Introduction to BusinessObjects Data Services

1. Introduction to
SAP BusinessObjects Data Services XI 3.0

2. Disclaimer
The information in this presentation is confidential and proprietary to SAP and may not be
disclosed without the permission of SAP. This presentation is not subject to your license
agreement or any other service or subscription agreement with SAP. SAP has no obligation to
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warranties of merchantability, fitness for a particular purpose, or non-infringement. This
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assumes no responsibility for errors or omissions in this document, except if such damages
were caused by SAP intentionally or grossly negligent.
All forward-looking statements are subject to various risks and uncertainties that could cause
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3. Agenda
1. Why Enterprise Information Management
2. Data Services: One tool for data integration and data quality
management
3. Metadata Management: Impact and lineage to prove trustworthiness of
your data
4. Some data services use cases in an SAP environment
5. Wrap-up

4. Trusted Information is Elusive
Key Problems in Managing Data
The volume of data within
enterprises is exploding
Application silos make it difficult for
people to collaborate
Users have little understanding of
the quality of available data
Excessive time is spent on
integration rather than innovation
IT is struggling to address rapidly
changing business requirements

5. Poorly Managed Information
Leads to Inefficiency and Risk
“ 90% of upper level management feel they don’t have
the necessary information for critical business
Lower Profits
decisions; 50% of them are afraid they are making
poor decisions because of it.”
― Economist Intelligence Unit
“ 50% to 70% of ERP implementations are reported as
“challenged” in part to data integrity and/or data Low
accuracy problems.”
Productivity
― Adaptive Growth, Inc.
“ © SAP 2009
90% of all businesses still do not have
sufficient policies in place to meet data
Compliance
governance regulations.”
/ Page 4 ― IT Policy Compliance Group Failures

6. Challenges to Effectively Managing Information
How Does This Impact IT?
Top issues
How do I empower all users with the information they
need to make better decisions?
How do I help people to work across enterprise
boundaries?
How do I provide applications with accurate data to
drive business operations?
How do I implement data governance to ensure
compliance and meet regulatory requirements?
How can I minimize cost and manage complexity?

7. Inconsistent Data Across Different Silos
Impacts Business Results and Increases Costs
Data Managed in Silos
Plant
Finance Sales
Departments create and store their own data
Data inconsistencies, redundancies, and errors impact business results and
increase costs

8. Manage Information as a Strategic Asset
Reduce Inefficiencies and Deliver Trusted Information
Enterprise Information Management
Plant
Enterprise-Wide Reusable
Information
Finance Sales
Each information asset is readily understood, available and trusted
Formal information architecture to identify, share and govern all data

9. SAP Provides A Complete Approach To EIM
Encompassing People, Process & Technology
Enterprise Information Management
Executive IT
PEOPLE
Sponsor
Line of Data
Business Steward
Owners
PROCESS
Create Cleanse Integrate Manage Govern Archive
Monitor
TECHNOLOGY
Content &
Data Integration &
Data Warehouse Master Data Information
Quality
Management Management Life-Cycle
Management
Management

10. SAP Provides Best-In-Class EIM Solutions
Deliver Information That Is Complete, Accurate, and Accessible
Data Integration & Quality Management: Master Data Management:
SAP BusinessObjects Data Services SAP NetWeaver Master Data Management
SAP BusinessObjects Data Federator SAP Master Data Governance for Financials
SAP BusinessObjects Text Analysis SAP Data Maintenance by Vistex
SAP BusinessObjects Data Insight
SAP Data Migration services
Content & Information Lifecycle Management: Enterprise Data Warehousing:
SAP NetWeaver Information Lifecycle Management SAP NetWeaver Business Warehouse
SAP Extended ECM by Open Text SAP NetWeaver Business Warehouse Accelerator
SAP Document Access by Open Text SAP BusinessObjects Rapid Marts
SAP Archiving by Open Text SAP BusinessObjects Metadata Management

11. Agenda
1. Why Enterprise Information Management
2. Data Services: One tool for data integration and data quality
management
3. Metadata Management: Impact and lineage to prove trustworthiness of
your data
4. Some data services use cases in an SAP environment
5. Wrap-up

12. SAP BusinessObjects Data Services
Data Services is the first single tool for data integration and data quality
Data Integrator XI R2 Data Services
Development
User Interface
One Development
User Interface
Metadata
Repository
Runtime
Architecture
One Metadata
Repository
Administration and Connectors
One Runtime
Architecture Access
Data Quality XI R2
Transform
Development
User Interface
Improve
Metadata
Repository
Deliver
Runtime
Architecture
One Administration Environment
Administration and Connectors One Set of Connectors

13. Data Services Architecture
SAP ERP, SAP CRM,
SAP Master Data
Management (MDM),
SAP NetWeaver BI, …
SOA
SAP R/3,
Data Migration,
SAP ERP,
SAP NetWeaver BI Data Synchronization, …
Data profiling
Cleansing
Oracle, SQL, Data
DB2, etc. Real Services
Time Data Query,
Engine
Validation Reporting,
PeopleSoft, Analysis,
Oracle Apps, Batch and Dashboards
Siebel, etc. Data
Auditing SAP NetWeaver BI
Files, XML, Data Lineage
Mainframe, Shared Metadata
Excel, etc. Impact Analysis

14. Enterprise-Wide Data Access
Support for structured and unstructured data
Broad connectivity to databases, applications, legacy, file formats, and unstructured
data
Databases Applications Files/Transport Mainframe Unstructured Data
(with partner)
Oracle JD Edwards Text delimited ADABAS Any text file type
DB2 Oracle Apps Text fixed width ISAM 32 languages
Sybase & IQ PeopleSoft EBCDIC VSAM
SQL Server Siebel XML Enscribe
Informix Salesforce.com Cobol IMS/DB
Teradata SAP NetWeaver Excel RMS
ODBC BI HTTP Both direct and
MySQL SAP R/3 JMS change data
Netezza – ABAP SOAP
HP NeoView – BAPI (Web Services)
– IDoc

15. Data Integrator : Enterprise-class
Data Integration platform
Explore, transform, and move data anywhere, at any frequency
Deliver trusted information
Market leading data quality functionality within the data integration environment
Built-in features for validating data against business rules and auditing data movement execution
End-to-end metadata impact analysis and lineage
Agility and ease-of-use
Single easy to use development interface
to build, test,and deploy
Web-based administration and management
Collaboration features for team development
Deliver extreme ETL scalability
Parallelized processing down to the transform level
Grid computing for high availability and throughput
Services-based architecture enabling
right-time data delivery
Powerful prepackaged transformations

16. Increase Value of Data Assets with Data
Quality
Measure and analyze data
through data assessment
and continuous monitoring
Cleanse and enhance
customer and operational
data anywhere across the
enterprise
Match and consolidate
data at multiple levels within
a single pass for individuals,
households, or corporations
Improve and automate the
delivery of direct mail and
goods

17. Data Cleansing examples : Customer Data
(name)
Input record Output record
Maggie.kline@future_electronics.com Salutation: Ms.
Margaret Smith-Kline phd First name: Margaret
Last name: Smith-Kline
FUTURE Electronics
Postname: Ph. D.
5/23/03 Match standards: Maggie, Peg, Peggy
101 6th ave Gender: Strong Female
manhattan Company name: Future Electronics
Address 1: 101 Avenue of the Americas
ny
City: New York
10012 State: NY
001124367 ZIP+4: 10013-1933
Email: maggie.kline@future_electronics.com
SSN: XXX-XX-XXXX
Date May 23, 2003

18. Data Cleansing examples : Product Data
(Universal Data Cleanse)
Input Parsed output
Description Product Dimension Type Form
Kallkyle screw screw Kallkyle
test steel plate 20 x 35 mm plate 20x35 mm steel test
wire 23.33 x 40.50 cm wire 23.33 x 40.50 cm
34 x 60 mm steel plate plate 34 x 60 mm steel
steel plate 34,0 60 mm plate 34 x 60 mm steel
34.0 x 60,0 mm steel plate plate 34 x 60 mm steel
34 x 60 mm steel plate? plate 34 X 60 mm steel
plate plate
steel plate plate steel

19. Matching and Consolidation example
Ms. Margaret Smith-Kline Ph.D.
Future Electronics Consolidated record
101 Avenue of the Americas
New York NY 10013-1933 Name: Ms. Margaret Smith-Kline Ph.D.
maggie.kline@future_electronics.com
Company name: Future Electronics Co. LLC
May 23, 2003
SSN: 001-12-4367
Input records
Maggie Smith
Purchase date: 5/23/2003
Future Electronics Co. LLC
101 6th Ave. Address: 101 Avenue of the Americas
Manhattan, NY 10012 New York, NY 10013-1933
maggie.kline@future_electronics.com
Latitude: 40.722970
001-12-4367
Longitude: -74.005035
Ms. Peg Kline
Fed code: 36061
Future Elect. Co.
101 6th Ave. Phone: (222) 922-9922
New York NY 10013 Email: maggie.kline@future_electronics.com
001-12-4367
(222) 922-9922
5/23/03

20. Data Services in action
Cleanse Validate
Deliver
Access
Profile

21. Agenda
1. Our vision of information management
2. Data Services: One tool for data integration and data quality
management
3. Metadata Management: Impact and lineage to prove trustworthiness
of your data
4. Some data services use cases in an SAP environment
5. Wrap-up

22. Data Lineage Helps Users Make Confident
Decisions
Where did this number come from?
Data lineage provides information on how a number in your
BI report is calculated during the ETL process and its origin

23. Data Lineage and Impact Analysis
Data Lineage: End users are able to trace back data in their reports to the original
source through all different layers and transformation and presentation steps.
Impact Analysis: IT needs to know which reports and users will be affected when
a change is made to one of the source systems.
© SAP 2008 /

24. Metadata Management Architecture
Consolidate metadata from multiple systems
Integrate into one central, open metadata repository
Audit impact, usage, and lineage using the Metadata Explorer
Trust your metadata with added business content
Consolidate
Integrate
Audit
Custom Attributes
Annotations, Metapedia Business
Metadata

25. Agenda
1. Our vision of information management
2. Data Services: One tool for data integration and data quality
management
3. Metadata Management: Impact and lineage to prove trustworthiness of
your data
4. Some data services use cases in an SAP environment
5. Wrap-up

26. Scenario 1: Data Quality for SAP CRM
Data Quality Management for SAP provides a prepackaged native integration of
data quality best practices within the SAP environment using the
BusinessObjects Data Services platform
Enforces data discipline directly within SAP CRM or SAP ERP systems
No extracts for external processing required
Virtually undetectable presence that provides:
Global address correction and standardization
Comprehensive duplicate detection
Convenient record searching
Supported versions
SAP CRM: Releases 4.0 and 5.0
SAP ERP Central Component: Release 5.0 and 6.0
SAP R/3 4.6C

27. Examples
Review the Corrected and
Fielded Information
Potential
Duplicates
Identified!

28. Scenario 2: Load SAP NetWeaver BW
SAP NetWeaver 7.0
Business Warehouse
Get easy access to data stored in non-
SAP sources
Replace database connectivity with
Reporting Layer Rapid Mart application understanding
InfoSource
(Architected Data Marts)
Business Transformation Layer Operational Include data cleansing and validation
Data Store
rules before loading data
Data Propagation Layer Corp.
Mem- PSA Standardize, correct, and enhance
DataSource
Harmonization Layer ory
Match and consolidate
Data Acquisition Layer Validate against validation rules before
loading into SAP NetWeaver BI
Data Services
Order Management

29. Scenario 3: Data Migration for SAP
Traditional
?
LEGACY SAP
Steps SYSTEM(S) ERP
Provision
of data
Upload
“Let’s cross the fingers
and hope it loads …
But attention:
Data migration is far from easy.
Analysts Why?
More than 80% of data migration projects run over time Lack of experience
and/or over budget. Cost overruns average 30%. Time Migration project plan is unrealistic
overruns average 41%. Data quality issues/lack of confidence in
Bloor, 2007 the data
You need to extend the consultants time for
80% of organizations … will underestimate the costs the SAP ERP project
related to the data acquisition tasks by an average of 50
percent
Gartner, Data Warehouse Infrastructure for Growth and It is crucial to identify the right
Change partner with the right expertise for
your data migration project.

30. SAP Data Migration Services
End-to-End Solution for Data Migration
Data migration is a critical element in the
success of the ERP implementation
Ensure accountability and a robust project
approach to data migration from a single
strategic vendor
Enable data governance best practices that
live on after the project
Industry-leading BusinessObjects Data
SAP Services platform benefits data migration and
DATA MIGRATION delivers many additional benefits in information
SERVICES
management
Framework
LEGACY SAP
SYSTEM(S)
Templates
ERP
Pre-built framework and tools reduce the
Methodology need for custom scripts and deliver data
Tools insights more quickly and consistently
Expertise
Engage business users early with better
The right tools combined with the access to data quality and metrics
right methodology and powerful
expertise – That’s SAP Data
Migration Service

31. SAP Data Migration Framework
Based on BusinessObjects Data Services
Data Governance Visualization
Project Management Summary Business users/Data Steward
Metrics reports
Track % quality and progress over Show detailed data exceptions
time against project requiring resolution for each SAP
milestones Business Objects, e.g., Customer,
including reconciliation
exceptions BUSINESS
Data Exceptions
&
DQ Metrics
Migration Framework
Staging SAP Load:
Oracle Apps, XML, IDOC,
PeopleSoft, Cleanse, Harmonize,
Reconcile File
JDEdwards, Siebel
Extract & SAP Business Object
transform to Validation Library
Legacy SAP IT
SAP Library of DS objects to
structures validate the data pre-
Post load
load. reconciliation
XML, The metrics created from
flat file this process drive the
Data Governance Engine

32. Agenda
1. Our vision of information management
2. Data Services: One tool for data integration and data quality
management
3. Metadata Management: Impact and lineage to prove trustworthiness of
your data
4. Some data services use cases in an SAP environment
5. Wrap-up

33. 7 Key Points to Take Home
Data is spread throughout systems and applications in the enterprise
You need a broad connectivity to all source systems
Don‘t forget the unstructured data!
Make sure you understand your data well before starting any project
Profiling your data will give you insight into your source data and identify potential data
quality issues
The quality of data will vary among source systems
Standardize, cleanse, and enrich data before loading into the target applications
Avoid duplicate data
Find matches and consolidate to get one “golden record”
Use a “data quality firewall”
Define validation rules to prevent incorrect data to get loaded
Deliver data in “right-time”
Sometimes you need real-time services, in other cases you need to bulk load data
overnight. One architecture should be able to serve all needs.
Don‘t underestimate the importance of metadata
Metadata gives insight in where the data comes from and how it was transformed

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