- 1. Introduction to SAP BusinessObjects Data Services XI
3.0
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materially from expectations. Readers are cautioned not to place
undue reliance on these forward-looking statements, which speak
only as of their dates, and they should not be relied upon in
making purchasing decisions. 3. Agenda 1. Why Enterprise
Information Management 2. Data Services: One tool for data
integration and data qualitymanagement 3. Metadata Management:
Impact and lineage to prove trustworthiness ofyour data 4. Some
data services use cases in an SAP environment 5. Wrap-up 4. Trusted
Information is Elusive Key Problems in Managing DataThe volume of
data withinenterprises is explodingApplication silos make it
difficult forpeople to collaborateUsers have little understanding
ofthe quality of available dataExcessive time is spent
onintegration rather than innovationIT is struggling to address
rapidlychanging business requirements 5. Poorly Managed Information
Leads to Inefficiency and Risk 90% of upper level management feel
they dont have the necessary information for critical businessLower
Profitsdecisions; 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 dataLowaccuracy problems.Productivity Adaptive
Growth, Inc. SAP 200990% of all businesses still do not have
sufficient policies in place to meet dataCompliance 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
CostsData Managed in Silos PlantFinanceSalesDepartments create and
store their own dataData inconsistencies, redundancies, and errors
impact business results andincrease costs 8. Manage Information as
a Strategic Asset Reduce Inefficiencies and Deliver Trusted
InformationEnterprise Information Management PlantEnterprise-Wide
ReusableInformation FinanceSalesEach information asset is readily
understood, available and trustedFormal information architecture to
identify, share and govern all data 9. SAP Provides A Complete
Approach To EIM Encompassing People, Process & Technology
Enterprise Information Management ExecutiveIT PEOPLESponsor Line of
Data Business Steward Owners PROCESS CreateCleanseIntegrateManage
Govern ArchiveMonitor TECHNOLOGYContent &Data Integration
&Data WarehouseMaster DataInformationQuality Management
ManagementLife-CycleManagement 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
FederatorSAP Master Data Governance for Financials SAP
BusinessObjects Text Analysis SAP Data Maintenance by Vistex SAP
BusinessObjects Data Insight SAP Data Migration servicesContent
& Information Lifecycle Management:Enterprise Data
Warehousing:SAP NetWeaver Information Lifecycle Management SAP
NetWeaver Business WarehouseSAP Extended ECM by Open TextSAP
NetWeaver Business Warehouse AcceleratorSAP Document Access by Open
TextSAP BusinessObjects Rapid MartsSAP Archiving by Open TextSAP
BusinessObjects Metadata Management 11. Agenda 1. Why Enterprise
Information Management 2. Data Services: One tool for data
integration and data qualitymanagement 3. Metadata Management:
Impact and lineage to prove trustworthiness ofyour 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 qualityData Integrator XI R2
Data Services Development User Interface One DevelopmentUser
InterfaceMetadataRepositoryRuntimeArchitectureOne Metadata
Repository Administration and Connectors One Runtime
ArchitectureAccessData Quality XI R2Transform Development User
InterfaceImproveMetadataRepository Deliver RuntimeArchitecture One
Administration EnvironmentAdministration and ConnectorsOne Set of
Connectors 13. Data Services ArchitectureSAP ERP, SAP CRM, SAP
Master DataManagement (MDM),SAP NetWeaver BI, SOASAP R/3,Data
Migration, SAP ERP, SAP NetWeaver BIDataSynchronization, Data
profilingCleansing Oracle, SQL,Data DB2, etc.Real ServicesTimeData
Query,EngineValidation Reporting, PeopleSoft,Analysis, Oracle Apps,
Batchand Dashboards Siebel, etc.DataAuditingSAP 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 dataDatabasesApplications
Files/Transport Mainframe Unstructured Data (with partner) OracleJD
EdwardsText delimited ADABAS Any text file typeDB2 Oracle Apps Text
fixed width ISAM 32 languagesSybase & IQ PeopleSoftEBCDIC
VSAMSQL
ServerSiebelXMLEnscribeInformixSalesforce.comCobolIMS/DBTeradataSAP
NetWeaver ExcelRMSODBCBIHTTP Both direct andMySQL SAP R/3 JMSchange
data Netezza ABAP SOAPHP NeoView BAPI (Web Services) IDoc 15. Data
Integrator : Enterprise-class Data Integration platformExplore,
transform, and move data anywhere, at any frequency Deliver trusted
informationMarket leading data quality functionality within the
data integration environmentBuilt-in features for validating data
against business rules and auditing data movement
executionEnd-to-end metadata impact analysis and lineageAgility and
ease-of-useSingle easy to use development interfaceto build,
test,and deployWeb-based administration and managementCollaboration
features for team development Deliver extreme ETL
scalabilityParallelized processing down to the transform levelGrid
computing for high availability and throughputServices-based
architecture enablingright-time data deliveryPowerful prepackaged
transformations 16. Increase Value of Data Assets with Data Quality
Measure and analyze datathrough data assessmentand continuous
monitoringCleanse and enhancecustomer and operationaldata anywhere
across theenterpriseMatch and consolidatedata at multiple levels
withina single pass for individuals,households, or
corporationsImprove and automate thedelivery of direct mail
andgoods 17. Data Cleansing examples : Customer Data (name)Input
recordOutput record Maggie.kline@future_electronics.com Salutation:
Ms.Margaret Smith-Kline phd First name: Margaret Last name:
Smith-KlineFUTURE Electronics Postname: Ph. D.5/23/03Match
standards: Maggie, Peg, Peggy101 6th aveGender: Strong
FemalemanhattanCompany name: Future Electronics Address 1: 101
Avenue of the Americasny City: New York10012State:
NY001124367ZIP+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 outputDescriptionProductDimension Type Form
Kallkyle screwscrew Kallkyle test steel plate 20 x 35 mm plate20x35
mm steel test wire 23.33 x 40.50 cm wire 23.33 x 40.50 cm34 x 60 mm
steel plateplate34 x 60 mm steel steel plate 34,0 60 mmplate34 x 60
mm steel 34.0 x 60,0 mm steel plateplate34 x 60 mm steel 34 x 60 mm
steel plate? plate34 X 60 mm steel plate platesteel plate plate
steel 19. Matching and Consolidation exampleMs. Margaret
Smith-Kline Ph.D.Future ElectronicsConsolidated record101 Avenue of
the Americas New York NY 10013-1933Name: 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
recordsMaggie Smith Purchase date: 5/23/2003 Future Electronics Co.
LLC101 6th Ave. Address: 101 Avenue of the AmericasManhattan, NY
10012New York, NY 10013-1933 maggie.kline@future_electronics.com
Latitude: 40.722970 001-12-4367 Longitude: -74.005035Ms. Peg Kline
Fed code: 36061Future 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
actionCleanse ValidateDeliverAccess Profile 21. Agenda 1. Our
vision of information management 2. Data Services: One tool for
data integration and data qualitymanagement 3. Metadata Management:
Impact and lineage to prove trustworthinessof your data 4. Some
data services use cases in an SAP environment 5. Wrap-up 22. Data
Lineage Helps Users Make Confident DecisionsWhere 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 AnalysisData Lineage: End users are
able to trace back data in their reports to the originalsource
through all different layers and transformation and presentation
steps. Impact Analysis: IT needs to know which reports and users
will be affected whena change is made to one of the source systems.
SAP 2008 / 24. Metadata Management Architecture Consolidate
metadata from multiple systemsIntegrate into one central, open
metadata repositoryAudit impact, usage, and lineage using the
Metadata ExplorerTrust your metadata with added business content
ConsolidateIntegrate AuditCustom AttributesAnnotations, Metapedia
Business Metadata 25. Agenda 1. Our vision of information
management 2. Data Services: One tool for data integration and data
qualitymanagement 3. Metadata Management: Impact and lineage to
prove trustworthiness ofyour 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
platformEnforces data discipline directly within SAP CRM or SAP ERP
systemsNo extracts for external processing requiredVirtually
undetectable presence that provides:Global address correction and
standardizationComprehensive duplicate detectionConvenient record
searchingSupported versionsSAP CRM: Releases 4.0 and 5.0SAP ERP
Central Component: Release 5.0 and 6.0SAP R/3 4.6C 27.
ExamplesReview the Corrected andFielded
InformationPotentialDuplicatesIdentified! 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
withReporting LayerRapid Mart application understanding
InfoSource(Architected Data Marts) Business Transformation Layer
Operational Include data cleansing and validation Data Storerules
before loading data Data Propagation Layer Corp.Mem-PSAStandardize,
correct, and enhance DataSourceHarmonization Layerory Match and
consolidate Data Acquisition LayerValidate against validation rules
before loading into SAP NetWeaver BIData ServicesOrder Management
29. Scenario 3: Data Migration for SAP Traditional ?LEGACYSAP
StepsSYSTEM(S) ERP Provisionof data Upload Lets cross the
fingersand hope it loads But attention: Data migration is far from
easy.AnalystsWhy?More than 80% of data migration projects run over
time Lack of experience and/or over budget. Cost overruns average
30%. TimeMigration project plan is unrealistic overruns average
41%.Data quality issues/lack of confidence in Bloor, 2007the
dataYou need to extend the consultants time for 80% of
organizations will underestimate the coststhe 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 Changepartner 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 andDATA
MIGRATION delivers many additional benefits in information SERVICES
management Framework LEGACYSAP 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 metricsright
methodology and powerfulexpertise Thats SAP Data Migration Service
31. SAP Data Migration Framework Based on BusinessObjects Data
Services Data Governance VisualizationProject Management Summary
Business users/Data Steward Metricsreports Track % quality and
progress overShow detailed data exceptions time against project
requiring resolution for each SAP milestones Business Objects,
e.g., Customer,including reconciliationexceptions BUSINESSData
Exceptions& DQ Metrics Migration FrameworkStaging SAP
Load:Oracle Apps,XML, IDOC,PeopleSoft,Cleanse, Harmonize, Reconcile
FileJDEdwards, Siebel Extract &SAP Business Object transform to
Validation LibraryLegacy SAPIT SAPLibrary of DS objects
tostructuresvalidate the data pre-Post loadload. reconciliation
XML, The metrics created from flat filethis process drive theData
Governance Engine 32. Agenda 1. Our vision of information
management 2. Data Services: One tool for data integration and data
qualitymanagement 3. Metadata Management: Impact and lineage to
prove trustworthiness ofyour data 4. Some data services use cases
in an SAP environment 5. Wrap-up 33. 7 Key Points to Take HomeData
is spread throughout systems and applications in the enterpriseYou
need a broad connectivity to all source systemsDont forget the
unstructured data!Make sure you understand your data well before
starting any projectProfiling your data will give you insight into
your source data and identify potential dataquality issuesThe
quality of data will vary among source systemsStandardize, cleanse,
and enrich data before loading into the target applicationsAvoid
duplicate dataFind matches and consolidate to get one golden
recordUse a data quality firewallDefine validation rules to prevent
incorrect data to get loadedDeliver data in right-timeSometimes you
need real-time services, in other cases you need to bulk load
dataovernight. One architecture should be able to serve all
needs.Dont underestimate the importance of metadataMetadata gives
insight in where the data comes from and how it was transformed 34.
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