1 Brett Hanes 30 March 2007 Data Warehousing & Business Intelligence 30 March 2007 Brett Hanes.

1Brett Hanes30 March 2007

Data Warehousing &Business Intelligence

30 March 2007

Brett Hanes


Agenda• Overview• Data Warehousing

• Definition & Purpose• Varieties• General Architecture• Modeling• More Information

• Business Intelligence• Definition & Purpose• Common Components

• How It All Works Together• Why Is It Useful?• How To Convince The Business• Summary


Data Warehousing (DW)• Definition

• A subject-oriented, integrated & non-volatile database updated on a typically rhythmic cycle from an enterprise’s various transaction databases.

• Purpose• Accumulate data from disparate data sources

for querying purposes• Separate reporting and analysis operations from

transaction systems to maximize the performance of both

Commonly very large repositories that house historical data


Common Data Warehouse Components• Staging Area

• A preparatory repository where transaction data can be transformed for use in the data warehouse

• Data Mart • Traditional dimensionally modeled set of dimension and

fact tables• Per Kimball, a data warehouse is the union of a set of

data marts

• Operational Data Store (ODS)• Modeled to support near real-time reporting needs• Contains traits of both relational and dimensional

modeling techniques


Data Warehouse Modeling

• Data warehouses typically use a denormalized method called dimensional modeling made up of the following components:

• Dimension• An entity defined in its entirety with a single primary key• Examples: Customer, Product, Sales Force, Calendar

• Fact• Details (often numerical) regarding a set of dimensions• Example: Order Details


Data Flow from Transaction to Warehouse

Complex Structure

Necessary for Accurate

Transactions

Simplified Structure

Necessary for Fast,

Powerful Reports

1 - Data Input viaApplications to transaction databases

2 - Data transfer from transaction system to data warehouse via Extract-Transform-Load (ETL) Tool (i.e. Informatica)

3 - Data Output via Business Intelligence Tool (i.e. Cognos, Business Objects, Hyperion)

Separation of Transactions and Reporting Improves Performance and Enhances Capabilities


Learning More About Data Warehousing• Pre-eminent Data Warehousing Minds

– Bill Inmon -> Normalization• Building the Data Warehouse• Corporate Information Factory

– Ralph Kimball -> Dimensional• The Data Warehouse Lifecycle Toolkit• The Data Warehouse Toolkit

Word is they don’t really get along


Business Intelligence Software• Definition

• A set of tools that allow users to access enterprise data via reports, Online Analytical Processing (OLAP) cubes, graphs/charts, ad-hoc queries and dashboards

• Purpose• Allow users to view the data from all levels of

the enterprise• Provide users with information necessary to

make timely, well-informed business decisions

The tools must be easy for the end user to understand and manipulate


Some Components In The BI Toolkit• Reports (Example)

• Commonly needed data can be structured in a set of canned reports made available to large numbers of users

• Flexibility can be given to users through ad-hoc querying and filters

• Cubes (Example)• Multi-dimensional, allowing the user the view

the data from multiple angles• Interactive, giving the user the ability to

change what is viewable on the fly


Some Components In The BI Toolkit• Charts & Graphs (Example)

• Graphical Representation of data • Commonly used in presentations and statistical

analysis

• Dashboards (Example)• Actively updating graphical displays that

provides business users with updates on key metrics

• Some dashboards provide drill through capability, allowing users to start with summary data and dive in to the details


How It All Works TogetherExtract

TransformLoad

Data Input

OLTP

ATRRS

OLTP

RECBASS

OLTP

AIMSPC

RATSSRFMSS

Other Possible Data Sources

Disparate Data Sources

TIMS DW

SingleReportingRepository

Real-timeDashboards

Static and Ad-hoc Reporting

GraphicalData Analysis


Why Is It Useful?

ODS

DW

The data transmitted from the engine in flight can alert a service

team of an engine component in need of repair so they can meet the plane

at the gate.

Engineers can analyze the data to find ways of designing engine

components with longer life spans.


Convincing The Business

• Consider the Previous Example– Having a team waiting at the gate to

service an engine reduces flight delays– Engineering analysis helps create higher

quality engines that:• Requires less servicing• Stay on wing longer

• In Other Words….You Save $$$$$$$$$!!!!!

Learn to speak the language of the business users…Understand what is

important to them


Keys To Success• Sponsorship

• High level endorsement is essential to ensuring you have the authority to drive the effort

• Funding• You have to spend money to save/make money

• Time• This can be a years long effort to implement• Maintenance is ever-present

• Central Governance• Without strict governance over components of

your enterprise data warehouse, you risk stove piping


Summary• Data is Key

• Whether coming in or going out, data is the foundation of all business applications and should be structured to properly meet the need

• Solutions are Complex• There are many components to a good BI

strategy…and they all have to work

• Diligence Required• Data will change• Technology will change• Be assured…user requirements will change


Questions?


Appendix


Report Example


Cube Example

Dimensions and facts can be dragged and dropped on the to

display to view the data in different ways


Chart/Graph Example


Dashboard Example

1 Brett Hanes 30 March 2007 Data Warehousing & Business Intelligence 30 March 2007 Brett Hanes.

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