP BY CLIENT.CLIENT_ID

4. Use Check Syntax to verify your SQL statement syntax.

5. Insert a join between the Best_Cust and Client tables.

6. Add the new join to the Sales context.

The join between the Best_Cust and Client tables is from the Client_ID primary key in the

Client table to the Client_ID foreign key in the Best_Cust table.

The table schema looks like this.

7. Add the Number of Transactions object to the Client class. Define the object as a measure

object.


9. In Web Intelligence Rich Client, build a report that shows the number of transactions per

customer and the number of transactions per country.

10. In Universe Designer build a nested derived table, called Nested_Derived_Table, using the

following syntax:

SELECT Best_Cust.CLIENT_ID,CLIENT.CLIENT_LASTNAME,

sum(Best_Cust.Number_of_transactions)as Total_Transactions

FROM @DerivedTable(Best_Cust),CLIENT

WHERE Best_Cust.CLIENT_ID=CLIENT.CLIENT_ID

GROUP BY Best_Cust.CLIENT_ID,CLIENT.CLIENT_LASTNAME



11. Join the Nested_Derived_Table to the Best_Cust table.

Tip: All joins in the universe need to be part of at least one context.

12. Add the Total_Transactions object to the Client class. Define the object as a measure object.


14. In Web Intelligence Rich Client, build a report that shows the total transactions and sales

revenue, per customer and per country.



Applying index awareness This unit describes how to set up a universe in Universe Designer to take advantage of primary

and foreign keys that may already exist in the data source.


• Understand what index awareness is

• Set up primary key index awareness

• Set up foreign key index awareness

What is index awareness? Index awareness is the ability to take advantage of the indexes on key columns to speed data

retrieval.

The objects that you create in the universe are based on database columns that are meaningful

to an end user. For example, a Customer object retrieves the field that contains the customer

name. In this situation the customer table typically has a primary key (for example, an integer)

that is not meaningful to the end user, but which is very important for database performance.

When you set up index awareness in Universe Designer, you tell Universe Designer which

database columns are primary and foreign keys. This can have a dramatic effect on query

performance in the following ways:

• Universe Designer can take advantage of the indexes on key columns to speed data retrieval.

• Universe Designer can generate SQL that filters in the most efficient way. This is particularly

important in a star schema database. If you build a query that involves filtering on a value

in a dimension table, Universe Designer can apply the filter directly on the fact table by

using the dimension table foreign key. This eliminates unnecessary and costly joins to

dimension tables.

Universe Designer does not ignore duplicates with index awareness. If two customers have

the same name, Universe Designer retrieves only one unless it is aware that each customer has

a separate primary key.

Setting up index awareness Report designers in your organization want to build a report using the Motors universe that

returns the Highest Priced Value retail price by maker, manufactured in the United Kingdom

or the United States.

To build this report in Web Intelligence Rich Client, you would drag the Maker and Highest

Priced Value objects into the Result Objects pane in the Report Panel. Then, drag the Maker

Country object into the Query Filters pane and restrict the countries to the United Kingdom

and the United States.

Without index awareness, Universe Designer generates the following SQL:

SELECT

MAKER.MAKER_NAME,

max(MODEL.MODEL_PRICE)



FROM

MAKER,

MODEL,

COUNTRY COUNTRY_MAKER

WHERE (MODEL.MAKER_ID=MAKER.MAKER_ID) AND (MAKER.COUNTRY_ID=COUNTRY_MAKER.COUNTRY_ID) AND COUNTRY_MAKER.COUNTRY_NAME In

( 'United Kingdom','USA' ) GROUP BY MAKER.MAKER_NAME

In this case, Universe Designer has created a join to the Maker Country table in order to restrict

the countries retrieved.

With index awareness, you can tell Universe Designer that Country_ID is the primary key of

the Country_Maker table and that it also appears in the Maker table as a foreign key. Using

this information, Universe Designer can restrict the countries without joining to the

Country_Maker table.

In this case, Universe Designer is able to generate SQL that restricts the countries simply by

filtering the values of the Country_ID foreign key.

After setting up Index Awareness for Maker Country, Universe Designer generates the following

SQL, where “44” is the United Kingdom Country_ID value and “1” is the USA Country_ID

value:

SELECT

MAKER.MAKER_NAME,


FROM

MAKER,

MODEL

WHERE (MODEL.MAKER_ID=MAKER.MAKER_ID)

AND MAKER.COUNTRY_ID In ( 44,1 )

GROUP BY

MAKER.MAKER_NAME

To set up primary key index awareness 1. There are two ways to set up primary key index awareness:

• Right-click the object on which you want to set up index awareness and select Object

Properties from the shortcut menu.

• Select the object and click Object Properties on the Edit menu.

The Edit Properties Of dialog box displays.

2. Click the Keys tab.



3. Click Insert.

A key line is inserted in the list of keys box. 4. To define key awareness for the primary key:

• Click the drop-down arrow next to Primary Key and select Primary in the Key Type list.

• Click within the line under Select field, and then click the ... button that appears, to open

the SQL editing dialog box.

• The Edit Select Statement dialog box appears.

• In the Edit Select Statement dialog box, use the SQL Editor to build the primary key

SQL Select clause or type it directly. 5. Select Enable.

6. Click OK.

7. Repeat steps 3 and 4 for all columns that make up the primary key.

What happens behind the scenes? By applying index awareness for the Maker Country, by identifying the primary key to use,

Business Objects is prompted to add an alternative piece of SQL in the WHERE clause whenever

a query uses Maker Country as a condition.



Instead of using the County_Name field from Country_Maker table, it will now use Country_Id

field from the Country_Maker table. This is determined from the key entries made in the object

properties.

But how did Business Objects convert the Maker Country names selected in the LOV into the

primary key values necessary for the SQL?

The default SQL query that is generated to retrieve the Maker Country LOV is:

SELECT DISTINCT

COUNTRY_MAKER.COUNTRY_NAME

FROM

MAKER,

COUNTRY COUNTRY_MAKER WHERE (MAKER.COUNTRY_ID=COUNTRY_MAKER.COUNTRY_ID)

Note: The WHERE clause shown here is a result from using the Tables button, and adding the Maker

table, to make sure that Maker Country object only returns countries in which car manufacturers

exist.

In order to convert the Maker Country names to primary keys, the primary key that was defined

in the Keys tab is added to the query:

SELECT DISTINCT

COUNTRY_MAKER.COUNTRY_NAME

COUNTRY_MAKER.COUNTRY_ID

FROM

MAKER,

COUNTRY COUNTRY_MAKER WHERE (MAKER.COUNTRY_ID=COUNTRY_MAKER.COUNTRY_ID)

This way Business Objects matches the country names from the Country_Maker table to the

primary key values.

Note: This SQL is visible by either editing the LOV for the Maker Country object and/or tracing

SQL that passes through the middleware to the database.

With index awareness defined, if you select Maker Country names from the LOV dialog you

indirectly select the primary key values as well. The primary key values acts like a hidden

column in the LOV dialog box. The operand „Value(s) from list‟ dialog box in the BusinessObjects

end-user querying tools returns the primary key values that match the visible values in the

LOV dialog.

Index Awareness allows universe designers to automatically redirect a WHERE clause condition

to another column that is known to provide better performance at query time. The index

awareness option can be used to determine which column to choose as an alternative based

on database schema knowledge and the RDBMS optimizer.

The LOV values that end users select actually tell Business Objects what primary key values

to substitute in final query SQL. The Keys tab tells Business Objects which SQL syntax to

substitute in the final query SQL.

To view the altered LOV 1. Double-click the indexed object to access the Object Properties.




3. Click Edit.

The Designer Query Panel opens displaying the indexed object in the Result Objects pane. 4. Click View SQL.

The SQL Viewer Opens.

It now displays both the indexed object value and its index key as generated columns in the

LOV.

Avoiding joins in tables

Another use of index awareness is to reduce the number of tables or joins involved in a query.

Reducing the number of joins in a query can help improve query performance.

The SQL from the last example improved performance by restricting on the primary key

(indexed) of the Country_Maker table.

SELECT

MAKER.MAKER_NAME,


FROM

MAKER,

MODEL,

COUNTRY COUNTRY_MAKER

WHERE (MODEL.MAKER_ID=MAKER.MAKER_ID) AND (MAKER.COUNTRY_ID=COUNTRY_MAKER.COUNTRY_ID) AND COUNTRY_MAKER.COUNTRY_ID In ( 44,1 ) GROUP BY MAKER.MAKER_NAME

This query has the Maker and Country_Maker tables in it which both can provide the

Country_ID column.

The Country_Maker table is only needed to satisfy the WHERE clause and is not needed in the

SELECT or GROUP BY clauses.

Using Index Awareness it is possible to remove the Country_Maker table from the query

completely, by telling BusinessObjects to use the Maker table to retrieve Country_ID data from.

By defining the foreign key in the Maker Country object, the same query returns the following

SQL:

SELECT

MAKER.MAKER_NAME,


FROM

MAKER,

MODEL

WHERE (MODEL.MAKER_ID=MAKER.MAKER_ID)

AND MAKER.COUNTRY_ID In ( 44,1 )

GROUP BY

MAKER.MAKER_NAME

The Country_Maker table is no longer referenced in the SQL. This table no longer shows up

in the FROM clause, nor in the WHERE clause as a join to the Maker table or as a table used to

retrieve the condition values from.



Note: The LOV SQL is only affected by the primary key entry and always returns the primary

key entries „behind the scenes‟. Therefore all columns you provide in foreign key entries must

have the same type of values and column type as the column referenced by the primary key

entry.

To set up foreign key index awareness 1. Right-click the object on which you are setting up index awareness and select Object

Properties from the shortcut menu.

The Edit Properties dialog box displays. 2. Click the Keys tab.

3. Click Insert.

A key line is inserted in the list of keys box. 4. To define key awareness for the foreign key:

• Select Foreign in the Key Type list.

• Click in the Select field and then click the ... button.

• In the Edit Select Statement dialog box, use the SQL Editor to build the foreign key SQL

SELECT or type it directly. 5. Repeat steps 3 and 4 for all columns that make up the primary key.

6. Select Enable.

7. Repeat the steps for all columns in the foreign key and then click OK.

Multiple foreign key entries The Keys tab allows more than one foreign key entry. This allows you to deal with repeated

values in multiple tables (denormalized data).

Database designers may denormalize primary key values beyond what is necessary to satisfy

constraints or to assist in performance and simplification of SQL generation.

It is expected to see an entity repeated twice: initially in the entity‟s own table as its primary

key and then in a table that refers to this primary key through its foreign key.

Denormalization implies that the database designer has gone beyond this duplication and has

more than two instances of the value in a schema.

In the Motors schema you can find such a scenario with the following tables:

• Client

• Region

• Country_Region

All three tables contain a Country_ID column.



If you set up the keys for the Client Country object, you can give Business Objects three choices

from which it can retrieve these values for the purposes of restricting data in the WHERE clause.

This can aid query performance.

When running the Web Intelligence Rich Client query shown above, the SQL generated is as

follows:

SELECT

CLIENT.CLIENT_LASTNAME + ', ' + CLIENT.CLIENT_FIRSTNAME, REGION.REGION_NAME FROM CLIENT, REGION WHERE (REGION.COUNTRY_ID=CLIENT.COUNTRY_ID) AND REGION.COUNTRY_ID In (1,44)

The Region table is used to restrict on Country_Region (Country_ID) as it is one of the foreign

key entries and the Country_Region table is not used anywhere else in the query and is

subsequently dropped from the SQL.

Why does Business Objects use the Region table and not the Client table? Both tables exist in

the FROM clause, however the Region table is used as the Country_ID key replacement.

The reason for this is the order in which the foreign keys have been defined.The Country_ID

key from the Region table was the last one defined in the list and this is the one that will be

used in the SQL generation.

Rearranging the keys by placing the Country_ID key from the Client table last will result in

the following SQL instead:

SELECT

CLIENT.CLIENT_LASTNAME + ', ' + CLIENT.CLIENT_FIRSTNAME, REGION.REGION_NAME FROM CLIENT, REGION WHERE



(REGION.COUNTRY_ID=CLIENT.COUNTRY_ID)

AND

CLIENT.COUNTRY_ID In (1,44)

Note: If a shortcut join has been defined between the Country_Region and Client table, this

shortcut key takes precedence as the foreign key, even if the last foreign key defined is the

Region key.

SQL Editor dialog box The SQL editor available to the management of Index Aware is the same SQL editor dialog

available to predefined conditions, objects SELECT and objects WHERE clauses.

If your target database allows them, you can add SQL comments to the Primary Key and Foreign

Key entries so that they are identifiable in the final query SQL for example: /* Index Awareness

Foreign Key */

To add a string value in the SQL Editor dialog box 1. Edit the object that has been made index aware, and click the Keys tab.

2. Double-click on the primary key select statement and append an appropriate string value.

String values need to be appended by "/*" and closed with "*/" 3. Double-click on the foreign key select statement and append an appropriate string value.

String values need to be appended by "/*" and closed with "*/" 4. Click OK to apply your changes.

Using an index awareness WHERE clause In this section you will look at using a WHERE clause for the primary and foreign key. Using a

WHERE clause condition in either the primary or foreign key index will act as a data restriction.

This may be useful if there is a large amount of data returned for a particular object.

To add an index awareness WHERE clause 1. Double-click the object on which you are setting up index awareness and select the Keys

tab.

2. Double-click on the primary key Where clause field.

3. Type in the required Where clause syntax.

4. Double-click on the foreign key Where clause field.

5. Type in the required Where clause syntax.

6. Click OK to apply the changes.



Activity: Setting up index awareness Objective

• Apply index awareness to improve the performance of SQL generation in Web Intelligence

Rich Client.

Instructions 1. Using the Client Country object in Motors, enter the following under Keys:

Primary key COUNTRY_REGION.COUNTRY_ID

WHERE COUNTRY_REGION.COUNTRY_ID=CLIENT.COUNTRY_ID

Foreign key CLIENT.COUNTRY_ID


3. Create a query in Web Intelligence Rich Client with Client Country and Client Name.

4. Apply a query filter, and use the Value(s) from list option to restrict the data to a single

country, such as the United States.

5. View the SQL.

Notice that the WHERE clause no longer uses the

COUNTRY_REGION.COUNTRY_NAME=USA statement (or whichever country you

specified). It uses CLIENT.COUNTRY_ID =1.



Quiz: Derived tables and indexes 1. What part of the SQL expression does Designer use to create column names in the derived

table?

2. When you insert a derived table and insert joins, what happens if you do not add the new

join to the appropriate context?

3. How do you apply index awareness on a universe object? 4. How can index awareness improve query performance?



Lesson summary


o Use derived tables

o Apply index awareness

Relational and Dimensional Modeling—Learner’s Guide 283


Appendix A

Relational and Dimensional Modeling

Understanding the metadata Before developing a universe you must familiarize yourself with the underlying data. Which

type of database schema is going to be used for the universe? Will this be a Data Warehouse

model, an Online Transactional Processing system (OLTP), or a Data Mart? How can you best

implement the metadata into a universe schema to meet the end user requirements?



Data warehouses A data warehouse is an enterprise wide centralized storage facility for different types of data.

Data stored in a data warehouse is characteristically subject oriented, time sensitive, and should

be organized in a way that allows data analysis. For example, a data warehouse can contain

customer information and sales details per customer, over the past five years. These customer

details and sales records are often derived from several production systems in the enterprise.

Performing query and trend analysis on this dispersed data can prove to be a difficult task.

This is where data warehousing comes into play. Data warehousing is the process of collecting,

aggregating, storing, and maintaining information so that it may lead to accurate business

decisions. Some characteristics and features of data warehousing are as follows:

• Provides a consolidated storage of information from across the enterprise.

• Warehoused data is organized by subject area and is populated from many operational

systems.

• Can act as a decision support system.

• Generally concerned with historical data and aggregates.

• Added to regularly, but loaded data is rarely ever directly changed.

• Regular schedule of dumps and loads from operational data stores.

All these features differentiate data warehouses from typical operational database systems.

Data warehouses are commonly kept on separate machines that can be tuned for a lower

frequency of users with different querying characteristics. Data warehouses are usually read-only

based systems, aside from the periodic loading of current information.



Online Transactional Processing systems Operational database systems deal with handling many users and transactions. These databases

are often referred to as Online Transactional Processing systems (or OLTP). These operational

databases are continuously used systems in which users add, update, and query the stored

information.

An example of an OLTP is a typical order-entry application. A customer calls a call center and

orders products from a catalog. The sales representative answering the call can pull up the

order entry screen and enter the line items the customer desires. Whenever an order is placed

it triggers inventory allocations. This seems like a relatively small process, but it will have

generated many records, and many underlying transactions. This type of OLTP system requires

transactions to be speedy and inventory levels to be accurate. The sheer volume of these diverse

operations and the amount of data that is produced provide a poor environment for decision

support.

OLTP systems have been designed to support the primary business processes and are optimized

for transaction processing. To avoid data redundancy and possible data conflicts the data model

has been normalized. An OLTP environment is not necessarily designed for querying and

reporting, which can potentially make universe design based on an OLTP a bit more challenging.



Data Marts A data mart is a repository of data gathered from operational data or other sources and is

designed to serve a particular department or functional group. It is similar to a Data warehouse,

but there would be a difference in size and focus. The emphasis of a data mart is on meeting

the specific demands of a particular group of users. These users can run reports and analyze

data stored in the data mart that is designed to portray information based on their group

requirement needs.

A common approach to using data marts is to keep data at a detail level in the data warehouse

and summarize this information into the data mart for each functional group or department.

Sometimes data marts are designed for each departmental unit, and all departmental data

marts are merged later on into an enterprise-level data warehouse.

Either method offers the benefit of centralizing the information for the end users. Some

characteristics of data marts are as follows:

• Data specialized for a particular group of an organization.

• Engineered for easy access.

• Optimal response from lower volume queries.

Due to more simplified and specialized nature of data marts, organizations are turning to data

marts, as a quick solution to their decision-support needs.



Dimensional Modeling The traditional entity relationship (ER) model uses a normalized approach to database design.

Normalization removes redundancy from the schema to optimize storage. Data warehousing

is not that concerned with saving space. It is more concerned with meeting the decision support

needs. A small amount of redundancy is usually acceptable.

Star and snowflake schemas Dimensional modeling is a more appropriate approach to the warehouse design. With

dimensional modeling you separate the business data into logical events or facts and a set of

corresponding dimensions.

This results in a schema that is commonly referred to as the star schema. This schema will

normally contain a large and centralized fact table which branches off into many small dimension

tables, resembling a star-like layout.

Fact Tables The fact table that sits in the center of this star schema usually contains business events recorded

over time. Examples of data that can be found in this table are: sales transactions, orders and

returns, bank transactions, shipments, and so forth.

The fact table normally consists of a set of numeric values and a number of foreign keys that

correspond to primary keys in the various dimension (lookup) tables. The information stored

in the fact tables is usually static as it is historical. The most common example of a fact table in

the star schema is for sales.

Dimensions The dimension tables consist mainly of descriptive information linked to fact records. Example

of dimension data are: customer names, product descriptions, suppliers, and vendors. Dimension

tables contain fewer records than the facts table. An important factor is that the information in

dimension tables is not static as records in dimension tables can be updated. For example, a

customer address might be modified in the source system.



A typical data warehouse schema will always use dimension tables or tables that deal with

periods of time. These tables are the key element to tracking the time variant information in

these types of databases.

Sometimes a more normalized approach is taken to the dimension tables. When this happens

the star schema changes to a snowflake (or constellation) schema. A snowflake schema is

basically one fact table, connected to a number of dimension tables, and these dimension tables

in turn are connected to additional dimension tables.

In a snowflake schema it is also common to include aggregations across dimensional hierarchies,

for example sales values summed up by store. These sales values can also be summarized into

separate fact tables by region or district.

The dimensional model is a logical technique optimized for queries and reporting. It is the

most common model used in current data warehousing or data mart designs. It provides

simplified hierarchical paths that would enable end users with drill-down analysis capabilities.

Precalculated aggregations can be also embedded in the fact tables, which can result in rapid

query-response times.

Alternative SQL syntaxes for other RDBMS—Learner’s Guide 289


Appendix B

Alternative SQL syntaxes for other RDBMS

SQL syntaxes for other RDBMS This appendix provides the alternative SQL syntaxes for Oracle, MySQL, DB2 and Microsoft

Access, for the more complex objects used within this course.



Object

Name

Oracle

MySQL

DB2

Client

Name

CONCAT(CONCAT(

CLIENT.CLIENT_LASTNAME,',

'),

CLIENT.CLIENT_FIRSTNAME)

{fn concat({fn concat(


')},

CLIENT.CLIENT_FIRSTNAME)}



')},

CLIENT.CLIENT_FIRSTNAME)}

Model

CONCAT(CONCAT(CONCAT

(CONCAT(MODEL.MODEL_NAME,'

'),

MODEL.MODEL_TRIM),' '), MODEL.MODEL_ENGINE)


{fn concat({fn concat( MODEL.MODEL_NAME,' ')} ,MODEL.MODEL_TRIM)},' ')}, MODEL.MODEL_ENGINE)}


{fn concat({fn concat( MODEL.MODEL_NAME,' ')} ,MODEL.MODEL_TRIM)},' ')}, MODEL.MODEL_ENGINE)}

Sale

Year

CONCAT('Calendar Year ',

TO_CHAR(SALE.SALE_DATE,'YYYY'))

{fn concat('Calendar

Year ',

YEAR(SALE.SALE_DATE))}

{fn concat

('Calendar Year ',char(year( SALE.SALE_DATE)))}

Sale

Quarter

CONCAT('Q',TO_CHAR

(SALE.SALE_DATE,'Q'))

{fn concat('Q',

QUARTER(SALE.SALE_DATE))}

{fn concat

('Q',char(quarter(

SALE.SALE_DATE)))}

Sale

Month

TO_CHAR

(SALE.SALE_DATE,'Month')

MONTH(SALE.SALE_DATE)

MONTH(SALE.SALE_DATE)

Rental

Year

CONCAT('Calendar Year ',

TO_CHAR(RENTAL.SALE_DATE,'YYYY'))

{fn concat('Calendar

Year ',

YEAR(RENTAL.SALE_DATE))}

{fn concat

('Calendar Year ',char(year( RENTAL.SALE_DATE)))}

Rental

Quarter

CONCAT('Q',TO_CHAR

(RENTAL.SALE_DATE,'Q'))

{fn concat('Q',

QUARTER(RENTAL.SALE_DATE))}

{fn concat

('Q',char(quarter(

RENTAL.SALE_DATE)))}

Rental

Month

TO_CHAR

(RENTAL.SALE_DATE,'Month')

MONTH(RENTAL.SALE_DATE)

MONTH(RENTAL.SALE_DATE)

Sales

Revenue

2003

sum(CASE WHEN

to_char(SALE.SALE_DATE,'YYYY') ='2003' THEN (SALE_MODEL.SALE_QTY

* MODEL.MODEL_PRICE *(100

- SALE.SALE_SALE_DISCOUNT)/100))

ELSE 0 END)

sum( CASE WHEN

{fn year( SALE.SALE_DATE )} = 2003 THEN (SALE_MODEL.SALE_QTY * MODEL.MODEL_PRICE * (100 - SALE.SALE_SALE_DISCOUNT)/100)) ELSE 0 END )

sum(CASE WHEN

year(SALE.SALE_DATE) = 2003 THEN (SALE_MODEL.SALE_QTY *

MODEL.MODEL_PRICE *(100

- SALE.SALE_SALE_DISCOUNT)/100)) ELSE 0 END )

Sales

Revenue

2004

sum(CASE WHEN

to_char(SALE.SALE_DATE,'YYYY') ='2004' THEN (SALE_MODEL.SALE_QTY



sum( CASE WHEN

{fn year( SALE.SALE_DATE )} = 2004 THEN (SALE_MODEL.SALE_QTY * MODEL.MODEL_PRICE * (100 -

sum(CASE WHEN

year(SALE.SALE_DATE) = 2004

THEN (SALE_MODEL.SALE_QTY *


-

Alternative SQL syntaxes for other RDBMS—Learner’s Guide 291


Object

Name

Oracle

MySQL

DB2

ELSE 0 END)

SALE.SALE_SALE_DISCOUNT)/100))

ELSE 0 END )


ELSE 0 END )

Sales

Revenue

for

FY03-04

sum(CASE WHEN

FINANCE_PERIOD.FP_YEAR

='FY03-04'

THEN (SALE_MODEL.SALE_QTY



ELSE 0 END)

sum( CASE WHEN


='FY03-04' THEN

(SALE_MODEL.SALE_QTY *

MODEL.MODEL_PRICE *

(100 -


ELSE 0 END )

sum(CASE WHEN


='FY03-04' THEN




Sales

Revenue

sum(CASE WHEN


='FY04-05'

sum( CASE WHEN


='FY04-05'

sum(CASE WHEN


='FY04-05'



Object

Name

Oracle

MySQL

DB2

for

FY04-05

THEN (SALE_MODEL.SALE_QTY



ELSE 0 END)

THEN


MODEL.MODEL_PRICE *

(100 -


ELSE 0 END )

THEN




Object Name Microsoft Access

Client Name CLIENT.CLIENT_LASTNAME +', '+ CLIENT.CLIENT_FIRSTNAME

Model MODEL.MODEL_NAME +' '+ MODEL.MODEL_TRIM +' '+ MODEL.MODEL_ENGINE

Sale Year 'Calendar Year ' + format(SALE.SALE_DATE,'YYYY')

Sale Quarter 'Q' + format(SALE.SALE_DATE,'Q')

Sale Month format(SALE.SALE_DATE,'Mmm')

Rental Year 'Calendar Year ' + format(RENTAL.SALE_DATE,'YYYY')

Rental Quarter 'Q' + format(RENTAL.SALE_DATE,'Q')

Rental Month format(RENTAL.SALE_DATE,'Mmm')

Sales Revenue 2003 sum(IIf{fn year(SALE.SALE_DATE )} = 2003,

(SALE_MODEL.SALE_QTY * MODEL.MODEL_PRICE *

(100-SALE.SALE_SALE_DISCOUNT)/100)),0))

Sales Revenue 2004

sum(IIf{fn year(SALE.SALE_DATE )} = 2004,

(SALE_MODEL.SALE_QTY * MODEL.MODEL_PRICE *

(100-SALE.SALE_SALE_DISCOUNT)/100)),0))

Sales Revenue for

FY03-04

sum(IIf(FINANCE_PERIOD.FP_YEAR

='FY03-04',(SALE_MODEL.SALE_QTY * MODEL.MODEL_PRICE * (100-SALE.SALE_SALE_DISCOUNT)/100)),0))

Sales Revenue for

FY04-05

sum(IIf(FINANCE_PERIOD.FP_YEAR

='FY04-05',(SALE_MODEL.SALE_QTY * MODEL.MODEL_PRICE * (100-SALE.SALE_SALE_DISCOUNT)/100)),0))

Answer Key-Learner's Guide 293


Answer Key

This section contains the answers to the reviews and/ or activities for the applicable lessons.

Answer Key—Learner’s Guide 295


Quiz: Understanding BusinessObjects universes Page 27

1. What are the two main panes in Universe Designer?

Answer: Universe pane, Structure pane 2. What are the three ways to issue commands in Universe Designer?

Answer: menu options, toolbar buttons, right-click drop-down menus 3. Where can you define what specific information about the universe gets printed?

Answer: Under Tools ➤ Options ➤ Print/PDF



Quiz: Creating the course universe Page 48

1. Information about universe administration appears on the Universe Parameters dialog box.

Under which tab can you find this information?

Answer: Summary tab 2. Can a universe and its content be embedded in another universe?

Answer: Yes, you can set this up in the Links tab of the Universe Parameters dialog box.

Remember that both universes must reference the same database account or targeted data

source.

3. If you want to distribute the completed universe to the user population using the

BusinessObjects repository, which type of connection should you use?

Answer: Use a secured connection.



Quiz: Building the universe structure Page 86

1. A schema contains two elements. What are they?

Answer:

○ Tables

○ Joins 2. What are three reasons why using the automatic detection routine for setting join cardinalities

is not recommended?

Answer:

○ Cardinality is based on logic. The automatic detection routine uses physical cardinality,

and runs a physical count on the values in both columns being joined. You may get

incorrect results if the physical count does not return the same result as a logical analysis

of the data.

○ The algorithm used by the automatic detection routine assumes that you have sufficient

quantity of data in both tables to be representative in ratio to the database in a live

environment. If you are designing against a test database, for example, with only a

representative sampling of data, because the routine runs a physical count, it could give

you the incorrect answer.

○ The automatic detection routine runs three subsequent queries at the target database per

join, which may take a very long time for large databases.

3. What type of join is created by default between two tables?

Answer: The default join type is equi-join.



Quiz: Creating dimension objects Page 113

1. Which of the three types of objects contain aggregate functions that map to statistics in the

database?

Answer: Measure objects 2. When you are testing objects, what are the three things for which you need to test?

Answer:

○ Do the objects exist? If not, you may have forgotten to save your universe since the object

you are testing was created.

○ Does the SQL appear correct?

○ Are the results of the query correct? 3. If each object maps to a column or function in a target database, when used in a query, what

kind of statement does the object infer?

Answer: A SELECT statement



Quiz: Creating measure objects Page 132

1. Measure objects are very flexible because they are semantically dynamic. What does this

mean?

Answer: This means that the values they return in a query will vary depending on the

dimension and detail objects that are used with them.

2. Measure objects are created in the same way as a dimension or detail object. However, the

object properties differ in two ways. What are they?

Answer: The object properties differ as follows:

○ The Data Type field must be set to Number.

○ The Select field must include an aggregate function.



Quiz: Using lists of values Page 147

1. By default what values are contained in a list of values (LOV)?

Answer: An LOV is a list associated with an object that, by default, contains all the distinct

values from the fields in the database for that object.

2. What are three things that a universe designer should keep in mind when deciding whether

to associate an LOV with an object?

Answer:

○ Because an LOV is based on a SELECT DISTINCT query that is sent to the target database,

associating an LOV will have implications for the efficiency of Web Intelligence.

○ The only purpose for creating an LOV is to assist the end user in choosing an operand

value for a condition. If the LOV does not do this, there is no point in associating it with

the object.

○ Unless the LOV is based on a personal file and not a query, the list will only hold values

that exist within the database.

3. For what types of objects is it recommended not to provide an LOV?

Answer: It is recommended that you do not provide an LOV for the following types of

objects:

○ All measure objects.

○ Any object where the LOV will consist of a large number of values.

○ Any object where the list on its own would be meaningless.



Quiz: Resolving loops in a universe Page 178

1. What is the first step in resolving loops?

Answer: Detecting cardinalities 2. What causes a loop?

Answer: A loop is a join path issue that arises from the way that lookup and fact tables are

related in a relational database. Loops can produce instances where a query returns too few

rows of data.

3. What are the two main methods of resolving loops?

Answer:

○ Aliases

○ Contexts

4. What are the three types of queries you can use to test your contexts?

Answer:

○ Inferred

○ Incompatible

○ Ambiguous



Quiz: Resolving SQL traps Page 207

1. A chasm trap can occur when:

Answer:

1. Two joins from many-to-one-to-many converge on a single table.

2. The query includes objects based on the two “many” tables.

3. There are multiple rows returned for a single dimension value.

2. Describe two ways to resolve chasm traps.

Answer:

1. Create a context for each fact table. This solution works in all cases.

2. Modify the SQL parameters for the universe so you can generate separate SQL queries

for each measure. This solution only works for measure objects. It does not generate

separate queries for dimension or detail objects.

3. Describe three ways to resolve fan traps.

Answer:

1. Alter the SQL parameters for the universe. This only works for measure objects. This

resolution works the same for chasm and fan traps.

2. Create an alias for the table containing the initial aggregation, and then use Detect

Contexts (Tools > Detect Contexts) to detect and propose a context for the alias table and

a context for the original table. This is the most effective way to solve the fan trap problem

as it will work with measure and dimension objects.

3. Avoid the fan trap in the first place by using the same level of granularity.



Quiz: Applying restrictions on objects Page 221

1. What is a restriction?

Answer: A restriction is a condition in SQL that sets criteria to limit the data returned by a

query.

2. Explain two drawbacks of using restrictions at the object level.

Answer:

○ You would get a confusing proliferation of objects for end users because you would then

need a French Clients object, a German Clients object, and so on.

○ As these objects would all represent alternate restrictions, you would not be able to

construct a logical default hierarchy (which end users make use of when drilling down).

○ Although the UK Clients example is fairly clear, in many cases the restriction will not be

obvious to the user simply from the name of the object. The details of the WHERE clause

are not shown in the User module.

○ If two or more similarly restricted objects are included in the same query, the conflict

between the WHERE clauses will cause no data to be returned.

3. When should you use self-restricting joins?

Answer: Use self-restricting joins to apply restrictions to tables when you want the restriction

to apply irrespective of where the table is used in the SQL. This method is ideal when a

table uses a flag to switch between two or more domains.



Quiz: Using @functions with objects Page 235

1. What parameter does the @select require?

Answer: @select requires the path of the existing object to be dynamically linked to. 2. True or False. You can use the @where function in a condition object to point to an object,

but not the other way round.

Answer: True 3. What function is used to create an interactive object that causes a message to appear at query

runtime, that asks the user for specific input?

Answer:

b. @prompt

4. In the @prompt two parameters are mandatory and three are optional. What parameters are

optional?

Answer:

○ LOV pointer or hard-coded list

○ Mono or Multi

○ Free or Constrained



Quiz: Using hierarchies Page 256

1. A hierarchy is the hierarchy based on the order of the objects within the

class.

○ a) Default

○ b) Custom

Answer: a) Default 2. What are two advantages of Automatic Time Hierarchies?

Answer:

1. It is a fairly quick and easy way to set up a Time Hierarchy.

2. It automatically creates an SQL Select clause using the appropriate scalar function or the

RDBMS of the target database.



Quiz: Derived tables and indexes Page 275

1. What part of the SQL expression does Designer use to create column names in the derived

table?

Answer: It uses an alias (in SQL) to create column names.

For example: count(Region.Region_ID) as number_of_regions. 2. When you insert a derived table and insert joins, what happens if you do not add the new

join to the appropriate context?

Answer:

○ When you parse the derived table‟s SQL, it will generate an exception.

○ When you run a query, the derived table will create a Cartesian product.

○ The objects you create from the derived table will be incompatible with objects from any

of the existing contexts.

3. How do you apply index awareness on a universe object?

Answer: Go to the Keys tab of the Edit Properties dialog box for the object you want to make

index aware.

4. How can index awareness improve query performance?

Answer: It can improve query performance by taking advantage of indexes on key columns

in the data source.


Notes

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