TZHANA

SAP HANA Appliance 1.0

TZHANA for Application Consultants

SAP AG 2011

Copyright 2011 SAP AGAll rights reserved

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SAP AG 2011

SAP AG 2011

Agenda

SAP HANA Appliance 1.0Lesson 1: Introduction to HANA

Lesson 3: Architecture

Lesson 2: Look & Feel

Lesson 4: Data Provisioning

Lesson 5: Modelling

Lesson 7: User Management

Lesson 6: Reporting

Lesson 1 Introduction to HANA

New business REALITY

Entirely new POSSIBILITIES

SAPs IN-MEMORY offering

High-Performance ANalytic Appliance

HANA in CONTRAST to SAP Applications

HANA in DETAIL

SAP AG 2011

SAP Naming Update: SAP HANA** always refer to SAP HANA. Never use HANA.

Application

, powered by SAP HANA

Example: SAP Smart Meter Analytics, powered by SAP HANA

Studio

SAP HANA studio

Appliance

SAP HANA appliance software

Database

SAP HANA database

Cloud

SAP HANA application cloud

CategorySAP in-memory computing

PlatformSAP HANA platform

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new business reality / new challenges

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DAILY CHALLENGES

Complex system landscapes

Massive growth of data volume

Immediate results

High flexibility

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Missing opportunitiesCompetitive disadvantage

Reactive business mode

Need for aggregationOutdated figuresGuessing current situation

Lack of transparency

Lack of responsivenessUser frustrationUnsupportable business processes

Sub-optimal execution speed

CONSEQUENCES

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Multicore CPUs

10 Cores / CPU

HARDWARE INNOVATIONS

320 CORES and more! 4 TB RAM and more!

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Multi-CPU Boards

8 CUPs / Board

Multi Server Board

x Boards

Massive Memory setups

2 TB/Server

New to SAP HANA Appliance 1.0

SPS02

new business reality / new challenges

The new realityNew possibilities SAPs offeringHANA in ContrastHANA Details

Rethink old paradigmsInnovation enables new ways of thinking

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AVOID BOTTLENECKS - LATENCY

Prevent CPU IDLE TIME Introduce COLUMNAR DATA STORAGE

S

P

E

E

D

YEAR

CPU Cloc

kspeed

Memory B

andwidth

Memory latency!

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UNDERSTAND Columnar Data Storage

Customer Country Product Amount

100 DE 1 100

100 DE 1 110

200 US 1 120

300 US 2 130

Tuple 1

Tuple 2

Tuple 3

Tuple 4

Column 1

Column 2

Column 3

Column 4

ROW-BASED Storage

COLUMN-BASED Storage

OPTIMIZEDfor current HW

Easily COMPRESSABLE

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AVOID BOTTLENECKS DATA TRANSFER

MOVE calculations into database Only transfer RESULTS

APPLICATION

LAYER

Calculation

DATABASE

LAYER Calculation

Classical Approach

Future Approach

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AVOID BOTTLENECKS PARTITIONING

SPREAD table contents across blades Work on smaller sets of Data in PARALLEL

Initial

Data

Table 1Year A

Table 2Year A

Table 3Year A

Table

Table 1Year B

Table 2Year B

Table 3Year B

Table

Table 1

Table 2

Table 3

Table

Table 1

Table 2

Table 3

New to SAP HANA Appliance

1.0 SPS02

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DISCOVER NEW POSSIBILITIES

NEW APPLICATIONS

Old processes can be IMPROVED

Feasibility boundaries are SHIFTING

No need for AGGREGATION anymore

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COMBINE BUSINESS & TECHNOLOGY

SAP Business Applications

Integrated Systems Business Knowledge

SAP In-Memory Applications

Live Cache BW Accelerator HANA

Strong HARDWARE Partners

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TODAYS SITUATION CLASSIC EDW

Enterprise Data Warehouse (BW)

Corporate BI

Database

Local BI

Data Mart

DB

BWA

Data Mart

DB

NON SAP

Database

Local BI

SAP ERP 1

Database

SAP ERP 2

Database

Data Mart

DB

Local BI

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SHORT TERM SAP HANA Appliance 1.0


Corporate BI

Database

BWA

HANA

NON SAP

Database

Local BI

SAP ERP 1

Database

SAP ERP 2

Database

HANA

Local BI

HANA

Local BI

HANA

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MID TERM SAP HANA Appliance 1.0 SPS03(planned)


Corporate BI

HANA

NON SAP

Database

Local BI

SAP ERP 1

Database

SAP ERP 2

Database

HANA

Local BI

HANA

Local BI

HANA

NEW APPLICATIONS

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VISION SAP IN-MEMORY ComputingApplication Foundation


Corporate BI

SAP ERP 1

SAP ERP 2

New

APP 1

New

APP 2

HANA

NON SAP

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SAP In-Memory ComputingProduct Strategy

In-Memory Analytics HANA 1.0 Real-time operational

analytics with HANA 1.0 Complete BI Suite with BI 4.0

(Aurora) runs on Hana SAP Business by Design 2.6 runs

on in-memory

One Store for Data and Analytics

HANA only persistence layer for SAP Business Suite

SAP Business Suite optimized for In-Memory

Flexible real time analysis of operations at non-aggregated

level

Real-Time operational planning, simulation and forecasting: link

to execution

Reduced landscape complexity Value chain transformation

Capabilities

Benefits

Next generation applications

SAP BW fully running on SAP HANA 1.0 SP03

SAP HANA 1.0 SP03 platform for In-Memory Apps

Business Suite runs on HANA 2.0 SBOP 4.x (Aurora) unified modeling

with Hana Industry and LOB Business Analytics

Solutions BAS

Q4 2010Renovation

SAP HANA Appliance 1.0

2011-12Innovation

SAP HANA Appliance 1.0SP03 2.0

2012+Transformation

HANA 2+

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How does SAP HANA compare to BWA?... Probably the wrong question, but lets give it a whirl...

Technically SAP HANA is far more than BWA

Standard interfaces (SQL, MDX) Real persistence layer (not just flat files) redo/undo logs, backup/recovery, ...

There is a lot of BWA/TREX in HANA Column store; distributed computing; calculation engine

Beyond BWA: Row store (P*time); persistence, transactions (MaxDB), SQL Parser (P*time), ...

Data Models / Content Life is simpler for BWA in the short term

You only load InfoCubes into BWA Technically trivial data model; Automatic creation of relations / join conditions

BWA has BW on top Complex logic? Do it in BW Defining the data model? Do it in BW Analysis authorizations? Do it in BW

SAP HANA 1.0 is intended as a Data Mart (and BWA clearly is not) -> Flexibility (not tied to BW)

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So what do customers get?An empty box plus

SAP HANA 1.0 is: The In-Memory Computing Engine

Including SQL and MDX interface, calculation engine, relational stores, persistence, ... SAP HANA Studio

Administration and Modelling

SAP HANA 1.0 does not have Comprehensive Content The ABAP Data Dictionary No Application Server tier it will be the application server tier in the future (native

applications on HANA like SAP BPC) Front-End Tools (exception: MS Excel)

There are several working front-ends (not included with the In-Memory Appliance) Parallel Ramp ups: SAP BI 4.0, SAP BusinessObjects Analysis 1.1

One consistent administration and monitoring tool for all components

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Creating Models in SAP HANAThe real world (I)

Select the ERP tables you need Understand the ERP data model Locate all required tables

Transactional, master dataand texts...

Load ERP tables into SAP HANA Initial load Implement some delta mechanism

SAP Landscape Transformation for Realtime Data Services: batch/near realtime...

Recreate table relationships in SAP HANA All master data modelling (incl. Texts) Join conditions between tables More complex logic (may be a decision point for Data

Services) SQL script

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Creating Models in SAP HANAThe real world (II)

Create Analysis Authorizations If not everyone should see everything

No import of users from ERP (let alone authorizations)

Build report(s) on top of data model Will you do part of the modelling above SAP HANA layer?

Select suitable reporting tool Excel, SAP BusinessObjects Explorer, SAP BusinessObjects Web Intelligence, SAP

BusinessObjects Dashboards, SAP Crystal Reports, SAP Business Objects Analysis ... Create the report

Verify that what you see is correct Data in SAP HANA correct? Model correct? SAP HANA computing correctly?

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Agenda

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Lesson 5: Modelling


Lesson 6: Reporting

Lesson Objectives

After completing this lesson, you will be able to: Understand in-memory computing in SAP HANA Understand the structure of SAP HANA studio Understand how to configure perspectives Understand how to create a package

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Look&FeelSAP HANA Studio

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Look&FeelAdministration View

NavigatorView

Cheat Sheets

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Look & FeelNavigator View - Default Catalog

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Look & FeelSystem Monitor

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Look & FeelPre-Delivered Administration Console

NavigatorView

PropertiesView

AdministrationView

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Look & FeelPerspectives are built up based on views

Fast Perspective

SwitchChoose perspective from main

menu

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Look and FeelInformation Modeler

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Look&FeelNavigator View - Information Models

Information Models organized in Packages

Attribute Views, Analytic Views,Calculation Views, Analytic Privilegesorganised in folders

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Look & FeelPerspectives are built up based on views

VIEWS!

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Look & FeelTips & Tricks

RESET PERSPECTIVE

will restore your screen!

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Summary

You should now: Understand in-memory computing in SAP HANA Understand the structure of SAP HANA studio Understand how to configure perspectives Understand how to create a package

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Agenda





Lesson 5: Modelling


Lesson 6: Reporting

Lesson Objectives

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After completing this lesson, you will be able to understand the: Architecture of SAP HANA 1.0 Persistence Layer of SAP HANA 1.0 Concept of Backup & Recovery

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Agenda

Lesson 3:Architecture

Backup & Recovery

Persistence Layer

ERP

Architecture OverviewIn Memory Computing Engine (IMCE) and Surroundings

LogERP DB

In-Memory Computing Engine

Clients (planned, e.g.) BI4 Explorer

Dashboard Design

SAP BI4 universes (WebI,...)

Request Processing / Execution Control

MS Excel

BI4 Analysis

SQL Parser MDXSQL Script Calc Engine

Transaction Manager

Session Management

Relational EnginesRow Store Column Store

Persistence LayerPage Management Logger

Disk StorageLog VolumesData Volumes

Authorization Manager

Metadata Manager

IMCE Studio

Administration Modeling

Load Controller

Replication Agent

Replication Server

SAP Business Objects BI4

Data Services Designer

SBO BI4 servers

( program for client)

SBO BI4 Information Design Tool

Other Source Systems

SAP NetWeaver

BW3rd Party

Data Services

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ERP

Architecture OverviewThe engine itself

LogERP DB

Clients (planned, e.g.) SBOP Explorer 4.0

XcelsiusSAP BI universes

(WebI,...)

MS Excel

SBOP Analysis

IMCE Studio


Load Controller

Replication Agent

Business Objects Enterprise


SBO server

programs for clients

SBO Information

Design Tool


SAP NetWeaver

BW3rd Party

Data Services


Request Processing / Execution ControlSQL Parser MDXSQL Script Calc Engine

Transaction Manager

Session Management





Metadata Manager

Replication Server

Load Controller

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ERP

Architecture OverviewLoading Data into HANA

LogERP DB



Transaction Manager

Session Management





Metadata Manager

IMCE Studio

Replication Agent



SBO BI4 servers


SBO Information

Design Tool


SAP NetWeaver

BW3rd Party

Data Services


Dashboard Design


MS Excel

BI4 AnalysisAdministration Modeling

Load Controller

Replication Server

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SLT Replication Concept: Trigger-Based ApproachArchitecture and Key Building Blocks

SAP HANA systemSLT system (NW7.02)

Application Tables

Source system

Write Modules

Controler Modules

DBConnection

RFCConnection

Read Modules

LoggingTables

Application Tables

DB Trigger

Initialization of data replication based on DB trigger

and delta logging concept(as with NearZero downtime

approach)

Flexible and reliable replication process, incl. data conversion

(as used for TDMS and ByDesign) SLT can also be installed on source

system or Solution Manager

Fast data replication via DB connection

(no other interaction)

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ERP

Architecture OverviewData Modeling

LogERP DB



Transaction Manager

Session Management





Metadata Manager

IMCE Studio


Replication Agent



SBO BI4 servers


SBO Information

Design Tool


SAP NetWeaver

BW3rd Party

Data Services


Dashboard Design


MS Excel

BI4 Analysis

Load Controller

Replication Server

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Clients (planned, e.g.)

ERP

Architecture OverviewReporting

LogERP DB



Transaction Manager

Session Management





Metadata Manager

IMCE Studio


Replication Agent



SBO BI4 servers


SBO Information

Design Tool


SAP NetWeaver

BW3rd Party

Data Services

BI4 Explorer

Dashboard Design


MS Excel

BI4 Analysis

Load Controller

Replication Server

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ERP

Architecture OverviewAdministration

LogERP DB



Transaction Manager

Session Management





Metadata Manager

IMCE Studio


Replication Agent



SBO BI4 servers

(program for client)

SBO Information Design Tool


SAP NetWeaver

BW3rd Party

Data Services


Dashboard Design


MS Excel

BI4 Analysis

Load Controller

Replication Server

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Agenda


Backup & Recovery

Persistence Layer

Persistence Layer in In-memory Comp. Engine

Why does an in-memory database need a persistence layer Main Memory is volatile. What happens upon

Database restart? Power outage? ... Data need to be stored in a non-volatile way

Backup and restore

IMCE offers one persistence layer which is used by row store and column store Regular savepoints full persisted image of DB at time of savepoint Logs capturing all DB transactions since last savepoint (redo logs and undo logs written) restore DB from latest savepoint onwards

Create Snapshots ( backup)

Purpose and Scope

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SAP In-Memory Computing Engine

Persistence Layer in In-memory Comp. Engine

Memory

Data

Persistent Storage

Regular automatic savepoints

Information aboutdata changes

LogVolume

DataVolumes

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Data is saved to disk in intervals

Persistence Layer in In-memory Comp. EngineSavepoint writing data in IMCE

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DATA&

Undo

DATA&

Undo

Page Buffer

Log queueData Cache Other

Data PagesData pages of virtual files

Savepoint Coordinator

DATA&

UndoDATA

&Undo

4712

4713

Converter

Persistence Layer in In-memory Comp. EngineSystem Restart

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Reboot or Power failure deletes in-memory data System is normally restarted (lazy restart to keep downtime short: tables with preload flag +

subsequently requested tables are loaded first) System is restored to the state just before the failure (except non-committed transactions) Used for recovery: Last data savepoint Log between the last data savepoint and the time of failure

(contains the data changes of all commited transactions up to that point)

Time

Data savepointto persistent storage

1Log written

to persistent storage(committed transactions)

2Power failure

3

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Agenda


Backup & Recovery

Persistence Layer

Backup & Recovery

Data backup: From persistent storage to external backup destinations Using database functions (SAP in-memory computing studio)

Log backup: Not supported in SAP HANA 1.0

Configuration backup Manual copy of configuation files to external backup destination

Persistent Storage

LogVolume

DataVolumes

conf

Configuration Backup

Save to External Backup Destinations

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Backup & Recovery

Disk failure (data volumes are damaged)System is restored to the state just before the failure (except non-committed transactions)Used for recovery:

Last data backup Log since the last data backup

Assumption: log area undamaged, all log entries still available (not yet overwritten)

Time

Data backupto external backup

destination

1Log written

to persistent storage(committed transactions)

2Disk failure

(data volumes)

3

Recovery scenario Disk Failure (Data Volume)

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56

5

6

Data Backup

Log Backup

Recovery to last Data Backup

Point in Time Recovery

Backup & Recovery

SAP HAnA 1.0

Recovery to status before crash (5)If log is not damaged

Feature Overview

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Summary

In this lesson, you learned about the: Architecture of HANA 1.0 Persistance Layer of HANA 1.0 Concept of Backup & Recovery

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Agenda





Lesson 5: Modelling


Lesson 6: Reporting

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Agenda

Lesson 4:SAP BusinessObjects Data Services

SAP LT Replication Server

Lesson Objectives

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After completing this lesson, you will be able to: Import metadata from SAP ERP into the SAP HANA Database Create a simple 1:1 SAP BusinessObjects Data Services batch job

and dataflow to extract data from your SAP ERP system and load it into the SAP HANA Database

SAP BusinessObjects Data Services 4.0 and SAP HANA

In-Memory Computing Engine (ICE)

SAPERP

Any Source

BW

Modeler

Data Load

Metadata

Repository Server

Open Hub

SAP BusinessObjectsData Services 4.0

HANA

Designer and Management

Console

Data Services is the engine to load data into ICE The HANA Modeler will generate initial loading jobs

Modeler will use Data Services to browse and import external metadata Modeler will generate initial flows to load data into NewDB tables Further modifications to flows done via Data Services Designer

Not yet working

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Process Flow: SAP HANA and Data Services

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Process Flow: SAP HANA

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Basic Data Services Connection Types

Connectivity options already available in Data Services 3.x: Read tables via ABAP dataflows

For large volumes and transformations inside the SAP source (joins, lookups, and so on) ABAP program generated & executed Data transported via file

RFC_READ_TABLE (SAP Table inside a regular dataflow) For single tables, few lines only

RFC/BAPIs function calls To utilize SAP logic instead of reading tables and designing the logic in Data Services

again (limited number of rows per call) IDOCs

Real-time messages mostlyNew to Data Services 4.0 Improved ABAP integration to ERP ODP Operational Data Provider

New SAP delivered API implemented on the ERP side

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Full extractor support through ODP

Full extractor support through ODP data replication API : Data Services can use this API to get initial and delta loads, the data can be streamed to Data Services. Benefits: Only released extractors are shown to Data Services.

Business Suite team releases standard extractors as they are certified for ODP Customer can release custom extractors (created in tx RS02)

Delta support through the delta queues (same mechanism as used by BW today) Data is streamed from SAP to Data Services. No ABAP programs created, no staging in

files. Requirements Support package is need on the ECC/NetWeaver. Standard extractors need to be released by the Business Suite team

* ODP = Operational Data Provider. NOTE: Release in HANA timeframe on ECC 6.0 EhP1 Ehp5 is a limited, DS-specific subset of overall ODP functionality to be released with ECC 6.0 EhP6

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Create a connection to a SAP ERP target

Create a new DataStore of type SAP Applications with specific connection details

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Setup Information Modeler to communicate with Data Services (Configure Import Server)

Click Import to import meta data via Data Services or use the menu

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SAP HANA StudioImporting meta data from an ERP System

Select the import of Source Objects into a connected target

system

1.2.

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Choose one of the maintained connections

Connections of DataStore type SAP Applicationsare imported from the specified DataServices

repository

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Select Objects for importSearch vs. hierarchy drill-down

There are two possibilities to select objects for import Search for objects via the direct input field Use applications hierarchy to drill down to a certain table

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Select In-Memory Computing Engine (ICE) target schema for the metadata import

RKT catalog in In-Memory Computing

Engine empty

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Validate the target structure

1.

2.Validate the target structure

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View the newly created target structure in the SAP HANA Studio

Table creation status in the deployment log

1.

2.

3.

Refresh the Tables section in the RKT catalog and

double click the table to see the structure

2.

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Process Flow: Data Services

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Import the created table structure into Data Services

For modeling of jobs and data flows within SAP Business Objects Data Services the created table structure needs to be imported. The subsequent steps are necessary:

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Create and execute a Data Services job to populate HANA

For creating and executing a simple Data Services job with a 1:1 transfer from the source SAP ERP system to the target HANA system, the following steps are required: Create a new batch job within Data Services (this is the high-level executable to

be started on the fly in Data Services or to be scheduled on a regular basis) Create a new data flow, containing the source table from the SAP ERP system,

a query object realizing a basic 1:1 mapping, and the target table which already exists within the HANA system)

Execute the newly created Data Services job and preview the records with the in SAP In-Memory Computing Studio

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Create and new Data Services Job and data flow with simple 1:1 mapping

Create a simple job and dataflow with a 1:1 mapping from the SAP EPR source table to the

HANA target

Simple 1:1 query object

ABAP dataflow recommended for large data sets

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Execute the job to populate the HANA target table and monitor the load

Monitor load progress

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View the uploaded data within the In-Memory Computing Studio

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Summary

In this lesson, you learned: How to replicate metadata from an SAP ERP system via the In-Memory

Computing Studio and SAP Business Objects Data Service into HANA How to use the replicate metadata to fill it with content, i.e. pulling

transactional data out of an SAP ERP system and pushing it into HANA with a SAP Business Objects Data Services job

Agenda

Lesson 4:SAP BusinessObjects Data Services

SAP LT Replication Server

SAP AG 2011

Lesson Objectives

SAP AG 2011

After completing this lesson, you will be able to: Understand the architectural foundation of LT Replicator and its

technical pre-requisites. Configure LT Replicator for connectivity to the source SAP ERP

system and the target SAP HANA Database. Configure data provisioning in SAP HANA Studio and trigger an

initial load and/or replication.

LT Replication Server for SAP HANA Appliance leverages proven SLO Technologies

Application Lifecyle Mgmt SLO technologies have been used for over 10 years in several hundred projects per year

Key offerings foster SAPs Application Lifecycle Mgmt concept

LT replication Server as a new use case leverages several SLO technologies

SAP AG 2011

LT Replication Server for SAP HANA Appliance

Key benefits of trigger based approach Allows real-time (and scheduled) data replication, replicating only relevant

data into the SAP HANA Database

Ability to migrate data into the SAP HANA Database format while replicating data in real-time

Unlimited release coverage (SAP R/3 4.6C onwards) sourcing data from SAP ERP (and other ABAP based SAP applications)

Leverages proven SLO technology (Near Zero Downtime, TDMS, SAP LT) Simple and fast set-up of LT replicator (initial installation and configuration

in less than 1day) and fully integrated with SAP HANA Studio (as of SPS02)

SAP AG 2011

LT Replication Concept: Trigger-Based Approach Architecture and Key Building Blocks

SAP HANA DatabaseLT Replication Server

Application Tables

Source system

Write Modules

Controler Modules

DBConnection

RFCConnection

Read Modules

LoggingTables

Application Tables

Efficient initialization of data replication based on DB trigger and delta logging concept(as with NearZero downtime approach)

Flexible and reliable replication process, incl. data migration (as used for TDMS and SAP LT)

Fast data replication via DB connectLT replication functionality is fully integrated with SAP HANA Studio

LT replication server does not have to be a separate SAP system and can run on any SAP system with SAP NetWeaver 7.02 ABAP stack (Kernel 7.20EXT)

DB Trigger

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LT Replication Concept: Trigger-Based ApproachKey Building Blocks in Detail Source System

DB Trigger and Table-Based Delta Logging: Only relevant tables considered for DB recording All relevant changes are recorded in logging tables Replicated changes are deleted from logging tables Recording and replication possible for all table classes (e.g.

cluster tables)

Read Module: Collects data changes Declustering of table classes into transparent format

Source system

Read Modules

LoggingTables

Application Tables

DB Trigger

Trigger-based approach has no measureable performance impact in source system

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Leveraging proven SLO technology, LT replication server provides a flexible and reliable infrastructure to manage the entire process

LT Replication Concept: Trigger-Based ApproachKey Building Blocks in Detail LT Replication Server

Controler Module: Ensures mapping between HANA DB structure and DB structure of

source system

Provides ability to conversion/migration values (e.g. date fields into strings)

Includes features to manage entire replication process in a holistic manner, e.g. provides scheduling options to determine the frequency of data replication

Triggers activities of WRITE moduleWrite Module: Writes data through DB connection to SAP HANA system Offers flexibility to switch from single operation (insert update delete)

to array operations LT Replication Server

Write Modules

Controler Modules

System Requirements:

- SAP Netweaver 702 with Kernel 7.20EXT (currently only available on linux 64 or win64) - Filesystem: 100 GB- RAM: 16-32 GB- CPU: 2-4 cores- Recommended number of background jobs: 10

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Technical Requirements and System Set-Up Information for LT Replication Server

SAP HANA systemLT Replication ServerSource system


- SAP Basis: Netweaver 702 with Kernel 7.20EXT (currently limited platform availability)

- Filesystem: 100 GB- RAM: 16-32 GB- CPU: 2-4 cores- Recommended number of background jobs: 10

DBConnection

RFCConnection


- SAP Basis 4.6C and higher- All data bases

Installation:

- respective DMIS 2010 version- Minimum support pack level: latest available

Installation:

- Addon DMIS 2010_1_700- Minimum support pack level: SP04 (planned with release of HANA SPS02)

Installation:

- HANA SPS02: includes LT replication functionality fully integrated into the UI ofthe HANA modeler

Basic Configuration:

- Define RFC connection to source system- Define DB connection to HANA system- Define max. number of jobs to be used for data replication


- Optional: define separate table spacefor logging tables

- Define RFC user with appropriate authorization


- Create a DB user (if required)

LT replication server can run on any SAP system with SAP NetWeaver 7.02 ABAP stack (using SAP Kernel 7.20EXT), for example on Solution Manager 7.1 or the source system it does not have to be a separate SAP system!

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LT Replication Concept: Trigger-Based Approach Configuration of LT Replication Server

RFC Connection

Table space (optional)

Replication mode

Connection to HANA

Number of jobs

A schema defines the configuration ofthe data replication for a source system

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LT Replication Concept: Trigger-Based ApproachSet-up of Data Replication in SAP HANA System (1/2)

Choose Data Provisioning to launch HANA Modeler UI

1. Select source system as defined in LT replication server, related system information and schema will be displayed

2. Use button Load and / or Replicate to set-up the data replication

3. Use button Stop Replication to end or to restart replication

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Select source system

LT Replication Concept: Trigger-Based ApproachSet-up of Data Replication in SAP HANA System (2/2)

Load: starts the initial load of the data from the source system. The data replication is a one-time event - no logging table and triggers are created in the source system.

Replicate: starts the initial load procedure and delta replication as configured in related schema on the LT replication server.

Stop Replication: Stops any current Load or Replicate processes.

Select relevant tables

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Summary and Key Take Aways

LT replication concept is based on the proven SLO technology (used for NearZeroDowntime, TDMS, etc.) used by hundreds of customers with large DBs.

It provides a holistic concept and valuable features to manage the data replication into SAP HANA very efficient and reliable

LT replication server is the ideal solution for all HANA customers who need real-time (and non-realtime) data replication sourcing from SAP ERP systems into HANA

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Summary

In this lesson, you learned: Whats required to setup LT Replicator in your system landscape. How to configure LT Replicator to establish connectivity to the source

SAP ERP system and the target SAP HANA Database. How to configure the SAP HANA Studio to launch an initial load and/or

replication.

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Agenda





Lesson 5: Modelling


Lesson 6: Reporting

Lesson Objectives

After completing this lesson, you will be able to: Understand the purpose of the Information Modeler Describe the levels of modeling in HANA 1.0 Create and display data for an Attribute View Create and display data for Analytical View Create and display data for an Calculation View Understand the purpose of the Export / Import Functionality

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Aim: Enable Plan/Actual Comparison in SAP HANA, Using Data From COPA

Actual Data Planned Data SAP AG 2011

Agenda

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Lesson 5:Introduction to CO-PA Scenario

Introduction to Information Modeler

Levels of Modeling

- Attribute Views

- Analytic Views

- Calculation Views

- Export & Import

CO-PA Background

Profitability Analysis (CO-PA) enables you to evaluate market segments, which can be classified according to products, customers, orders or any combination of these, or strategic business units, such as sales organizations or business areas, with respect to your company's profit or contribution margin.

The aim of the system is to provide your sales, marketing, product management and corporate planning departments with information to support internal accounting and decision-making.

Revenue

Costs

Loss

Profit

Sales quantitySales rev.

Direct material costsVariable production costs

Contribution margin IMaterial overhead Fixed production costs

Contribution margin IIVariances

Contribution margin IIOverhead costsOperating profit

Determine and analyze the profitability of market

segments

Sales OfficeBusiness Unit

Reporting Dimensions

Region Customer

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COPA Storage Architecture

Join ProfitabilitySegment Number

Characteristics

CE4xxxx-Segment Table

Fiscal yearPlan/act. Indic.Plan VersionRecord Type

Value Fields

CE3xxxx-Summarrization Level

CE2xxxx

ActualLine Items

CE1xxxx

Plan Line Items

e.g. xxxx = IDEA

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HANA and CO-PA as an example

SDSD FIFI COCO--PCPC COCO--OMOMCost centers Orders Processes Product costingPosting to a G/L accountBilling document

CE1XXXXCE1XXXX

CE2XXXXCE2XXXX

CE3XXXXCE3XXXX

CE4XXXXCE4XXXXERPERP

MDX

SQL


Other ApplicationsReal Time Replication Service

BICSSAP BusinessObjects

HANA HANA

In Memory Database

Calc & Planning Engine

Data ManagementData Services

HANA Modeling Studio

Application TableApplication Table

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HANA and CO-PA as an example

SDSD FIFI COCO--PCPC COCO--OMOMCost centers Orders Processes Product costingPosting to a G/L accountBilling document

CE1XXXXCE1XXXX

CE2XXXXCE2XXXX

CE3XXXXCE3XXXX

CE4XXXXCE4XXXXERPERP

Application TableApplication Table

But how can we find the tables and there dependencies for all of the ERP applications?

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HANA - Table Relations in ERP

ERPERP

More than 50.000 application tablesMore than 50.000 application tables

Can be analyzed with transaction code SD11 Can be analyzed with transaction code SD11

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HANA - Table Relations in ERP

ERPERP

SD11 SD11

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Agenda

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Levels of Modeling

- Attribute Views

- Analytic Views

- Calculation Views

- Export & Import

SAP HANA Studio Preferences

Select Windows Preferences Information Modeler Allows setting of default

values for information models created by userSet Default Client to

the client used incustomer systemOr set the Client on the User

Account (preferred)Leave Default Language

on preset value (dynamic)Enable preview of Calculated

Attributes

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SAP HANA Studio Features

Modeling Information Models Information models are used to create multiple views of transactional data that can be used for

analytical purposes.

Choice to publish and consume at 4 levels of modelingAttribute View, Analytic View, Calculation View , Calculation View enhanced with Analytical View

Database Views / Column StoresData Preview Physical tables Information Models

Import/Export ModelsData Source schemas (metadata) mass and selective loadLandscapes

Data Provisioning (both initial load and replication)Analytic Privileges / SecurityTroubleshooting / Trace / Logs

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Terminology

SAP HANA Studio: Information Modeler Data

Attributes descriptive data (known as Characteristics SAP BW terminology) Calculated Attributes

Measures data that can be quantified and calculated (known as key figures in SAP BW) Calculated Measures & Restricted Measures

Views Attribute Views i.e. dimensions Analytic Views i.e. cubes Calculation Views similar to virtual provider with services concept in BW

Graphical Script (SQL Script, CE Functions)

Procedures Functions re-usable functionality

Analytic Privilege security object Analytic Privileges

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Agenda

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Levels of Modeling

- Attribute Views

- Analytic Views

- Calculation Views

- Export & Import

Modeling Process Flow

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Modeling for SAP HANA 1.0Using HANA Studio

Step1: (Attribute View)

Separate Master Data Modeling from Fact data Build the needed master data objects as Attribute Views

Join text tables to master data tables If required: join master data tables to each other (e.g. join Plant to

Material)

Step 2: (Analytical View)

Create Cube-like view by joining attributes view to Fact data Build a Data Foundation based on transactional table

Selection of Measures (key figures) ... Add attributes (docking points for joining attribute views)

this is basically your fact table (key figures and dimension IDs)

Join attribute views to data foundation Looks a bit like a star schema

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Step 3: (Calculation View) / Optional

If joins are not sufficient create a Calculation View that is something that looks like a View and has SQL Script inside

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Composite view of other views (tables, re-use join, olap views) Consists of a Graphical & Script based editor SQL Script is a HANA-specific functional script language

Think of a SELECT FROM HANA as a data flow JOIN or UNION two or more data flows Invoke other (built in CE or generic SQL) functions


Step 4: Analytic Privileges Analysis authorizations for row-level security

Can be based on attributes in analytic viewsAnalytic privilege is always a concrete implementation I.e. Specific authorization for specified values of given attribute you have to create privileges for each group of users

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EXERCISE / COPA

Analytical View 1

Attribute Views Attribute Views

Analytical View 2Calculation View

Analytic Privilege3920-3950

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Agenda

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Levels of Modeling

- Attribute Views

- Analytic Views

- Calculation Views

- Export & Import

Attribute Views...... are the reusable dimensions used for analysis. (Time, Account, Product)

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What is an Attribute View? Attributes add context to data. Can be regarded as Master Data tables Can be linked to fact tables in Analytical Views

Attribute View

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Attribute View:View Creation Wizard

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Attribute View ParametersThe first step of the creation wizard

asks for basic view propertiesEnter a name (technical name)

and descriptionSelect view type

StandardTime

Either create a new viewOr select Derived (read only)Or copy (writeable)

Attribute View:Select table(s)

2.

An Attribute View is a join of several tables The second step of the creation wizard

presents a selector for DB tables One can either expand a schema and try

to find the required table(s) viable method for schemas containing a small number of tables

Or one can enter a search term and hit the search button

Highlight table in selector tree (left-hand side, Available) then add to list of Selected tables

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Attribute View:Add additional table

Add additional tables to view Via Add table button search window

One can only add one table at a time using this wizard.

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Attribute View:Add table via drag & drop

Add additional tables to view Via Drag&Drop from Navigator Tree

Set appropriate filter on schema Drag table(s) into the view

1. Filter on table name

2. Drag table into view

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Attribute View:Define join properties

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Table Joins and Properties Join Types

Referential Inner LeftOuter rightOuter TextJoin

Cardinality 1:1N:1 1:N

Language Column (for text join)Note: the direction in which you draw

the join matters (left table first)

Joins

Inner Join.. return rows when there is at least one match in both tables.

Inner is used even if its not added.

Left & Right Join. the Left Join (or Left Outer Join) returns all rows from the left

table even if there are no matches in the right table. The Right Join (or Right Outer Join) returns all the rows from the right table, even if there are no matches in the left table.

Full Outer Join the Outer Join is neither left nor right - it's both. It includes all

the rows from both of the tables or result sets participating in the Join. When no matching rows exist for rows on the left side or right side of the Join, you see NULL values.

Referential Join.. used where referential integrity is enforced

Text Join.. for text join a description mapping must be defined. For each

attribute it is possible to define a description mapping that will be language specific

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Attribute View:Output field selection and filters

4

Select Attributes to show up in view The output structure of the view must be

explicitly defined At least one key attribute is required. Any number of non-key attributes may

be defined.

Define static filter values Can be based on any table column Column does not need to be selected

for output ([key] attribute)

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Attribute View:Set description mapping

5

Map texts to (semantic) keys For each attribute in the output structure

one can define a description mapping Select the attribute in the output

structure Description mapping is configured in

the Properties view for the attribute.

The drop-down menu for the description mapping will show all fields of all tables which are joined in the attribute view.

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Attribute Properties

MDX per default only shows key fields This is governed by an

output field property ofthe attribute view

If Hierarchy Active= false for non-key field, field does not show upin Excel

Example: Product dimension has two attributes, but only Product_number appears in Excel

Property Hierarchy Active see non-key fields via MDX

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Attribute View:Define a level hierarchy

6.

Hierarchy filter in ExcelHierarchies are only accessible via MDX Define a level hierarchy

Need one attribute per hierarchy level Select column from output structure (drag & drop) Fixed number of levels

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Attribute View:Define a parent-child hierarchy

7.

Hierarchies are only accessible via MDX Define a parent-child hierarchy

Variable number of levels for sub-trees within the hierarchy

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Attribute View:Calculated Attributes

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Create a attribute based on a static value or dynamic calculation Built in functions (Conversion, String, Math, Date ...)

Attribute View:Save and activate the view

8.

Create executable version of the view Save the view

Save button in top-left corner of Studio This saves the information model, i.e. the metadata

of the view that has just been defined. This information model itself is not visible to

reporting tools Activate the view

Right-click view and choose Activate from context menu

This creates a database view in schema _SYS_BIC(a so-called column view)

Name of the column view:_SYS_BIC.I_/

This column view can be accessed from reporting tools

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Attribute View:Preview the view

Data Preview on the Information Model:

Data Preview on Column View:

9.

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Attribute View:Time Dimension Attribute Views

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GregorianDate (Timestamp), Year (2007)

Fiscal Variance (K4)

_SYS_BI.M_TIME_DIMENSION

_SYS_BI.M_FISICAL_CALENDAR

Attribute View:Time Dimension Attribute Views

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JOIN FACT table to Fiscal Attribute View

JOIN FACT table to Time Attribute ViewDate field

Agenda

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Levels of Modeling

- Attribute Views

- Analytic Views

- Calculation Views

- Export & Import

Analytical View are the multidimensional views that analyze values from single fact table

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An Analytic View can be regarded as a cube Multidimensional reporting model Fact table (data foundation) joined against modelled dimensions (attribute views)

Analytic Views do not store data Data is read from the joined database tables Joins and calculated measures are evaluated at run time Master data for MDX/BICS are stored in system tables

Analytic View

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Analytic ViewView creation wizard

Analytic View Set Parameters

Assign unique name Enter a description Create new view from scratch (Create New) Or choose an existing view as template (Copy From)

1.

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Analytic ViewSelect Table(s)

Tables for the data foundation Table selection wizard.

Same as with attribute views (search and select) Can only select measures from one table (transactional data) Can select attributes from several tables (must be joinable)

It is also possible to add tables later Via single-table selection wizard Or via drag & drop from navigator tree (same as with attribute views)

2.

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Dimension selection (Attribute views) Selection wizard.

Select any suitable Attribute View from any package Analytic View and Attribute View do not need to be in the same package

It is also possible to add Attribute Views later Via drag & drop from navigator tree You can only drop into the logical view-tab

of the view editor

Analytic ViewSelect Attribute view(s)

3.

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Two steps of view creation reflected in editor tabs Tab Data Foundation Create the data foundation (fact table)

(Optional: join data base tables) Select attributes and measures from table(s) this defines the data foundation (Optional: create calculated and restricted measures)

Tab Logical View Join Attribute Views to the data foundation This is where you can drag attribute views into the editor

Analytic ViewAnalytic View Editor

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Table FACT Table

Attribute ViewsData Foundation Logical View

Analytic ViewDefine the Data Foundation

Analytic View (Data Foundation) Attribute and Measures Can create Attribute Filters Must have at least one Attribute Must have at least one Measure Can create Restricted Measures Can create Calculated Measures Can rename Attribute and Measures

on the properties tab

5.

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Analytic ViewJoin Attribute Views to Data Foundation

4.

Define joins between Attribute Views and Data Foundation Join Attribute View to a private attribute of the data foundation

Private Attribute: attribute selected from a database table Typically one would include all key attributes of the attribute view in the join definition Default join type is inner join

Non-key fields of attribute view are implicitly added to the analytic view navigation attributes

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Analytic ViewDefining Calculated Measures

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Aggregation (sum, min, max, count), Data Types (decimals, numbers etc) Expressions / Operators Functions (String, Date Math, Conversion)

Analytic ViewDefining Restricted Measures

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Create executable version of the view Save the view

Save button in top-left corner of Studio This saves the information model, i.e. the metadata of

the view that has just been defined. This information model itself is not visible to reporting

tools Activate the view

Right-click view and choose Activate from context menu

This creates a database view in schema _SYS_BIC(a so-called column view)

Name of the column view:_SYS_BIC.I_/

This column view can be accessed from reporting tools

Analytic ViewSave and Activate the View

8.

8.

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Use the built-in Eclipse-Preview of HANA Studio Launch preview from the Information Model (not from the Column View)

Either right-click on Analytic View in Information-Model-part of navigator tree Or click on preview-icon in top-right corner of the view editor

Three preview-modes Raw data (table display) Number of distinct values per column Interactive graphical analysis

Analytic ViewPreview data of analytic view

9.

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Analytic View

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EXERCISE / COPA

Actual DataAnalytical View

Model

Planned DataAnalytical View

Model

Customer / ProductAttribute View

Models

Analytical View Column Stores

Activate Activate

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Agenda

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Levels of Modeling

- Attribute Views

- Analytic Views

- Calculation Views

- Export & Import

Calculation View

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are used to create your own data foundation using database tables, attribute views, and analytic views to address a complex business requirement.

Calculation views are: A column view that is visible to reporting toolsWhen the view is accessed, a function is implicitly executed

The function within the calculation view That function is defined in the HANA-specific language SQL Script Functions can contain SQL commands

SELECT FROM ... One can read not only from DB tables but also from column views created for

analytic views or attribute views SQL in functions must be read only (no insert, update, delete, drop, ...)

Functions can call other functionsModularize the logic within the calculation viewHANA offers pre-defined functions, e.g. for creating a join or union of tables

Two Types of Calculation Views

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Composite views, re-uses Analytical and Attribute viewsSQL / SQL Script / Custom Functions

Analytical View

UNION

GRAPHICAL SQL Script

Analytical View

UNION

Calculation View (graphical)

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Calculation View (Graphical)View creation wizard

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Parameter wizard for calculation view Enter a view name and description

Name must be alphanumeric (A-Z; 0-9; _)

Select Graphical or SQL Script Note: SQL knowledge required

when selecting SQL Script.

Calculation View (Graphical)View creation wizard

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Select any tables, attribute or analytical views to Add to the Calculation View Either select raw tables or on the next screen select existing views.

Calculation View (Graphical)

Select Nodes from the Tools Palette and draw a data flow graph Select 2 projection nodes and 1 Union node

Projection nodes will be used to set the Actual versus Planned indicatorDrag a connection line between all the nodesThe output node will represent the data flow graph end

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Select each Projection node and add all the fields to the output node Do not select the PLIKZ field, this field will by added with a calculated column

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Create a Calculated Column called KPLIKZ for each Projection node Actual = 0, Planned = 1

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Define the UNION by mapping both Projection Nodes to the target

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Add the Attributes and Measure to the Output Activation will create the Column view that can be accessed by the front end tools

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Calculation View (scripting)

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SQL Script - New Programming Model

Functional extension - allows the definition of (side-effect free) functions which can be used to express and encapsulate complex data flows

Data type extension - allows the definition of types without corresponding tables

Traditional Model:Data to Code

DB Server

Application

ServerCode

New Model:Code to Data

DB Server

Application

Server

Code

is a collection of SQL extensions to push data-intensive logic into the Database

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Calculation View (Scripting)Calculation View Wizard

Parameter wizard for calculation view Enter a view name and description

Name must be alphanumeric (A-Z; 0-9; _)

Select SQL Script Note: Select the database

Schema where the tables are located.

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Calculation View (scripting)Calc View table type

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Define the Output structure (Table Type) of the Calculation View

Calculation View (scripting)Function definition

Define Function (with input and output parameters) The input parameter is optional

Can be a scalar value to pass parameters from the front-end tools in order to filter the results (if supported by front-ends).

Can be a table type to pass results from one function into another The output parameter is mandatory

Can be a locally defined table type or a globally existing table Defines the structure of the function output

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Calculation View (scripting)Add the SQL Script code

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Write the necessary select statements to query the data and populate the output table structure

Creating the database object for the calculation view Metadata (the calculation view coding) has to be translated into run-time objects

This is done by executing the coding (green arrow in SQL editor) The defined table type is dropped and created The SQL script function is created Column views are created in the chosen output schema. View name:._SYS_SS_CE__RET

Calculation View (scripting)Creating run-time objects

Verify result (log area of the SQL editor).

Execute the view

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Calculation View (scripting)Calc View output structure

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Select the attributes and measure for the output node. This will represent the definition of the column view that the front end tools will query against

Calculation View (scripting)Save and activate

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Final step: save and activate the calculation view Store the view metadata etc. Save the view via the save button Activate the view from its context menu

save and activate

Calculation View (scripting)Viewing the data

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Viewing the data in a calculation view from the IMCE Studio Data PreviewData preview for calculation views is not available (neither for Information Model nor for

Column View)Alternative: SQL editorUse a SELECT statement of the form:SELECT SUM(), FROM GROUP BY

Recommendations - How to build content

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How to build content

Analytical View Attribute View Tables

Calculation View

Recommended

Not recommendedNot recommended

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Calculation View & SQL Script When to use

Create custom re-usable calculation functions Re-use standard SQL functions not provided within modeler

Calculation views support UNION Built in SQL Script functions available for union support

Calculation views required if key figures span across tables

Advanced SQL Scripting development within Calculation Views SQL Scripting can query existing Attribute & Analytical views Perform join between Column and Row store

Complete Control over

SQL

Business Logic

Unions between

tables

Key figures span fact

tables

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Agenda

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Levels of Modeling

- Attribute Views

- Analytic Views

- Calculation Views

- Export & Import

Import and Export

Import and Export

What are the purposes of an the Export and Import Functionality? What are the steps involved in Export and Import Functionality?

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Process Flow

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Exporting and importing with SAP HANA

HANA supports export and import of Information Models, tables and moreExport and Import is handled via SAP HANA Studio

Client-side export/import: to / from client PC running SAP HANA Studio Server-side export/import: to file system of SAP HANA Database server

DB Server

Information Models

Tables

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Start Import / Export wizardsIn SAP HANA Studio

Two options: From Menu:

File Export From Quick Launch

Menu Help Quick Launch

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Process Flow

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Client Side Export / Import of Information Models

What is a client-side Export? Export of Repository Objects

Definitions of Attribute-, Analytic-, Calculation Views

Analytic Privileges To the Client

I.e. to the host on which Studio is running

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Client Side Export of Information Models (I)Creation Wizard

Select client-side export Information Modeler Information Models

Select system/user to export fromThat user needs access to repository

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Client Side Export of Information Models (II)Select views and Analytic Privileges to export

Select Objects to Export Highlight on left-hand side tree add to the right-hand side tree Select individual views / privileges Or entire packages

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Client Side Export of Information Models (III)Specify the export location

Specify a folder on the client PC to export into Within that folder, a folder with the name of the HANA system will be created

Name of HANA System = ; here: GBS

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Client Side Export of Information Models (IV)Verify Export

Check export in Job log

Check output on file system Package structure recreated in export path

Objects exported as XML files

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Client-Side Import of Information Models (I)Import Wizard

Choose client-side importof Information Models

Select target system/user combination to import into

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Process Flow

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Client-Side Import of Information Models (II)Select source folder

Select the source folder to import from This is the folder

Must contain a sub-folder

Which in turn has sub-foldersanalyticviewsattributeviews

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Client-Side Import of Information Models (III)Select objects to import

Choose list of views to import As before:

Select individual views Or entire packages

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Client-Side Import of Information Models (IV)Run the import

Click Finish to execute the import

Then: check progress in job log

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Client-Side Import of Information Models (V)Considerations

Client side import cannot overwrite existing objects For importing an update to a view into a target system

First delete the view from the target system Then perform the import

Client side import does not activate Run mass activation following the import

Exported objects (xml files) can be changed Difficult to control editing of objects

It is a way to copy views from one package into anotherNote: quick launch mass copy is the intended tool for this task

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Mass Activation of Information Models (I)Set up quick launch

Important prerequisite: Configure Quick Launch to use the correct system/user combination

Check current configuration Use Manage

Connectionsto change

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Mass Activation of Information Models (II)Mass activation wizard

Start mass activation from Quick Launch In the wizard

Select entire package Or individual views / privileges

Click Activate This takes care

of dependencies Activates in the

correct order

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Summary

In this lesson, you learned: Understand the purpose of the Information Modeler Describe the levels of modeling in HANA 1.0 Create and display data for an Attribute View Create and display data for an Analytical View Create and display data for a Calculation View Understand the purpose of the Export / Import Functionality

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Agenda





Lesson 5: Modelling


Lesson 6: Reporting

Lesson Objectives

After completing this lesson, you should be able to: Understand connectivity options for reporting on top of SAP HANA Understand the BusinessObjects BI4.0 platform and reporting possibilities Use different client tools to report on SAP HANA

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Agenda

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Lesson 6:SAP HANA, reporting layer and connectivity options

Microsoft Excel

SAP BusinessObjects Analysis

SAP BusinessObjects Explorer

SAP BusinessObjects BI 4.0

SAP Crystal Reports for Enterprise, Dashboards and Web Intelligence

ERP

Architecture OverviewSAP HANA Engine and Surroundings

LogERP DB



Dashboard Design


Request Processing / Execution Control

MS Excel

BI4 Analysis

SQL Parser MDXSQL Script Calc Engine

Transaction Manager

Session Management





Metadata Manager

IMCE Studio


Load Controller

Replication Agent

Replication Server

SAP Business Objects BI4


SBO BI4 servers

(program)

SBO BI4 Information

Design Tool


SAP NetWeaver

BW3rd Party

Data Services

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Reporting on SAP HANA Client and connectivity options

SAP HANA

SAP In-memory Computing Engine

Web Intelligence

Dashboards

Excel

Crystal Reports

for Enterprise

Semantic Layer (universe UNX)

MDX SQL

ODBO

Analysis Office v1.1

BICS

ODBC

Explorer

JDBCJDBC ODBC

Crystal Reports 2011

JDBC ODBC

SQLSQL

Are part of SAP BusinessObjects BI 4.0

SQL

SAP AG 2011

Reporting on SAP HANAOpen interfaces

SAP HANA 1.0 provides various interface reporting options ODBO OLE DB for OLAP

Microsoft-driven specification for multidimensional (cross-tab style) reporting Requests are sent to the database via MDX (MultiDimensional eXpression language)

ODBC Open DataBase Connectivity Microsoft-driven specification for relational reporting Database requests are made via SQL (Structured Query Language) Heavily adopted in industry No longer Microsoft-centric - Unix and Linux drivers exist for ODBC

JDBC Java DataBase Connectivity Relational reporting drivers specified by the Java community. Popular on Unix platforms.

BICS BI Consumer Services SAP Proprietary interface that offers advantages for OLAP access over MDX on

multidimensional reporting objects Common driver technology used by SAP BusinessObjects Analysis, Office Edition for

connectivity to SAP NetWeaver BW SQLDBC is SAP native database SDK

SAP AG 2011

Agenda

SAP AG 2011


Microsoft Excel





SAP BusinessObjects Analysis, Office Edition

Access Analytic and Calculation Views from Analysis Office (MS Excel or Powerpoint) via a locally defined ODBC connection

SAP AG 2011

SAP BusinessObjects Analysis, Office Edition

SAP AG 2011

Agenda

SAP AG 2011


Microsoft Excel





Reporting on SAP HANANative Excel interface - Pivot Tables (ODBO)

Multidimensional reporting is available via Excel Pivot Tables This has the advantage of quick and dirty cross-tab style reporting via Excel Numerous disadvantages exist

The report definition is only available locally (workarounds exist) Subject to performance limitations of the desktop machine where Excel runs

Pivot Tables can be initiated in numerous ways but primary entry point is via the Excel DATA menu option.

SAP AG 2011

Reporting on SAP HANANative Excel interface via ODBO

HANA ODBO drivers is available via the Other/Advanced option of the Data Connection Wizard:

Clicking OK yields HANA Logon:

SAP AG 2011

Reporting on SAP HANANative Excel interface the Pivot Table

Standard Microsoft Pivot Table interface is presented. Check Measures, Drag and drop rows/columns

SAP AG 2011

Agenda

SAP AG 2011


Microsoft Excel





Bring BI to all business users Simplicity and speed of search Intuitive data exploration and

visualization Fast response across mountains of

data anywhere in the organization Accelerated version with in-

memory technologies

Help IT to be successful Easy and efficient to manage

and scale More reactive to business with

faster delivery Support for heterogeneous data

sources

Data Search and ExplorationSAP BusinessObjects BI4.0 Explorer

SAP AG 2011

What is BusinessObjects Explorer?Its search against BI

Use familiar key-word search to find business information Answers on-the-fly and

investigative questionsSearches directly on pre indexed data No previous reports or metrics

need to exist Provides fast search and

explorationSearches across all data sources Any universe accessible source Any SAP NetWeaver BW

Accelerator accessible source And of course any accessible

HANA system

SAP AG 2011

and Then Its Exploration Of the Results

Intuitively explore on data No data model or data

knowledge required

Automated relevancy of results Most relevant information

is displayed first Best chart type auto

generated

Share insights with others Export to CSV or image Save it locally as a browser bookmark One-click to send a link to the results by email

SAP AG 2011

Explorer for HANASetup

In SAP BusinessObjects BI4.0 Central Management Console, Advanced configuration for Explorer Application Enable the use of HANA connections defined from Information Design Tool

http://mybiserver:8080/BOE/CMC-> Applications -> Explorer -> Properties on contextual menu -> Advanced configuration

newdb.connections.enabled = true

SAP AG 2011

Explorer for HANAInformation Space Creation

SAP AG 2011

Agenda

SAP AG 2011


Microsoft Excel





Complete BI Suite to Put Together Information in the Users Preferred Format

DIFFERENT NEEDS

Dashboards

Reporting

Interactive Analysis OLAPAnalysis

DataExploration

How do I visualize key performance

indicators for better decision

making?

How do I answer ad hoc questions and interact with

shared information?

How do I find immediate answers to business

questions?

How do I uncover trends from

historical data and make possible

better forecasts?

How do I turn data into pixel-perfect formatted reports

for greater insight?

SAP AG 2011

Reporting on HANA SAP BusinessObjects BI4.0 Reporting Clients

Web Intelligence (Interactive Analysis)

Web Intelligence (Interactive Analysis)

ExplorerExplorer

Guided

Dashboard Design

(Xcelsius)

Dashboard Design

(Xcelsius)

Search &Exploration Ad-Hoc QRA

Dashboarding &Visualization

EnterpriseReporting

Interactive ExperienceFree

Professionally Informed

Technically Capable

InformationConsumers

Executives &Managers

Business Analysts

Crystal ReportsCrystal Reports

SAP AG 2011

The Business Intelligence placeSAP BusinessObject BI 4.0 Launch Pad

New self-service BI access making it easier to find all available content

Enhanced filtering and search options reducing page scrolling

Enhanced navigation for working with multiple documents at the same time

New self-service BI access making it easier to find all available content

Enhanced filtering and search options reducing page scrolling

Enhanced navigation for working with multiple documents at the same time

Self-Service Information Consumption

Self-Service Information Consumption

SAP AG 2011

User personalized BI WorkspaceSAP BusinessObjects BI 4.0 BI Workspace

Hom

ePage Modules

BI Workspace

Web C

ontent

Agnostic

Crystal R

eports

Analysis

Web Intelligence

Dashboards

Reporting, Analysis Other ContentVisual

Organizing and displaying any BI content with decreased IT dependency

Simple WYSIWYG authoring for creating and modifying content

Inter-portlet communication enabling information exchange between components

Organizing and displaying any BI content with decreased IT dependency

Simple WYSIWYG authoring for creating and modifying content

Inter-portlet communication enabling information exchange between components

Personalized Information Consumption

Personalized Information Consumption

SAP AG 2011

Semantic Layer Mission

Enable the business users to freely and securely access, analyze, enrich and share information using familiar business terms Make business users autonomous Enable single user experience over all data (structured & unstructured) Provide trust and consistency over data by ensuring that the same business terms are used

throughout the organization Enable consumption by all applications and BI tools Allow IT to keep control and ensure security of information

Semantic LayerData Sources

Query and Analysis

Dashboards andVisualizations

Reporting

Full-Spectrum Business Intelligence

SAP AG 2011

Common Semantic Layer

One consistent user experience across all BI front-ends

One abstraction layer for data sources Adapt and leverage data source capabilities without

requiring to change data models and/or move data Smooth evolution from universes for existing

customers

PioneerPioneer WebIntelligenceWeb

IntelligenceCrystalReportsCrystalReports XcelsiusXcelsius

Common Semantic LayerCommon Semantic Layer

InfoProviderInfoProvider

Data SourceData Source DTPDTP DSODSO

XML WS

BI Consumption

Business Semantic Design

Data Access Design

ETLETL

Common semantic layer = one unified approach for meta data support

SAP AG 2011

Semantic Layer deliverables in SAP BusinessObjects BI 4.0

ToolsInformation design tool

Universe design tool

New generation design toolAll new projects should use this tool. Most existing

universes can be opened and converted to the new format by this tool.

Universe design as XI3.xStill shipped in this version in order to enable the

smoothest possible transition.

Components

Information engine

Query server Data federation engineThis is the component that enables MSU (Multi-Source

Universe) functionality.

Connection server

Query & computation Behind the scenes, this is the component that enables querying and computational capabilities to BI clients

during report consumption.

ConnectivityThis is the component that establishes the connectivity

to data sources.

SAP AG 2011

SAP BusinessObjects Information Design Tool

New Project Define Relational Connection Define Data Foundation Define Business Layer Publish Universe

SAP AG 2011

Agenda

SAP AG 2011


Microsoft Excel





Pixel perfect reportingSAP Crystal Reports for Enterprise

New styling with ribbon bar look and feel

Common query design experience across all data sources with new semantic layer

Automated report translation for global deployments

New styling with ribbon bar look and feel

Common query design experience across all data sources with new semantic layer

Automated report translation for global deployments

Next-Generation Report Designer Experience

Next-Generation Report Designer Experience

SAP AG 2011

SAP Crystal Reports for Enterprise 4.0

SAP AG 2011

Consume attractive, personalized dashboards online or offline Access to personalized, Flash-

based dashboards Secure visualizations anywhere

portal, reports, PDF, MS Office documents

Empower business users with interactive information Powerful what-if analysis with

sliders and other controls Ability to drill-down into details Pre-built components, skins, maps,

charts, gauges, and selectors

Dashboarding & Data VisualizationSAP BusinessObjects BI4.0 Dashboards (XCelcius)

SAP AG 2011

SAP BusinessObjects Dashboards 4.0Universe Queries

SAP AG 2011

Ad Hoc Query, Reporting, Analysis SAP BusinessObjects BI4.0 Web Intelligence

Empower business users with powerful, yet easy to use analysis Intuitive, Web-based interface with

TZHANA

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