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© SAP UCC 2006 SAP BW Course 1
SAP® NetWeaver™ Business Intelligence
Business Information Warehouse
The German University Competence Centers’ BW CourseBased on SAP BW 3.5 and mySAP® ERP® 2004 (ECC 5.0)
Basics - Reporting & Analysis - Modeling & Staging - Data MiningmySAP® ERP® Connectivity
© SAP UCC at Technische Universität MünchenDipl. oec. Matthias Mohr / Prof. Dr. Helmut Krcmar
© SAP UCC 2006 SAP BW Course 2
Copyright 2006 SAP UCC TU München All Rights Reserved
Neither this publication nor any part thereof may be copied or reproduced in any form or by any means, or translated into another language, without the prior consent of SAP UCC TU Munich. The information contained in this publication may be changed without prior notice.
Software products offered by SAP AG or its sales and distribution companies also may contain software components of other software manufacturers.
Microsoft®, WINDOWS®, NT®, EXCEL®, Word®, PowerPoint®, and SQL Server® are registered trademarks of Microsoft Corporation.
IBM®, DB2®, DB2 Universal Database, OS/2®, Parallel Sysplex®, MVS/ESA®, AIX®, S/390®, AS/400®, OS/390® and OS/400®, iSeries, pSeries, zSeries, z/OS, AFP, Intelligent Miner, WebSphere®, Netfinity®, Tivoli®, Informix®, and Informix® Dynamic ServerTM are registered trademarks of IBM Corporation in the United States and other countries.
ORACLE® is a registered trademark of ORACLE Corporation.
UNIX®, X/Open®, OSF/1®, and Motif® are registered trademarks of Open Group.
Citrix®, the Citrix logo, ICA®, Program Neighborhood®, MetaFrame®, WinFrame®, VideoFrame®, MultiWin®, and other names of Citrix products mentioned here are trademarks of Citrix Systems, Inc.
HTML, DHTML, XML, and XHTML are trademarks or registered trademarks of W3C®, World Wide Web Consortium, Massachusetts Institute of Technology.
JAVA® is a registered trademark of Sun Microsystems, Inc.
JAVASCRIPT® is a registered trademark of Sun Microsystems, Inc., used under the license of the technology developed and implemented by Netscape.
MarketSet and Enterprise Buyer are joint trademarks of SAP AG and Commerce One.
SAP, R/3, mySAP, mySAP.com, xApps, xApp, SAP NetWeaver, and other SAP products and services mentioned in the text as well as the corresponding logos are trademarks or registered trademarks of SAP AG in Germany and other countries. All other names of products and services are trademarks of their respective companies.
© SAP UCC 2006 SAP BW Course 3
Course Overview
The purpose of this course is to provide an introduction to the functionalities of SAP Business Information Warehouse. The participants learn the basics of reporting and gain an overview of data modeling and data loading. Not only are the rules for using BW in a UCC environment discussed, but the course also provides suggestions for possible user scenarios of SAP Business Information Warehouse.
Duration: 5 days
Target group: Instructors interested in using SAP BW in their coursesUsers of SAP BW in their courses with little previous knowledge
Dates: June 2006
Prerequisite: Basic Knowledge of Data Warehousing
Release: SAP BW 3.50
Course contents: Rules for using BW in a UCC environmentBasics of data warehousingArchitecture and tools of BWReporting & Web ReportingData ModelingData flow & data extractionAdministrationSuggestions for using SAP BW in the course
This course does not replace participation in follow-up SAP BW courses from SAP.
© SAP UCC 2006 SAP BW Course 4
Europe
© SAP UCC 2006 SAP BW Course 5
Germany
© SAP UCC 2006 SAP BW Course 6
German Soccer Fans
© SAP UCC 2006 SAP BW Course 7
Bavaria
© SAP UCC 2006 SAP BW Course 8
Our SAP UCC at Munich
© SAP UCC 2006 SAP BW Course 9
Selected Chapters
Data Warehousing and SAP BW Basics• 2.1 Introduction to DW• 2.2 System Handling• 2.3 Crash Course Reporting• 2.7 Business ContentBasic Reporting and Data Analysis• 3.1 Query Definition• 3.2 Exception Reporting
Modeling of Data Structures• 4.2 Stars & Galaxies• 4.3 InfoObjects• 4.4 InfoCubesData Staging I: Flat Files• 5.1 Staging Scenarios• 5.2 Master Data Staging• 5.3 Transaction Data Staging• (5.6 Transformations)
Advanced Reporting• 6.1 Geo Maps• 6.2 Web Reporting• 6.3 Data miningData Staging II: mySAP ERP Connections• 7.1 Transaction Data Extraction• 7.2 Delta Extraction
Monday
Tuesday
Wednesday
© SAP UCC 2006 SAP BW Course 10
Course Schedule
Mon. 09:00 a.m. – 04:30 p.m.
Tues. 09:00 a.m. – 04:30 p.m.
Wed. 09:00 a.m. – 04:30 p.m.
© SAP UCC 2006 SAP BW Course 11
• SAPLogonG48
• Client800
• UsersAUSER-3-XXwith XX = 01 to 30
• Initial PasswordINIT
• Please note your new password when you log on for the first time!
Logging On Made Easy
© SAP UCC 2006 SAP BW Course 12
Naming Conventions
Self-defined objects are named according to the pattern AYXX…
• A TU Munich• Y=3 SAP BW course no.• XX Seat no./Team no.
• Example: A303Cube01 or A304Cube01
Guidelines on Using SAP BW
© SAP UCC 2006 SAP BW Course 13
Introduction to Data Warehousing
© SAP UCC 2006 SAP BW Course 14
Google Search Results Over Time
09/2002 03/2003 07/2003 02/2004 07/2004 02/2005 07/2005
“data ware-house”
451,000 574,000 650,000 1,780,000 1,840,000 4,450,000 2,560,000
“data ware-housing”
352,000 443,000 490,000 1,060,000 963,000 2,650,000 4,790,000
“business intelli-gence”
850,000 1,160,000 1,140,000 2,960,000 3,330,000 8,820,000 12,800,000
Source: www.google.de
Number of Search Results
© SAP UCC 2006 SAP BW Course 15
Data Warehouse / Business Intelligence
Wider view of BI
DataProvision
DataAnalysis
Technology Application
Phase
Focus
Analysis oriented view of BI
Closer view of BI
Extraction,Transformation *
DataWarehouse *
Reporting *
Standard *
Ad-hoc *
OLAP *MIS/EIS *Text
Mining
Data Mining * Planning/Consolidation **
Analytical CRM
Performance Measurement Systems/ BSC Systems **
* covered by SAP BW ** covered by SAP SEM Views of Business Intelligence (BI) (Source: Kemper et al. 2004, p. 4)
© SAP UCC 2006 SAP BW Course 16
Definitions for Data Warehouses
1. A data warehouse is a central repositoryfor all or significant parts of the data that an enterprise's various business systems collect.
2. A data warehouse is a copy of transaction data specifically structured for querying and reporting.
3. A collection of data designed to support management decision making. Data warehouses contain a wide variety of data that present a coherent picture of business conditions at a single point in time.
© SAP UCC 2006 SAP BW Course 17
Inmon Definition: Data Warehouse
“A data warehouse is a subject-oriented, integrated, nonvolatile, time-variant collection of data in support of management’s decision.”
(Bill Inmon)
Constant data collection
Organization-wide integration of data
Period reference as a data component
Subject-oriented to organization issues
© SAP UCC 2006 SAP BW Course 18
Considering Inmon’s Definition
subject-oriented Why be limited to customers, suppliers, products, etc.?
integrated Schema integration (metadata) and data integration are indispensable.
time-variant “Snapshot view” of historical data does not account for:- Current data (e.g. shares)- Constant data (master data)
Not necessary
Keep
Time dependency as one possibility of many
nonvolatile If consistency is guaranteed, the ban on updates can be lifted.
Not necessary
collection of data Of course… Keep
in support of management‘s decision
Data warehouses for managers only? Not necessary
A data warehouse is a physical dataset enabling an integrated view of the underlying DataSources.
Zeh, T. (2003). Data Warehousing als Organisationskonzept des Datenmanagements. Eine kritische Betrachtung der Data-Warehouse-Definition von Inmon. Informatik - Forschung und Entwicklung, 18(1), 32-38.
© SAP UCC 2006 SAP BW Course 19
Data Warehouse: Expanded Definition
Creating at Reports
Creating Graphics
Calculating Tables
Analysis Methods
External Data External
Data
Operative Datan
Operative Data
Data Warehouse
Data Collection 1. Oriented by subject 2. Integrated 3. Constant 4. Time referenced D
W in
bro
ad s
ense
DW
in
narr
ower
sen
se
© SAP UCC 2006 SAP BW Course 20
Three-Level DW Concept
Data Staging
Data Storage
Information Analysis
© SAP UCC 2006 SAP BW Course 21
Structure of SAP BW
© SAP AG
© SAP UCC 2006 SAP BW Course 22
Benefit Potential
Technical Benefits• Improved data integration• Decentral data checks no
longer necessary• Fast query handling• Relieves operative
applications• Flexible access options
Business Benefits• Improved information
staging• Early trend recognition• Prompt reaction to
environmental changes• Improvement in customer
satisfaction• Harmonization of
terminology
© SAP UCC 2006 SAP BW Course 23
BW in SAP NetWeaver™
© SAP AG
© SAP UCC 2006 SAP BW Course 24
SAP BW System Handling
© SAP UCC 2006 SAP BW Course 25
Navigating SAP BW
• SAP Easy Access Menu
• Favorites• Transaction Codes
– Find– Enter– Combination with /o
and /n– Activate technical
names
© SAP AG
© SAP UCC 2006 SAP BW Course 26
Help for SAP BW
• Field help (F1)• Input help (F4)• Help for error messages
• SAP Library• Glossary• http://help.sap.com,
SAP NetWeaver™ area• http://service.sap.com/bw
© SAP AG
© SAP UCC 2006 SAP BW Course 27
UCC Guidelines
© SAP UCC 2006 SAP BW Course 28
Crash Course Reporting
© SAP UCC 2006 SAP BW Course 29
SAP BW Tools
AdministratorWorkbench (AWB)System administration
BEx AnalyzerStage andpresent reports
BEx BrowserManage and execute reports,portal function
Most Important Tools:
BEx Query DesignerDefine reports
Web Application DesignerCreate web applications
© SAP UCC 2006 SAP BW Course 30
Business Explorer (BEx)
© SAP AG
© SAP UCC 2006 SAP BW Course 31
Multidimensional Data Structures
© SAP UCC 2006 SAP BW Course 32
Multidimensionality
Distribution Channel
Tim
e
Division
Other dimensions cannotbe displayed:
• Sales org.• Material• Sold-to party
Sales:2 M
Matrix element withkey figure(s)
Dimension/Characteristic
© SAP UCC 2006 SAP BW Course 33
Characteristic or Dimension?
Dimension Lehrstuhl
DimensionVeranstaltung
Note:2,3
Matrixelement mit Kennzahl(en)
510A 510B 510C 510H
394435
577
Entwurf
Makro
SAP
InfoCube mit Dimensionen (klassisch)
Dimension Zeit mit demMerkmal Semester
DimensionVeranstaltung
mit den MerkmalenVeranstaltung und
Lehrstuhl
Note:2,3
Matrixelement mit Kennzahl(en)
SS 01WS
01/02SS 02
WS02/03
394435
577
Entwurf(510H)
Makro(510B)
SAP(510H)
InfoCube mit Merkmalen in Dimensionen (SAP BW)
© SAP UCC 2006 SAP BW Course 34
What Does Multidimensionality Mean?
• Multidimensionality is a main characteristic of data in DWs
• No presentation of data in tables
• As many criteria (dimensions/characteristics) for analyses as you want
• Data descriptions as accurate and detailed as possible
• Often illustrated as a data cube
© SAP UCC 2006 SAP BW Course 35
Analysis Techniques
• To answer users' detailed questions, the multidimensional data model offers various types of operations for manipulating the data cube.
• Mainly, you can change the dimensions and summary levels and can navigate in the data space.
• These options for analysis can be accessed in BEx Analyzer through the shortcut menu in the result area, for example, and can be forwarded to the OLAP processor. The processor interprets the analyses and applies them to the dataset.
© SAP UCC 2006 SAP BW Course 36
Slicing, Dicing & Co.
• Pivoting means turning the data cube• Slicing means filters are set to create a “slice” of data • Dicing means creating a “smaller” data cube by slicing
an interval• Drilldown generally means adding information to a
report• Roll up = opposite of drilldown• Drill across is when the x- and y-axes are switched• Some data warehouse systems provide the option of
reporting on data that is not in the warehouse but is stored only in the OLTP systems. One example of this might be individual accounting documents. This capability is called Drill Through.
Based on http://miss.wu-wien.ac.at/~info1/stud/dw/main.html
© SAP UCC 2006 SAP BW Course 37
Query Areas
© SAP AG
© SAP UCC 2006 SAP BW Course 38
Data Warehouse Lifecycle
© SAP UCC 2006 SAP BW Course 39
The Business Dimensional Lifecycleas Course Structure
time
by R. Kimball, modified
Bus
ine
ss R
equ
irem
ents
D
efin
ition
Pro
ject
Pla
nnin
g
Technical Architecture
Design
Product Selection & Installation
Dimensional Modeling
Physical Design
Data Staging Design &
Development
End-user Application
Specification
End-user Application
Development
Dep
loym
ent
Man
agem
ent
& G
row
th
Rep
lace
men
t
Project Management
technically oriented lessons
management oriented lessons
© SAP UCC 2006 SAP BW Course 40
Project Planning & Management
• Project definition and scoping
• Development of Project Plan
• Parties involved
Bus
ines
s R
equi
rem
ents
D
efin
ition
Technical Architecture Design
Product Selection & Installation
Dimensional Modeling Physical DesignData Staging Design
& Development
End-user Application Specification
End-user Application Development
Dep
loym
ent
Man
agem
ent &
Gro
wth
Rep
lace
men
t
Project Management
Pro
ject
Pla
nnin
g
© SAP UCC 2006 SAP BW Course 41
Business Requirements Definition
• Gathering requirements
• Define terminology
Pro
ject
Pla
nnin
g
Technical Architecture Design
Product Selection & Installation
Dimensional Modeling Physical DesignData Staging Design
& Development
End-user Application Specification
End-user Application Development
Dep
loym
ent
Man
agem
ent &
Gro
wth
Rep
lace
men
t
Project Management
Bus
ines
s R
equi
rem
ents
D
efin
ition
© SAP UCC 2006 SAP BW Course 42
Technical Architecture Design
• Introducing architecture• Back room technical architecture• Architecture for the front room• Infrastructure and metadata
Pro
ject
Pla
nnin
g
Product Selection & Installation
Dimensional Modeling Physical DesignData Staging Design
& Development
End-user Application Specification
End-user Application Development
Dep
loym
ent
Man
agem
ent &
Gro
wth
Rep
lace
men
t
Project Management
Bus
ines
s R
equi
rem
ents
D
efin
ition
Technical Architecture Design
© SAP UCC 2006 SAP BW Course 43
Product Selection & Installation
• Evaluating products• Choosing a product• Features of SAP BW• Installation procedure
Pro
ject
Pla
nnin
g
Dimensional Modeling Physical DesignData Staging Design
& Development
End-user Application Specification
End-user Application Development
Dep
loym
ent
Man
agem
ent &
Gro
wth
Rep
lace
men
t
Project Management
Bus
ines
s R
equi
rem
ents
D
efin
ition
Technical Architecture Design
Product Selection & Installation
© SAP UCC 2006 SAP BW Course 44
Dimensional Modeling
• Designing dimensional models• Semantic, logical and physical data models• Fact table grain• Special fact types (non/semi-additive)• Specialities in modeling
Pro
ject
Pla
nnin
g
Technical Architecture Design
Product Selection & Installation
Physical DesignData Staging Design
& Development
End-user Application Specification
End-user Application Development
Dep
loym
ent
Man
agem
ent &
Gro
wth
Rep
lace
men
t
Project Management
Bus
ines
s R
equi
rem
ents
D
efin
ition
Dimensional Modeling
© SAP UCC 2006 SAP BW Course 45
Physical Design
• Physical structures necessary tosupport logical database design
• Naming standards• Physical file locations• Setting up database environment• Indexing• Partitioning
Pro
ject
Pla
nnin
g
Technical Architecture Design
Product Selection & Installation
Data Staging Design & Development
End-user Application Specification
End-user Application Development
Dep
loym
ent
Man
agem
ent &
Gro
wth
Rep
lace
men
t
Project Management
Bus
ines
s R
equi
rem
ents
D
efin
ition
Dimensional Modeling Physical Design
© SAP UCC 2006 SAP BW Course 46
Data Staging Design and Development
• Extract, transform and load• Data quality• Initial population load• Regular, incremental loads
Pro
ject
Pla
nnin
g
Technical Architecture Design
Product Selection & Installation
End-user Application Specification
End-user Application Development
Dep
loym
ent
Man
agem
ent &
Gro
wth
Rep
lace
men
t
Project Management
Bus
ines
s R
equi
rem
ents
D
efin
ition
Dimensional Modeling Physical DesignData Staging Design
& Development
© SAP UCC 2006 SAP BW Course 47
End-User Application Specification & Development
• Standard vs. user-defined reports
• Geovisualization
• Web Reporting
Pro
ject
Pla
nnin
g
Technical Architecture Design
Product Selection & Installation
End-user Application Specification
End-user Application Development
Dep
loym
ent
Man
agem
ent &
Gro
wth
Rep
lace
men
t
Project Management
Bus
ines
s R
equi
rem
ents
D
efin
ition
Dimensional Modeling Physical DesignData Staging Design
& Development
© SAP UCC 2006 SAP BW Course 48
Deployment, Management & Growth, Replacement
• User support structures• Training measures• Performance metrics• Replacement
considerations
Pro
ject
Pla
nnin
g
Technical Architecture Design
Product Selection & Installation
End-user Application Specification
End-user Application Development
Project Management
Bus
ines
s R
equi
rem
ents
D
efin
ition
Dimensional Modeling Physical DesignData Staging Design
& Development
Dep
loym
ent
Man
agem
ent &
Gro
wth
Rep
lace
men
t
© SAP UCC 2006 SAP BW Course 49
Pro
ject
Pla
nnin
g
Technical Architecture Design
Product Selection & Installation
End-user Application Specification
End-user Application Development
Project Management
Bus
ines
s R
equi
rem
ents
D
efin
ition
Dimensional Modeling Physical DesignData Staging Design
& Development
Dep
loym
ent
Man
agem
ent &
Gro
wth
Rep
lace
men
t
Course Example
Strengths and Weaknesses of Data Warehouse Products
ETL (Flatfiles, R/3), ABAP™
Formulas, Web Reporting, Maps
Extended Star Schema, Snowflaking, Factless Fact Tables, Galaxy
Project Team Role Play
Interviews, Questionnaires
End Users, Work Places, Key Words, Training Concepts
Investment Appraisal,
License Costs
Client Server Architecture,SAP Web AS
© SAP UCC 2006 SAP BW Course 50
Data Warehouse Project Planning
© SAP UCC 2006 SAP BW Course 51
Preparing the Organization
• Find sponsor
• Find technical justification
• Perform a feasibility study
• Relationship between specialized departments and IT
• Understand analytical working methods
© SAP UCC 2006 SAP BW Course 52
Project Scope
• What content should be considered?
• What organizational units are involved?
• Type of data
• Time frame
• Budget
© SAP UCC 2006 SAP BW Course 53
Project Scope
Regions
Fun
ctio
ns
Depar
tmen
ts
© SAP UCC 2006 SAP BW Course 54
Justification
• DW project is not a purpose in itself• Cost-benefit analysis• Measurement of costs?• Measurement of benefits?
© SAP UCC 2006 SAP BW Course 55
Project Team
• Involvement of many organizational units
• Different professional disciplines
• Distribution of roles
• Availability of project team members
© SAP UCC 2006 SAP BW Course 56
Project Plan
• Planning• Controlling• Checking Fans Front Office Coaches Regular Line-Up Special Teams
Project Task Bus
ine
ss E
nd U
sers
Bus
ine
ss S
pons
or
IS S
pons
or
Bus
ine
ss D
river
Bus
ine
ss P
roje
ct L
ead
Pro
ject
Man
ager
Bus
ine
ss S
ys.
Ana
lyst
Dat
a M
odel
er
DW
DB
A
Dat
a S
tagi
ng
De
sig
ner
DW
Ed
ucat
or
E/U
Ap
pl'n
De
velo
per
Tec
h/S
ecur
ity A
rch
itect
Tec
h S
uppo
rt S
pec
ialis
t
Dat
a S
tagi
ng
Pro
gra
mm
er
Dat
a S
tew
ard
DW
QA
An
alys
t
PROJECT MANAGEMENT AND REQUIREMENTS
PROJECT DEFINITION
1 Assess Data Warehousing Readiness 2 Develop Preliminary Project Scope 3 Build Business Justification
PROJECT PLANNING & MANAGEMENT
1 Establish Project Identity 2 Identify Project Resources 3 Prepare Draft Project Plan 4 Conduct Project Team Kick-Off & Planning 5 Revise Project Plan 6 Develop Project Communication Plan 7 Develop Program to Measure Success 8 Develop Process to Manage Scope 9 Ongoing Project Management
USER REQUIREMENT DEFINITION
1 Identify and Prepare Interview Team 2 Select Interviewees 3 Schedule Interviews
© SAP UCC 2006 SAP BW Course 57
OLTP and OLAP Systems
© SAP UCC 2006 SAP BW Course 58
OLTP Systems
Operative Systems
Data Warehouse ...
Reserva-tion
System
OrderProcessing ...
Reserva-tion
System
OrderProcessing
Per-sonnelAdmin.
Per-sonnelAdmin.
Source: based on http://www.educeth.ch/informatik/vortraege/olap/docs/olap.ppt
© SAP UCC 2006 SAP BW Course 59
Differences Between Transaction-Oriented and Analysis-Oriented Systems
Transaction-Oriented SystemsOperative Systems
Analysis-Oriented Systems
Less frequent, complex queries
Large amounts of data per query
Frequent, simple queries
Small amounts of data per query
Quick calculations importantQuick updates important
Executing OLAP queries of operational datasets in parallel could limit the performance of OLTP applications
Operate with current and historical dataOperate mainly with current data
Database system cannot be optimized for OLTP and OLAP applications at the same time
OLTP(Online Transaction Processing)
OLAP(Online Analytical Processing)
Source: based on http://www.educeth.ch/informatik/vortraege/olap/docs/olap.ppt
© SAP UCC 2006 SAP BW Course 60
OLTP vs. OLAP
OLTP OLAP
Target Efficiency through automation Competitive advantages through knowledge generation
Data Content Application-oriented, function-oriented
Subject-oriented
Type of Data Transaction data Aggregated data
Age of Data Current, up-to-date: 30-60 days Historical (often 8-10 years old), current, future
Data Volume Low Comprehensive
Main Functionality Frequent changes Time-dependent reports
Data Integration Minimal integration with other applications
Integrated data from many applications
State-of-the-Art for Database Systems
Relational databases Relational and multidimensional databases
Data Model Normalized (often 3rd normal form) Denormalized data model
Semantic Modeling Method
Entity Relationship Model Multidimensional ERM:
Permitted Operations on the Dataset
Insert, update, delete, read Read
© SAP UCC 2006 SAP BW Course 61
Multidimensionality
© SAP UCC 2006 SAP BW Course 62
Data Warehouse Products
© SAP UCC 2006 SAP BW Course 63
DW Solutions and Providers
http://www.barc.de
Manufacturer Product Version
Ascential DataStage 6.0
Business Objects Data Integrator 6.0
Cognos DecisionStream 7.1
Hummingbird ETL 5
IBM DB2 Warehouse Manager 8.1
Informatica PowerCenter 6
Microsoft SQL Server 2000
MicroStrategy 7i 7i
NCR Teradata V2 R5.0
Oracle 9i 9i R2
Sagent Solution 4.5
Sand Analytic Server 3.0
SAP Business Information Warehouse 3.1 C
SAS System 8
Sybase IQ 12.4.3
© SAP UCC 2006 SAP BW Course 64
OLAP Providers and Products
1. Hyperion Solutions (Essbase, Wired)
2. Oracle (Express)
3. Cognos (PowerPlay)
4. MicroStrategy (MicroStrategy)
5. Microsoft (OLAP server)
6. Business Objects(Business Objects)
* Source: The OLAP Report (www.olapreport.com)
The six OLAP providers with the largest market share in 1999*:
Other OLAP servers:
• IBM (DB2 OLAP Server)
• Applix (iTM1)
• ...
Other OLAP frontends:
• Temtec (Executive Viewer)
• ...
Other OLAP providers:
• Brio Technology
• Pilot Software
• SAS Institute
• ...
© SAP UCC 2006 SAP BW Course 65
What's Being Said About SAP BW
• Especially suited for analyzing and presenting data stored in a DW
• Good tools for creating individual applications (BEx Analyzer, Web Reporting)
• Predefined information models (Business Content)
• Theoretically not dependent on R/3
• The structures are based in part on R/3 business processes
• Business Content is oriented toward R/3 structures
• Optimized performance in coordination with R/3 (special extractors, and so on)
© SAP UCC 2006 SAP BW Course 66
Business Content
© SAP UCC 2006 SAP BW Course 67
Why Have Preconfigured Information Models?
• Modeling data models to specific requirements is a tedious and sometimes highly complex task.
• The time and effort needed are even greater the more individual the requirements are and the less the developers can access and refer to existing templates.
• Organizations often model the same subjects.
© SAP UCC 2006 SAP BW Course 68
Contents of Business Content
© SAP AG
© SAP AG, Marianne Kollmann, Product Management BI
© SAP UCC 2006 SAP BW Course 69
Contents of Business Content
© SAP AG
© SAP AG, Marianne Kollmann, Product Management BI
© SAP UCC 2006 SAP BW Course 70
Definition of Business Content
• Business Content is a comprehensively prefabricated information model for analyzing business processes.
• Components of these models include:– Extractors in SAP R/3– Elements of the data model (such as key figures,
characteristics, InfoCubes, and ODS objects)– Components for the data loading process (such as
InfoSources and update rules)– Reporting components (such as queries, web
templates, and workbooks)– Basic components (such as roles and currency
conversion types)
© SAP UCC 2006 SAP BW Course 71
Number of SAP BW Business Content Objects
BI Content 3.2 Add-On
InfoObjects 11,772 ODS objects 349 InfoCubes 605 MultiCubes 121 Roles 861 Queries 3,299 Workbooks 1,979
© SAP UCC 2006 SAP BW Course 72
Working with Business Content
BusinessContent
Usewithout
adjustments
Refiningor
Coarsening
Template foryour own
Business Content
© SAP UCC 2006 SAP BW Course 73
Business Content Versions
• In BW, there are three different object versions of Business Content:– D version: SAP delivery version– A version: active version– M version: modified version
• To work with Business Content objects, you first have to convert them into active versions (A versions).
© SAP UCC 2006 SAP BW Course 74
Searching for the Right Business Content
1. Business Content can be searched in the Metadata Repository.
2. The Metadata Repository is integrated into AWB.
Questions:
• What is metadata?
• What is AWB?
• What is the Metadata Repository?
© SAP UCC 2006 SAP BW Course 75
SAP BW Tools
AdministratorWorkbench (AWB)Systemadministration
BEx AnalyzerStage and present reports
BEx BrowserManage andexecute reports,portal function
Most Important Tools:
BEx Query DesignerDefine reports
Web Application DesignerCreate web applications
© SAP UCC 2006 SAP BW Course 76
Administrator Workbench
© SAP AG
© SAP UCC 2006 SAP BW Course 77
What is Metadata?
• Metadata is information on the data structures and their relationships, “data about data”
© SAP UCC 2006 SAP BW Course 78
Technical and Specialist Metadata
• Technical Metadata contains information about the data warehouse required by DW administrators and designers to develop and operate the data warehouse. This includes data such as database fields, columns, tables, and the memory needs of the database, data models, and mappings.
• Specialist Metadata contains the information that gives a specialized user a business overview of the data warehouse. This includes data such as mappings, report details, specialist terms, and so on. Specialist metadata assigns data from the DW to the multidimensional business model and to the frontend tool of the end user and usually contains descriptions and hierarchies that are internal to the organization.
© SAP UCC 2006 SAP BW Course 79
Meta Database System
• Help system for users
• BW Metadata Repository: central management of all metadata
• BW Metadata Repository Browser: convenient access to all metadata
© SAP UCC 2006 SAP BW Course 80
Common Warehouse Metamodel (CWM™)
“The CWM™ is a specification that describes metadata interchange among data warehousing, business intelligence, knowledge management and portal technologies.”
From: www.omg.org/cwm
• Object Management Group (OMG)http://www.omg.org
• Common Warehouse Metamodelhttp://www.omg.org/cwm– Specification– Articles and links
© SAP UCC 2006 SAP BW Course 81
Query Definition
© SAP UCC 2006 SAP BW Course 82
InfoProviderQuerydefinition liefertDaten 0,n1,1
Arbeitsmappe(xls-Datei)
einge-betteteQuery
0,n0,m
alsView
speich-ern
View
MetaObjects: Query
© SAP UCC 2006 SAP BW Course 83
InfoProvider as Basis for a Report I
InfoCube ODS Characteristic with Master Data InfoSet Virtual Cube MultiProvider
InfoCube ODS Characteristic with Master Data
InfoProvider DataTargets
Reporting
Loading Data
© SAP UCC 2006 SAP BW Course 84
InfoProvider as Basis for a Report II
© SAP AG
No
Dat
a
Wit
h D
ata
Master Data
Basic InfoCube
MultiProvider
InfoSet
Info
Pro
vid
er Interface
ODS Object
OLAP Engine
Business
Explorer
Virtual InfoCube
© SAP UCC 2006 SAP BW Course 85
BEx Toolbar
© SAP AG
© SAP UCC 2006 SAP BW Course 86
Query Designer Toolbar
© SAP AG
© SAP UCC 2006 SAP BW Course 87
Defining Queries Using Drag & Drop
© SAP AG
© SAP UCC 2006 SAP BW Course 88
Defining a Formula
© SAP AG
© SAP UCC 2006 SAP BW Course 89
Some Important Elements of a Query Definition
• Insert characteristics• Insert key figures• Free characteristics• Filter characteristics• Properties of
characteristics• Formula key figures
© SAP AG
© SAP UCC 2006 SAP BW Course 90
Summary: Query Definition Procedure
To define queries, you:
1. Select an InfoProvider that the query is being defined for2. Select reusable structures that already contain combinations of characteristics or key figures (such as
a contribution margin scheme)3. Select characteristics from the InfoProvider4. Limit the selected characteristics to characteristic values, characteristic intervals, or hierarchy nodes5. Use variables for characteristic values, hierarchies, hierarchy nodes, formulas, and texts, and define
new variables if necessary6. Select key figures from the InfoProvider7. Formulate calculated key figures8. Limit the key figures by combining characteristics9. Define exception cells10. Arrange the characteristics and key figures in rows or columns to determine a starting view
for the query analysis
The steps not in bold print are optional.
You can save the query in your Favorites or in your role. You can then analyze the query data inBusiness Explorer. You can• Display the query with a click in the web in a standard view• Use the query as a data provider for web items and analyze the query data in a separately designed
web application OR• Place the query in a workbook and analyze it in BEx Analyzer (MS Excel-based)
Source: SAP BW Functions in Detail, Version 1.0
© SAP UCC 2006 SAP BW Course 91
Exception Reporting
© SAP UCC 2006 SAP BW Course 92
Exception Reporting: Process
© SAP AG
© SAP UCC 2006 SAP BW Course 93
Step by Step
1. Define the exception
2. Output: highlighted in color in the query worksheet
3. Define Reporting Agent settings
4. Schedule
5. Output: alert Monitor and messages
© SAP UCC 2006 SAP BW Course 94
Semantic Data Modeling
© SAP UCC 2006 SAP BW Course 95
ARIS Model
Source: Scheer, Wirtschaftsinformatik [Business Information Management]
© SAP UCC 2006 SAP BW Course 96
OLTP vs. OLAP
Data Modeling Methods for Transaction-Oriented Databases (OLTP)
• Semantic level: ERM• Logical level: relations model• Physical level: description of
relational database systems
Data Modeling Methods for Data Warehouses (OLAP)
?
© SAP UCC 2006 SAP BW Course 97
Selected Design Methods
Entwurfsebene Entwurfsmethoden Konzeptueller (semantischer) Entwurf
Semantisches Data Warehouse Modell Multidimensionales ERM Dimensional Fact Modeling Application Design for Analytical Processing Technologies
Logischer Entwurf Starschema Erweitertes SAP-Starschema Fact/Constellation Schema Galaxy Schema Snowflake Schema Partial Snowflake Schema
Physischer Entwurf Speicherungsstrukturen Zugriffsmechanismen Datenbanktuning usw.
© SAP UCC 2006 SAP BW Course 98
Multidimensional ERM (MERM)
• Derived from ERM
• New: fact relationship, dimension field, hierarchical relationship
• Principle of minimalism
• So there are only five Meta Objects:
Name
Central Fact Relationship
Name
Dimension Field
Name
Variable or Attribute
Hierarchical Relationship Relationship
© SAP UCC 2006 SAP BW Course 99
From ERM to MDM
Mapping transaction structuresas analytical structures
© SAP UCC 2006 SAP BW Course 100
Three-Step Method
Step Activity Description 1 Identify business processes Split ERM into one or more business processes
2 Generate fact relationship n-m-relationships between strong entities
provide the fact relationship, numerical attributes are candidates for key figures
3 Form dimensions Remaining entities are summarized intogroups that are strongly dominated by other entities
© SAP UCC 2006 SAP BW Course 101
Overlapping Entity: Example
Customer
Material Sales Person
Material group Sales Department
Customer noCustomer nameCityRegion
Material noMaterial nameMaterial type color price
Material group noMaterial group name....
Sales TransactionDateCustomer noMaterial noSales pers noAmountQuantityCurrency
Sales pers. noSales pers. name.......
Sales dep. noSales dep. location.......
© SAP AG
© SAP UCC 2006 SAP BW Course 102
Forming Dimensions
Sales Rep ID
LastNameSalesDep
Material ID
Material NameMaterial TypeMaterial Group
Customer ID
Customer NameCityRegionOffice Name
Time Code ID
YearFiscal YearQuaterMounthDay of the Week
Material IDSales Rep IDTime Code IDCustomer IDSales AmountQuantityUnit Price
Time DimensionCustomer Dimension
Sales Org DimensionMaterial Dimension
FACT??
Customer
City
Region
Material Group
Sales order
Price
Sales Person
Sales Dept.
Sales Dept. Loc.
Material
Material TypeColor
© SAP AG
© SAP UCC 2006 SAP BW Course 103
Granularity
• = Details of a data structure
• High granularity: data is described by many characteristics
• Low granularity: data is described by few characteristics
• Positive effect on options in the query
• Negative effects on performance of requests and load time
© SAP UCC 2006 SAP BW Course 104
Granulartity
© SAP UCC 2006 SAP BW Course 105
Logical Data Modeling
© SAP UCC 2006 SAP BW Course 106
Selected Design Methods
Entwurfsebene Entwurfsmethoden Konzeptueller (semantischer) Entwurf
Semantisches Data Warehouse Modell Multidimensionales ERM Dimensional Fact Modeling Application Design for Analytical Processing Technologies
Logischer Entwurf Starschema Erweitertes SAP-Starschema Fact/Constellation Schema Galaxy Schema Snowflake Schema Partial Snowflake Schema
Physischer Entwurf Speicherungsstrukturen Zugriffsmechanismen Datenbanktuning usw.
© SAP UCC 2006 SAP BW Course 107
Physical Conversion in the Data Warehouse System
Physical Multidimensional Data Warehouse Systems
• Database and storage structures are multidimensional
• There is no recognized standard yet
• Large datasets are problematic• Examples: Express (Oracle),
Holos (Seagate), Essbase (Applix)
Physical Relational Data Warehouse Systems
• Data classified in fact tables and dimension tables
• Connected by keys• Example: SAP BW
© SAP UCC 2006 SAP BW Course 108
Classic Star Schema
• Very effective requests can be made in the Star Schema
• It is very easy to understand
• Flexibility?
© SAP UCC 2006 SAP BW Course 109
Star Schema
Kennzahlen
Faktentabelle
Dimensions-attribute
Dimension 2
Dimensions-attribute
Dimension 1
Dimensions-attribute
Dimension 3
Dimensions-attribute
Dimension 4
© SAP UCC 2006 SAP BW Course 110
Problems with the Classic Star Schema
• No support for multiple languages
• Alphanumeric foreign keys
• No support for time-dependent master data
• Hierarchy relationships have to be modeled as attributes of a dimension table
© SAP UCC 2006 SAP BW Course 111
SAP's Expanded Star Schema
• Fact table is unchanged • Dimension characteristics are separated into segments– Attributes– Texts– Hierarchies
• Attributes and texts can be defined time-dependently
• Segments are optional and need not be created
• Introduction of SID
© SAP UCC 2006 SAP BW Course 112
• Solution-Dependent Data:Fact Tables and Dimension Tables
Solution-Dependent and -Independent Data
• Solution-Independent Data:Characteristics
G e b ie t 1 G e b ie t 2 G e b ie t 3
B e z irk 1
G e b ie t 3 a
B e z irk 2
R e g io n 1
G e b ie t 4 G e b ie t 5
B e z irk 3
R e g io n 2
G e b ie t 6
B e z irk 4
G e b ie t 7 G e b ie t 8
B e z irk 5
R e g io n 3
V e rtr ie b s o rg a n is a t io n
M a t e r i a l G r o u p
M a t e r i a l H i e r a r c h y T a b l e
M a t e r i a l N u m b e rL a n g u a g e C o d e
M a t e r i a l N u m b e rL a n g u a g e C o d e
M a t e r i a l N a m e
M a t e r i a l T e x t T a b l eM a t e r i a l _ D i m e n s i o n _ I D
M a t e r i a l N u m b e r
M a t e r i a l D i m e n s i o n T a b l e
M a t e r i a l M a s t e r T a b l e
M a t e r i a l N u m b e rM a t e r i a l N u m b e r
M a t e r i a l T y p e
M a t e r i a lM a t e r i a l D i m e n s i o n D i m e n s i o n
© SAP AG
© SAP UCC 2006 SAP BW Course 113
Surrogate ID (SID)
• Artificial primary key
• 4 byte whole number
• Technical link between InfoCube and characteristic
• Technical link between characteristic and corresponding attribute, text, and hierarchy tables
• Technical key instead of production key
© SAP UCC 2006 SAP BW Course 114
SID Tables
Text
SID Tables
Master
Hierarchies
Hierarchies
Master
SID Tables
Text
Hierarchies
Master
SID Tables
Text
Hierarchies
Master
SID Tables
Text
Hierarchies
Master
SID Tables
Text
Hierarchies
Master
SID Tables
Text
Text
SID Tables
Master
Hierarchies
Text
SID Tables
Master
Hierarchies
Text
SID Tables
Master
Hierarchies
DimensionTable
Text
SID Tables
Master
Hierarchies
DimensionTable
DimensionTable
DimensionTable
DimensionTable
Hierarchies
Master
SID Tables
Text
FACT
© SAP AG
© SAP UCC 2006 SAP BW Course 115
SID Tables
SID Tables andInfoCube Access
(1) Fact Table(1) Fact Table
(2) Dimension Tables(2) Dimension Tables
(3) time-independent-SID(3) time-independent-SID(4)(4) time-dependent-SIDtime-dependent-SID(5) ‘traditional‘ SID (5) ‘traditional‘ SID
11
22
22
22
22 3 3
55
4 4
3 3
5555
55
55
55
55
55
55
3 3 3 3
55
55
5555
4 4
3 3
55
55
55
55
© SAP AG
© SAP UCC 2006 SAP BW Course 116
Working with InfoObjects
© SAP UCC 2006 SAP BW Course 117
InfoObjects
• e.g. customer, product
InfoObject: Key Figure• e.g. sales, costs• numerical and
additive if possible
InfoObject: Characteristic
© SAP UCC 2006 SAP BW Course 118
Kennzahlen
Faktentabelle
Dimensions-attribute
Dimension 2
Dimensions-attribute
Dimension 1
Dimensions-attribute
Dimension 3
Dimensions-attribute
Dimension 4
From Star Schema to InfoObject
TextsAttributes
Hierarchies
• Every field of a dimension becomes a characteristic
– Exception because of expanded Star Schema: texts, attributes, hierarchies are placed in their own segments
• Each key figure of the fact table becomes a key figure
© SAP UCC 2006 SAP BW Course 119
Important Properties of Characteristics
• Name• Data type• Length• Master data
– Texts– Attributes– Hierarchies
© SAP AG
© SAP UCC 2006 SAP BW Course 120
Key Figures: Data Types
From: http://www.dpunkt.de/leseproben/3-89864-179-1/Kapitel_6.pdf
© SAP UCC 2006 SAP BW Course 121
Characteristics: Data Types
From: http://www.dpunkt.de/leseproben/3-89864-179-1/Kapitel_6.pdf
© SAP UCC 2006 SAP BW Course 122
Texts and Attributes: Fields
Texts• Short: 0TXTSH• Medium: 0TXTMD• Long: 0TXTLN
Attributes• Each attribute of
a characteristic InfoObject is an InfoObject itself (characteristic or key figure)
© SAP UCC 2006 SAP BW Course 123
Process Flow for InfoObject Creation
1. Create InfoObject
2. Check: syntax formula of the InfoObject checked
3. Save: definition saved
4. Activate: database tables generated
© SAP UCC 2006 SAP BW Course 124
Working with InfoCubes
© SAP UCC 2006 SAP BW Course 125
InfoCubes
• Central data store in SAP BW
• Compiled from characteristics and key figures
• 233 key figures max.
• Approx. 3,224 characteristics possible
© SAP UCC 2006 SAP BW Course 126
MetaObjects: InfoProvider
InfoProviderQuerydefinition liefertDaten 0,n1,1
Arbeitsmappe(xls-Datei)
einge-betteteQuery
0,n0,m
alsView
speich-ern
View
© SAP UCC 2006 SAP BW Course 127
InfoCube Structure
Dimension Lehrstuhl
DimensionVeranstaltung
Dim
ensio
n St
uden
t
Note:2,3
Matrixelement mit Kennzahl(en)
510A 510B 510C 510H
394435
577
Entwurf
Makro
SAP
InfoCube mit Dimensionen (klassisch)
Dimension Zeit mit demMerkmal Semester
DimensionVeranstaltung
mit den MerkmalenVeranstaltung und
Lehrstuhl
Dim
ensio
n St
uden
t
mit
dem
Mer
kmal
Stu
dent
Note:2,3
Matrixelement mit Kennzahl(en)
SS 01WS
01/02SS 02
WS02/03
394435
577
Entwurf(510H)
Makro(510B)
SAP(510H)
InfoCube mit Merkmalen in Dimensionen (SAP BW)
© SAP UCC 2006 SAP BW Course 128
InfoCube Step-by-Step
1. Create InfoCube
2. Add key figures
3. Add characteristics
4. Create dimensions
5. Sort characteristics into dimensions
6. Check, save, activate
© SAP UCC 2006 SAP BW Course 129
Line Item and High Cardinality
Line Item:Very few characteristic values of the InfoObject e.g. order numberin an order (detail) cube No dimension table, InfoObject integrated directly into the InfoCube
High Cardinality:Many entries in this dimension (min. 20% of the number of data records of the fact table) Different indexing
© SAP AG
© SAP UCC 2006 SAP BW Course 130
What Can Be Documented?
© SAP AG
© SAP UCC 2006 SAP BW Course 131
Documentation
• Possible Formats– Text (.TXT) – HTML – MS Word (.DOC) – MS Power Point (.PPT) – MS Excel (.XLS) – GIF – JPG
© SAP UCC 2006 SAP BW Course 132
Staging Scenarios
© SAP UCC 2006 SAP BW Course 133
Staging Scenarios
• Staging scenarios with transient data store
• Data is always collected anew and only kept in the BW system for the duration of a given transaction.
• Staging scenarios with persistent data store
• Data loaded from the source system into the SAP BW system is stored even after a transaction has been concluded.
© SAP UCC 2006 SAP BW Course 134
Staging Scenarios: Overview
Transient Data Store
Persistent Data Store
InfoCube/ODS RemoteCube
Source System RemoteCube
Source System PSA InfoCube ODS InfoCube
Source System PSA ODS
InfoCube InfoCube
InfoCube Source System PSA ODS
Staging Scenarios
© SAP UCC 2006 SAP BW Course 135
Transient Staging Scenarios with RemoteCubes
© SAP AG
© SAP UCC 2006 SAP BW Course 136
Persistent Staging Scenario
SourceSystem
PSA
InfoCube
InfoObjects(Characteristics)
© SAP UCC 2006 SAP BW Course 137
Flatfiles as Source System
• Source systems are all systems that stage data for SAP Business Information Warehouse (BW). These include:– SAP Systems (Release 3.0D and higher)– SAP Business Information Warehouse systems– Flatfiles, in which the metadata is maintained
manually and the data is transferred using a data interface to the SAP BW system
– A database system, in which data is loaded from an SAP-supported database without the assistance of an external extraction program
– External systems in which data and metadata is transferred using staging BAPIs
From: BW online documentation
© SAP UCC 2006 SAP BW Course 138
Flexible Master Data Staging
Flexible Master Data Staging
© SAP UCC 2006 SAP BW Course 139
Data in SAP BW
Data in BW
Metadata Application Data
Specialist Metadata
Technical Metadata
Transaction- Data Master Data
Attributes Texts Hierarchies
© SAP UCC 2006 SAP BW Course 140
Hints on Loading from Flatfiles
• Do not use titles if possible.Headers may be ignored during the loading process.
• The order of the fields in the file must match the order of the InfoObjects in the transfer structure.
• Date: YYYYMMDDTime: hhmmss
© SAP UCC 2006 SAP BW Course 141
Structure of Attribute Flatfiles
/BIC/<ZYYYYY> Key of the compounded characteristic (if characteristic is available)
/BIC/<ZXXXXX> Characteristic key
DATETO CHAR 8 Valid-to date (only with time-dependent master data)
DATEFROM CHAR 8 Valid-from date (only with time-dependent master data)
Attribute 1
Attribute …
© SAP UCC 2006 SAP BW Course 142
Structure of Attribute Flatfiles
Key Compound-ing
Datefrom
Dateto
Attribute 1
Attribute 2
...
optional optional optional
Fields relevant for case study
© SAP UCC 2006 SAP BW Course 143
Structure of Text Flatfiles
LANGU CHAR 1 Language key (D for German, E for English)
/BIC/<ZYYYYY> Key of the compounded characteristic (if characteristic is available)
/BIC/<ZXXXXX> Characteristic key
DATETO CHAR 8 Valid-to date (only with time-dependent master data)
DATEFROM CHAR 8 Valid-from date (only with time-dependent master data)
TXTSH CHAR 20 Short text
TXTMD CHAR 40 Medium text
TXTLG CHAR 60 Long text
© SAP UCC 2006 SAP BW Course 144
Structure of Text Flatfiles
Key Comp-ounding
Datefrom
Dateto
Shorttext
optional optional optional
Med. text
Longtext
Lang-uage
Fields relevant for case study
© SAP UCC 2006 SAP BW Course 145
Update Types
Flexible Updating• Transaction data• Master data
= with update rules
(= transaction data-InfoSources in BW-Release 2.X)
Direct Updating• Master data only
= without update rules
(= master data-InfoSources in BW-Release 2.X)
Easier, therefore preferable if update rules require no transformations
© SAP UCC 2006 SAP BW Course 146
Data Flow for Flexible Updating
© SAP
© SAP UCC 2006 SAP BW Course 147
Update Rules
• Update rules specify how data (key figures, time characteristics, characteristics) are updated from an InfoSource communication structure to the data targets.
• They combine an InfoSource with an InfoCube, characteristic or ODS object.
• For InfoCubes, there are two ways of defining the update rule for a key figure: no update or addition, minimum or maximum. Characteristics can also be looked up in external tables such as a master data table.
© SAP UCC 2006 SAP BW Course 148
Loading Master Data Step by Step
1. Enter characteristic as data target
2. Define InfoSource for master data
3. Assign source system and DataSource(s)
4. Maintain transfer structure and transfer rules
5. Create update rule
6. Create and schedule InfoPackage
© SAP UCC 2006 SAP BW Course 149
Define InfoSource
• An InfoSource describes the amount of all available data for a business process or a type of business process. An InfoSource is a unit of logically associated information, that is of InfoObjects and, when transfer rules are applied, can refer to data from one or more DataSources. The structure of an InfoSource is called the commu-nication structure. In contrast to the DataSource transfer structure, it is independent of the source system.
© SAP UCC 2006 SAP BW Course 150
Assign DataSource(s)
• Logically associated data are found in the source system in the form of DataSources. DataSources are also source system-referenced. They comprise many fields, which are offered for the data transfer to BW in a flat structure (extract structure). Data is transferred from the source system to BW in the form of a selection of fields of the extract, transfer structure.
© SAP UCC 2006 SAP BW Course 151
Transfer Rules
• Transfer rules determine how and which fields in the source system-dependent transfer structure are transferred to which fields in the source system-independent communication structure. Detailed transformation rules can be generated for this purpose.
© SAP UCC 2006 SAP BW Course 152
Transfer Rules
TransferRules
Write field in field Assign constantvalue
ABAP routine
Formula
© SAP AG
© SAP UCC 2006 SAP BW Course 153
Data Flow
1
2
3 4 5
© SAP AG
6 7
© SAP UCC 2006 SAP BW Course 154
Create and Schedule InfoPackage
• Data request
• Includes diverse parameters for the upload
• Can be planned and scheduled by job administration
© SAP UCC 2006 SAP BW Course 155
Monitor
• Monitor is the monitoring tool in Administrator Workbench.
• Use Monitor to supervise data requests and data processing in Administrator Workbench. The status of the data processing is
displayed on the different levels of the detailed display.
© SAP AG
© SAP UCC 2006 SAP BW Course 156
PSA
• The Persistent Staging Area (PSA) is the initial storage area of SAP BW for requested data from different source systems. The requested data is stored unchanged in the form of the transfer structure in transparent, relational database tables, and so may have errors if it had errors on the source system. Logical data packages (requests) can now be checked for quality and meaningfulness, order and completeness.
© SAP AG
© SAP UCC 2006 SAP BW Course 157
Loading Transaction Data
© SAP UCC 2006 SAP BW Course 158
Data in SAP BW
Data in BW
Metadata Application Data
Specialist Metadata
Technical Metadata
Transaction- Data Master Data
Attributes Texts Hierarchies
© SAP UCC 2006 SAP BW Course 159
Structure of Transaction Data Flatfiles
Char. 1
Char. 2
Char. n...
Key fig. 1
Key fig. 2
Key fig. n...
Characteristics Key Figures
• Maintain a consistent order• Do not use titles if possible• Give dates in the YYYYMMDD format
© SAP UCC 2006 SAP BW Course 160
Update Rules
• Update rules specify how data (key figures, time characteristics, characteristics) are updated from an InfoSource communication structure to the InfoCubes.
• They combine an InfoSource with an InfoCube, characteristic or ODS object.
• For InfoCubes, there are two ways of defining the update rule for a key figure: no update or addition, minimum or maximum. Characteristics can also be looked up in external tables such as a master data table.
© SAP UCC 2006 SAP BW Course 161
Loading Transaction Data Step by Step
1. Define InfoSource for the transaction data (flexible update)
2. Assign DataSource(s)
3. Maintain transfer structure and transfer rules
4. Maintain update rules
5. Create and schedule InfoPackage
© SAP UCC 2006 SAP BW Course 162
Copying InfoCubes
© SAP UCC 2006 SAP BW Course 163
Copying Cube Structure
Copying Data
Cube Copy: Concept
Cube A
Export DataSource
InfoSource Update Rule
Cube B
© SAP UCC 2006 SAP BW Course 164
Export DataSources
Export DataSources are needed to transfer data from a source BW to a target BW.
The selected InfoProvider is available for you to use as an InfoSource for another system. The corresponding export DataSource is not displayed in the InfoSource tree of the source BW.
The metadata of an export DataSource is generated as it exists in the source BW. This also includes the procedure for non-SAP systems.
Procedure:See document BW_Richtlinie03_Kopieren.doc
(BW_Guidelines03_Copying.doc)
The technical name of the export DataSource consists of the number 8 and the name of the data target. Example:
InfoCube: AYXX_EKFExport InfoSource: 8AYXX_EKF
Source: http://help.sap.com/saphelp_bw31/helpdata/de/ad/6b023b6069d22ee10000000a11402f/frameset.htm
© SAP UCC 2006 SAP BW Course 165
InfoSpokes and Open Hub Service
© SAP UCC 2006 SAP BW Course 166
Open Hub Service
Open Hub Service makes it possible to distribute data from an SAP BW system to non-SAP data marts, analytical applications, and other applications. This guarantees a controlled distribution across several systems. The central object for exporting data is the InfoSpoke. The InfoSpoke is used to define what data should be taken from which object, and to which target that data should be forwarded.
Source: http://help.sap.com/saphelp_bw31/helpdata/DE/a8/6b023b6069d22ee10000000a11402f/frameset.htm
© SAP UCC 2006 SAP BW Course 167
Transformations During Data Load
© SAP UCC 2006 SAP BW Course 168
Transformations in Data Flow
Communication Structure
DataSource DataSource
InfoSource Communication Structure
InfoSource
DataSource DataSource DataSource DataSource
Application - Spec.
Extractor: FI Application -
Spec. Extractor: CO
Generic Extractor
From Table
Update Rules
T ransfer Rules Homogenization: transforms
data data into structured and einheitliches uniform format
Integration of data in application-specific models
© SAP UCC 2006 SAP BW Course 169
Transformations in Transfer Rules
field 1:1 (no transformation) formula
constant ABAP routine
© SAP UCC 2006 SAP BW Course 170
Formula
© SAP UCC 2006 SAP BW Course 171
ABAP Routine
© SAP UCC 2006 SAP BW Course 172
Geovisualization
© SAP UCC 2006 SAP BW Course 173
Pictures Say More......
© SAP UCC 2006 SAP BW Course 174
... Than a Thousand Words
© SAP UCC 2006 SAP BW Course 175
Geo-Characteristics
• Many of the BW characteristics, such as customer, sales region, state or country, also have geographical significance.
• You can evaluate geographic information together with the business-relevant key figures in BEx Map.
• BEx Map is the geographical information system (GIS) of BW that is integrated in Business Explorer (BEx).
© SAP UCC 2006 SAP BW Course 176
Creating Maps Step by Step
1. Identify characteristic as geographically relevant
2. Load geographic data into BW
3. Insert BEx Map into the query
© SAP UCC 2006 SAP BW Course 177
Step 1: Identifying the Geo-Characteristic
• First, you need to identify the geo-relevant characteristics (such as region) as geo-characteristics in InfoObject maintenance.
© SAP UCC 2006 SAP BW Course 178
Static and Dynamic Geo-Characteristics
• Static Geo-CharacteristicA static geo-characteristic is a characteristic that describes a surface (polygon) and whose geographic coordinates do not change often. Countries or regions are examples of static geo-characteristics.
• Dynamic Geo-CharacteristicA dynamic geo-characteristic is a characteristic that describes a place (point-like information) whose geographic coordinates could change frequently. Customers or plants are examples of dynamic geo-characteristics, since they are located at a geographic “point” that can be described by an address, and the address data of these characteristics may change frequently.
© SAP UCC 2006 SAP BW Course 179
Step 2: Loading Geographic Data into BW
• This will load the maps available as shape files into the BW system and assign them to the respective characteristic.
• A shape file is a standard file that is commonly used to describe geographic data and which is used in many geographical information systems. Detailed shape files also may contain demographic information about social structure, age structure, and so on, but may be very expensive. However, simple shape files are available on the internet and can often be downloaded free of charge. A simple shape file containing the structure of the German states will be used in this course.
© SAP UCC 2006 SAP BW Course 180
Step 2: Loading Geographic Data into BW
1. Download “geo-data”: Downloads the master data of the characteristic. Important: SAPBWKey
2. Open the DBF file of geo-data and enter the SAPBWKey
3. Upload modified shape files
© SAP UCC 2006 SAP BW Course 181
Shape File Structure
• The map on which you can display static geo-characteristics is provided as a shape file.
• The shape file consists of three files in different formats that belong together: *.shp contains the actual geo-data that forms the map *.shx contains an index, which improves access time to the map *.dbf contains the attributes for individual geographic items such as
countries or regions • You copy the SAPBWKEY from the geo-data file for your InfoObject into
the dbf file within the shape file
Master Data OREGION
010203...
BavariaBremenHamburg...
Region: *.dbf
...
...
...
...
BerlinHamburgBavaria...
050301...
© SAP UCC 2006 SAP BW Course 182
From Shape File to Map
© SAP UCC 2006 SAP BW Course 183
Step 3: BEx Map
• Finally, define a query with geo-characteristics and insert it into a workbook. After you attach a map, it displays query data of geographical relevance. You can navigate through the map to further evaluate geo-relevant data.
© SAP UCC 2006 SAP BW Course 184
Web Reporting
© SAP UCC 2006 SAP BW Course 185
Advantages of Web Reporting
• Constant availability and access
• Access to information on intranet and internet
• Dispenses with complex software installations
• Intuitive operation
• Many users have experience with web browsers
• Robust navigation in web browsers
© SAP UCC 2006 SAP BW Course 186
Approaches for Web Reporting
1. Offline Approach– Querying the report data periodically– Storing the data on the web server as static HTML documents SAP BW: Reporting Agent
2. Dynamic Generation– Webpages are generated at the request of users SAP BW: Embeds items in web applications
3. Applets– Java or ActiveX Applets allow you to program and generate more
sophisticated interfaces SAP BW: JavaScript
© SAP UCC 2006 SAP BW Course 187
Web Application Server Architecture
Web Browser
HTTP
ITS Web Serv.
ITS
• Mainly used for web-enabling of existing SAP applications
• Dynpro-based
• SAP BW used ITS only as a gateway (WEBRFC)
• ITS Flow Logic was used only in special cases
mySAP WAS
• Enhanced scalability, performance, and robustness
• Generation of charts and maps on Internet Graphic Server (IGS)
• Supports background processing
• BEx Mobile Intelligence
• Easy administration
SAP BW 3.0 with mySAP Web
AS technology
IGS
SAP BW 2.0
© SAP AG
© SAP UCC 2006 SAP BW Course 188
Web Application Designer: Overall Architecture
SAP BW Server (using mySAP Web
App Server Technology)
HTMLTemplates
Data-base SAP BW Charting EngineSAP BW Charting Engine
Any Web Design Tool
OLAP ProcessorOLAP Processor
Portal/Web Browser
http
• Save HTML templates in Web Content Management
• Generate URL automatically
BEx Web Application
Designer
SAP BW Web Service
SAP BW Web Service
BEx Query Designer
(Excel-based, Windows-based,
Web-based)
createQueries/
Views
© SAP AG
© SAP UCC 2006 SAP BW Course 189
Web Application DesignerAvailable web
itemsMultiple documents Web item
propertiesDrag&Drop
© SAP AG
© SAP UCC 2006 SAP BW Course 190
Dependencies
The range of functions of analysis in Web Applications is dependent on which Web Browser you use.
Requirements for Unrestricted Range of FunctionsYou can have the complete range of functions with shortcut menus, snippet operations, and an expanded function toolbar for maps only if the current web browser supports DOM Level 2(with dynamic generation of DOM objects), ECMA-262 Script, HTML 4.0, and CSS 1.0.The reference web browsers are Microsoft Internet Explorer (MS IE) andNetscape Navigator (NS) in the current versions of Windows (MS IE 6.x and NS 6.x).Versions of these web browsers on other systems, such as Apple Macintosh or Linux may deviate in performance.
Minimum RequirementsYou can use Web Applications on web browsers that satisfy the HTML 3.2 standard and supportelementary functions of CSS 1.0.
Web Browser and Range of FunctionsIf you use Internet Explorer 6.x and 5.x as well as Netscape Navigator 6.x, you can utilize the complete range of functions of the shortcut menu and the ad-hoc query designer as well as navigate smoothly.For Internet Explorer 4.x and Netscape Navigator 4.x, the Hierarchical shortcut menu web item islimited: reloading hierarchy branches is not possible.Web browsers such as Internet Explorer 3.0 or Netscape 3 do not enable a shortcut menu in in BEx Web Applications. Instead, you can use symbols for limited navigating.For more information on Web Browser dependencies, go to SAP Service Marketplace, alias SAP BW,and look under Services & Implementation Frequently Asked Questions SAP BW & WebApplication Server.
Source: SAP BW Functions in Detail, Version 1.0 SAP BW 3.0B
© SAP UCC 2006 SAP BW Course 191
Objects Used in the Design Process
ExcelWorkbookExcelWorkbook
HTMLTemplates
ExcelWorkbook
ExcelWorkbook
Items(Charts, Tables, News Tickers ..)
ExcelWorkbook
ExcelWorkbook
SAP BW Queries
ExcelWorkbook
ExcelWorkbookQuery Views
derived from
can be stored with
used in
supply data to
ExcelWorkbook
ExcelWorkbookLibraries
ExcelWorkbook
ExcelWorkbook
SAP BW Workbooks
embedded in
supply data to
= stored in roles
© SAP AG
© SAP UCC 2006 SAP BW Course 192
View
• = Data basis for the items
• Define a set of data
• Specify workbook filters, outlines, exceptions, and so on
• Derived from a query but contain workbook filters and navigation
© SAP UCC 2006 SAP BW Course 193
Items
For example:
• Table (results area)
• Navigation block
• Chart
• Filter
• Alert Monitor
• Exceptions
• Conditions
© SAP UCC 2006 SAP BW Course 194
New Web Items
– Ad-hoc Query Designer– News Ticker– Checkboxes for filter values– Hierarchical dropdown boxes– Single documents and
document list– Menu
New Items
© SAP AG
© SAP UCC 2006 SAP BW Course 195
Structuring the Layout
You can change the layout of your web template - an HTML page with SAP BW content - the sameway you would in an HTML editor.
Arranging Web Items on the Page• You can change the size of the placeholders• You can arrange the web items horizontally• You can drag and drop the web items to the positions you want them and regroup them within the web
template
Arranging Web Items Using an HTML TableYou can use an HTML table to arrange web items.You can lay out this grid for your own needs and place various web items in each table cellvertically or horizontally, according to how you want to arrange them.
Enhancing Web Templates with TextAs well as adding and arranging Web items, you can enhance the Web template with text and formatthis text.
Enhancing Web Templates with ImagesYou can also insert images such as your organization logo into your web template. The images are storedIn the MIME repository of the SAP BW server. The system supports image formats GIF, JPG, and BMP.
Source: SAP BW Functions in Detail, Version 1.0 SAP BW 3.0B
© SAP UCC 2006 SAP BW Course 196
URL
• In General:http://server/sap/bw/BEx?sap-language=Language&cmd=ldoc&TEMPLATE_ID=Template (and other parameters)
• Example:http://hcc2b12.informatik.tu-muenchen.de:8001/sap/bw/BEx?sap-language=DE&cmd=ldoc&TEMPLATE_ID=A200_APPL1
© SAP UCC 2006 SAP BW Course 197
Web Reporting: User and Password
Enter User and Password in URL
• &sap-user=xxx&sap-password=yyy
Anonymous Logon• See SAP Note
498936
© SAP UCC 2006 SAP BW Course 198
Integration in HTML Code
<html>
<body>
<object>
SAP BW Object
</object>
</body>
</html>
SAP BW Objects• Data Provider (View)• Item
© SAP UCC 2006 SAP BW Course 199
Additional Editing of the HTML Code
You have the following options for editing the HTML source of a web template:
1. You can edit the web template directly in the HTML view of Web Application Designer. In the lower part of the Template window of Web Application Designer, select the HTML tab page.
2. You can also use an external HTML editor to edit the web template.
Source: SAP BW Functions in Detail, Version 1.0 SAP BW 3.0B
© SAP UCC 2006 SAP BW Course 200
Data Mining: ABC Classification
© SAP UCC 2006 SAP BW Course 201
What is Data Mining?
• Data mining helps you analyze and understand customer behavior:
– Data mining is an analytical approach that looks for hidden data patterns and relationships in large databases
– Data mining not only provides insights by analyzing past data, but it is also capable of predicting future trends and behaviors
– Data mining allows organizations to make the critical jump from retrospective analysis to prospective decision-making
© SAP AG
© SAP UCC 2006 SAP BW Course 202
ABC Classification - Definition
• ABC Classification is used to classify objects (such as customers, employees, or products) based on a particular measure (such as revenue or profit)
– Two different approaches for classification:• Define intervals for classification criteria• Define intervals for classified object
– Absolute values or cumulated percentages can be used to create these intervals
© SAP AG
© SAP UCC 2006 SAP BW Course 203
Data Mining – Process Overview
Step 1. Create Query
Step 2. Define Model
BW
Step 4. Transfer Results
CRM
Step 3. Run Model
© SAP AG
© SAP UCC 2006 SAP BW Course 204
Revision: Data Flow in BW
© SAP UCC 2006 SAP BW Course 205
Contents
1. Data Flow in SAP BW
2. Source Systems
3. Technical Prerequisites
© SAP UCC 2006 SAP BW Course 206
Exercise
Unit 1• Assignment 1:
Data Warehouse• Assignment 2:
Change the color
© SAP UCC 2006 SAP BW Course 207
Exercise
Additional Assignment• Describe the data
flow in BW.
© SAP UCC 2006 SAP BW Course 208
Data Flow: Overview
SourceSystem
UpdateRule Role
Work-books
Query
Characteristicwith Master Data
InfoSource(Comm. Structure)
TransferRules
PSADataSource(TransferStructure)
Source System
BW
InfoCube(InfoProvider)
xls
Data
Transformation
InfoPackage
View
xls
Web Template
HTMLStructures/Definitions
1
2
3
DS Replication
45+6
7
8
Reporting
© SAP UCC 2006 SAP BW Course 209
Source System Types and Their Interfaces
BW Service APIBW Service API
Web Service
Web Service
RDBMSRDBMSFlat file
Flat file
ExtractorExternal
DB
RF
CS
erve
r
RF
CC
lient
ExtractorNon-SAPSystems
SAP Source System(R/3, CRM, SEM, BW, APO)
FileInter-face
FileInter-face
XMLInter-face
XMLInter-face
DBConnect
DBConnect
StagingBAPI
StagingBAPI
InfoSourceInfoSource
Data Targets
Transfer Rules
Update Rules
BW
1
RFC Connection (sm59)
with Background Users
© SAP UCC 2006 SAP BW Course 210
DataSource
• Metadata of a business process or business unit
• Types: Transaction data, master data (attributes, texts, hierarchies)
• Reference to source system• Each DataSource (DS) has
exactly one extract structure (ES)
• ES is filled by an extractor• Metadata table: ROOSOURCE• DS is replicated from the
source system to the target system
2 0CO_OM_CCA_9: Cost center actual costs line items (Delta)
Function Module View Query
© SAP UCC 2006 SAP BW Course 211
Extractors
• Extracting data from SAP R/3 systems is done by extractors.
• Plug-ins provide the technical solution that makes extraction possible. They also provide prefabricated extraction scenarios for the various modules.
HRHRFIFICOCO
ExtractorExtractor ExtractorExtractor ExtractorExtractor
ExtractorExtractor ExtractorExtractor
DB ViewSAP QueryFunction Module
R/3 System
…
© SAP UCC 2006 SAP BW Course 212
DataSource Replication
3
© SAP AG
© SAP UCC 2006 SAP BW Course 213
InfoSource
• Contains metadata for a business process
• Functions– Metadata comparison
with DataSources– Supplying the data
targets
• Types– Direct updating– Flexible updating
4
© SAP AG
© SAP UCC 2006 SAP BW Course 214
DS-IS Assignment and Transfer Rules
5+6
Fields in the transfer structure are assigned to InfoObjects.
Transfer Rules:- 1:1- Constants- ABAP routine- Formula
© SAP AG
© SAP UCC 2006 SAP BW Course 215
Data Targets
1. Basic InfoCube
2. ODS object
3. Master data-bearing characteristic
Data Target = contains physical data
InfoProvider = reporting basis
7
© SAP UCC 2006 SAP BW Course 216
Update Rules
• Connects flexibly updated InfoSources with data targets
• Various updating methods
8
© SAP AG
© SAP UCC 2006 SAP BW Course 217
Data Flow Modeling in BW
Communication Structure
DataSourceDataSource
InfoSource
Communication Structure
InfoSource
DataSourceDataSource DataSourceDataSource
Application-specific
extractor: FI
Application-specific
extractor: CO
Genericextractor
from table
Update Rules
Transfer Rules Homogenization: transforming
data into a structured and singularformat
Data integration into user-specific models
© SAP UCC 2006 SAP BW Course 218
Exercise
Unit 1• Assignment 3: Data
Flow
Instructor
Unit 1• Assignment 4: Test
the source system
© SAP UCC 2006 SAP BW Course 219
Loading Data from mySAP® ERP®
© SAP UCC 2006 SAP BW Course 220
R/3® Extraction: Tips for Use in Courses
1. Cross-system activities 2 systems must be mastered
2. BW cannot handle clients:multiple customers on a BW system Rules and considerations
3. Large amounts of data may be transferred Transaction time
4. No singular procedure available because extraction is heavily dependent on the application in use large amount of time and effort required for initial use
5. Work with central objects of the Data Dictionary high requirements for designing case studies many activities must be performed by the instructor first
© SAP UCC 2006 SAP BW Course 221
Prerequisites for Data Extraction from R/3
• Necessary plug-ins and patches installed• R/3 system set up as the source system in BW (performed by UCC
upon request)• Unique ID of the systems: logical name• Settings for RFC and ALE• ALE provides monitoring and error handling for data transfer• Requirements and acknowledgement sent through IDocs
R/3 BW
© SAP UCC 2006 SAP BW Course 222
Data Extraction from SAP R/3 Systems
• Extracting data from mySAP ERP systems is done by extractors as plug-ins.
• Plug-ins provide the technical solution that makes extraction possible. They provide prefabricated extraction scenarios for the various modules.
HRFICO
Extractor Extractor Extractor
Extractor Extractor
DB ViewSAP QueryFunction Module
R/3 System
…
© SAP UCC 2006 SAP BW Course 223
Data Flow
Extract structure
Transfer Structure
DataSource
DataSource
Update Rules
SAP BW
SAP R/3
Selection of Fields
Selection of Fields
Replication
Communication Structure
Transfer Rules
Extract structure
ExtractorExtractor
Extract Structure
Extractor
• Data from a DataSource in the source system are provided in the extract structure.
• The extract structure contains the number of fields that an extractor in the source system provides for the process of loading data.
• The extract structures of DataSources are processed in the source system.
• In the transfer structure, data is transferred from the source system to BW.
• The transfer structure represents a selection of fields from a DataSource of the source system.
• A transfer structure is always related to a DataSource from a source system and an InfoSource in BW.
• A DataSource consists of a number of fields that are provided for data transfer to BW.
• Technically, the DataSource is based on the fields of the extract structure.
• You can expand or filter the fields.
© SAP UCC 2006 SAP BW Course 224
Process of an R/3 Upload
• When metadata is uploaded, the corresponding DataSource is copied into BW. In BW, the DataSource can be assigned to an InfoSource.
• The fields of the DataSource can be assigned to InfoObjects in BW.
• An InfoPackage can be scheduled after the data flow has been set by maintaining the transfer rules.
• The process of loading the data is triggered by a request IDoc to the source system.
© SAP UCC 2006 SAP BW Course 225
Extraction Scenarios
Business ContentDataSources
Customer-DefinedDataSources
GenericDataSources
Application-SpecificExtractors
GenericExtractors
App
licat
ion-
Spe
cific
(CO
, F
I, H
R,
etc
.)
Cus
tom
er-
defin
ed(T
ab
les,
Vie
ws,
Q
ue
ries)
Extractors
Dat
a S
tora
ge
in R
/3
-
Extraction Process
Applications
Extractors
Possible focus points in the
course
Legend:
© SAP UCC 2006 SAP BW Course 226
Exercise Scenario
ZYXX_KUVZYCO_OM_CCA_IK0CO_OM_CCA_90CO_OM_CCA_9
R/3 BW
DataSource DataSource InfoSource
InfoCube
0CCA_C11
Template
replicate
0CO_OM_CCA_9
Template
FR
InfoPackage 3
1
2
assign
45
6
Monitoring
7
© SAP UCC 2006 SAP BW Course 227
Delta Data Extractionfrom mySAP® ERP®
© SAP UCC 2006 SAP BW Course 228
Full vs. Delta Upload
There are two kinds of extraction:
– Full Upload: extracting the entire dataset– Delta Upload: only data that has changed since the
last extraction is loaded into BW.
Significant improvement in performance compared to extracting the entire dataset
© SAP UCC 2006 SAP BW Course 229
Exercise Scenario: Postings in OLTP
Material consumptionfor cost center
Vendor invoice
Internal activity allocation
MM
FI
CO
Posting costs in application table COVP
Extractor:Function module BWOMD_GET_CTRCSTA1
DataSource0CO_OM_CCA_9
BW
Postings in the OLTP system after a full update is performed
© SAP UCC 2006 SAP BW Course 230
Exercise
InstructorUnit 3• Assignment 1:
Delta initialization
Unit 3• Assignments 2-4
Perform postings in R/3
Unit 3• Assignments 5-7
Add to delta loading process
© SAP UCC 2006 SAP BW Course 231
Delta Transfer to BW
The BW scheduler offers the following updating modes:– Full Update
Requires all data that matches the selection criteria in the scheduler
– Delta-Update:Requires data that has occurred since the last loading in the source system
– Initializing the Delta Process:Prerequisite for delta processes. Selections for the initialization are used to load the delta records.
© SAP UCC 2006 SAP BW Course 232
Delta Transfer to BW
Update Mode to BW
Update Mode to BW
© SAP AG
© SAP UCC 2006 SAP BW Course 233
How are Deltas Identified?
Delta Queue
• Key values from modified or new records created in one table.
• SAP stores before and after images of each modified dataset in the delta queue.
• Similar approach to DBMS logs.
Time Stamp
• Time stamps posted in an external table.
• Discrepancy between time stamp and posting time.
• So, default safety time should be set.
• Changes cannot be historicized.
© SAP UCC 2006 SAP BW Course 234
DB
Dynpro 1 Dynpro 2 Dynpro 3
... COMMIT WORK.
SAVE
Posting Section
DB COMMIT
Log Tables Application Tables
DB COMMIT DB COMMIT DB COMMIT
DB-LUW 1
Time
Dialog Section
DB COMMIT
SAP-LUW
DB-LUW 2 DB-LUW 3 DB-LUW 4 DB-LUW 4
SAP-LUW
SAP LUW vs. DB LUW
© SAP AG
© SAP UCC 2006 SAP BW Course 235
Safety Time
Because the SAP R/3 system needs a certain amount of posting time to post line items and because it sets the time stamp at the beginning of the posting, there may be a deviation between the posting time and the time stamp. Line items located within this deviation have not yet been posted to the database. Therefore, they cannot be selected when creating a delta dataset and are not loaded into BW.By setting a safety time (a time period in which line items will certainly be posted) you ensure that line items are extracted and loaded into BW despite the deviation between the time stamp and the posting time.
© SAP AG
© SAP UCC 2006 SAP BW Course 236
Delta Procedure of the DataSources
• The delta modes used in a DataSource define a certain delta procedure.
• The delta procedure is a property of the extractor.
• As an attribute of the DataSource, it indicates how the data will be transferred to the data target.
• This enables you to determine the data targets for which a DataSource is suitable, how to perform updates, and how to perform serialization.
© SAP UCC 2006 SAP BW Course 237
DataSource Delta Capability
Delta update possibleDelta update possible
© SAP AG
© SAP UCC 2006 SAP BW Course 238
Delta Extraction – Example: Cost Centers
0CO_OM_CCA_9Cost Centers:
Actual costs line items(Delta)
0CO_OM_CCA_9Cost Centers:
Actual costs line items(Delta)
DataSource
Data origintables R/3
Data Records:-Before Img.-After Img.
Time StampTable
BW
Defining the Delta Process
ADD
Delta ProcessADD: Additive Extraction via Extractor• The extractor allows fields to be added only.• Updating possible in InfoCube and ODS.• Request Serialization.
Because of Posting of Line Items:• Deviation between time stamp and posting time• Set a safety time
Updating modes supported:• Delta-Init (determining the initial set)• Delta Update (determining and uploading the delta dataset)• Full Update (determining and uploading the entire dataset)
R/3
DataSource 0CO_OM_CCA_9 returns information on actual costs that have been posted to cost centers.
© SAP UCC 2006 SAP BW Course 239
Conclusion: Uses of “BW Extraction”
1. Simply, “Filling InfoCubes”
2. Database-oriented subject
3. Delta Management as challenging SAP subject
4. System-wide case studies
1. System-wide activities 2 systems must be mastered
2. BW cannot support multiple clients: several customers in one BW system Rules and consideration
3. Large datasets may be moved Length of transactions
4. No single procedure, as extraction is largely dependent on application considerable time and effort required for initial use
5. Work with central objects of the Data Dictionary high requirements for designing case studies many activities must be carried out by the instructor
Opportunities Challenges
© SAP UCC 2006 SAP BW Course 240
Extraction from mySAP ERP Using Generic Data Sources
© SAP UCC 2006 SAP BW Course 241
mySAP ERP Users
• G51, Client 902(mySAP ERP ECC 5)
• Users: DEVELOP-XX, with XX = 01 to 20
• Password: init
• There are developer keys for these users (see table)
© SAP UCC 2006 SAP BW Course 242
Extraction Scenarios
Business ContentDataSources
Customer-DefinedDataSources
GenericDataSources
ApplicationSpec.Extractors
GenericExtractors
App
licat
ion-
Spe
cific
(CO
, F
I, H
R,
etc
.)
Cus
tom
er-
Def
ined
(Ta
ble
s, V
iew
s,
Qu
erie
s)
Extractors
Dat
a S
tora
ge
in R
/3
-
Extraction Process
Applications
Extractors
Possible focus points in the
course
© SAP UCC 2006 SAP BW Course 243
mySAP ERP Source system
Scenario: Generic Extraction
USR01
USREFUS
R/3 Application tables(User administration)
Z_YXX_Userdata
Extractor (View)
Z_YXX_Userdata_DS
GenericDataSource
BW System
Z_YXX_Userdata_DS
GenericDataSource(copy)
AYXX_US_IS
InfoSource
Z_YXX_Userdata
Z_YXX_Userdata_DS
Z_YXX_Userdata_DS
AYXX_US_IS
AYXX_US
Characteristic (with master data)
AYXX_US
© SAP UCC 2006 SAP BW Course 244
Project Completion
© SAP UCC 2006 SAP BW Course 245
Distribution of a Data Warehouse
• Making the product known to users• Marketing: newsletter, webpage• Community• Technical setup at the workplace• User training• Creating a support structure
The users are the most sensitivefactor in a data warehouse project!
NewDataWare-
house !!!
© SAP UCC 2006 SAP BW Course 246
Data Warehouse Maintenance
• User-Related “Maintenance”– Constant contact with users– Continuous Support– Providing training continuously and repeatedly
• Technical Maintenance– Avoiding system downtime– Maintaining the infrastructure– Guaranteeing and improving performance
• Managing Growth– Equipping the system for growth– Growth is a sign of DW acceptance
© SAP UCC 2006 SAP BW Course 247
Terminating/Replacing a DW
• Determining the time for complete termination or replacement
• Conversion costs
• Residual license costs
Investment calculation Life cycle view Follow-up project!
© SAP UCC 2006 SAP BW Course 248
SourceSystem
UpdateRule Role
Work-books
Query
Characteristicwith Master Data
InfoSource(Comm. Structure)
TransferRules
PSADataSource(TransferStructure)
Source BW
InfoCube(InfoProvider)
xls
Source: BW Course, TUM March 31, 2004
Data
Transformation
InfoPackage
View
xls
Web Template
HTML
Structures/Definitions
© SAP UCC 2006 SAP BW Course 249
Current BW Courses from SAP AG
© SAP UCC 2006 SAP BW Course 250
Courses on SAP BW: Overview
Source: www.sap.de(online course catalog),accessed April 2006
© SAP UCC 2006 SAP BW Course 251
Courses on SAP BW: Reporting Emphasis
• Focus on analyses and evaluations• Primarily BEx Analyzer• InfoProvider and up
Source: www.sap.de(online course catalog),accessed April 2006
© SAP UCC 2006 SAP BW Course 252
Courses on SAP BW: Data Warehousing Emphasis
• Technically oriented• Primarily AWB• Up to InfoProvider
Source: www.sap.de(online course catalog),accessed April 2006
© SAP UCC 2006 SAP BW Course 253
Courses on SAP BW: Administration Emphasis
• Not necessary for UCC customers• Task of UCC
Source: www.sap.de(online course catalog),accessed April 2006