Introduction to SAP BusinessObjects Data Services XI 3.0

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1. Why Enterprise Information Management2. Data Services: One tool for data integration and data quality

management3. Metadata Management: Impact and lineage to prove trustworthiness of

your data4. Some data services use cases in an SAP environment5. Wrap-up

Agenda

Trusted Information is ElusiveKey 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

90% of upper level management feel they don’t have the necessary information for critical business

decisions; 50% of them are afraid they are making poor decisions because of it.”

― Economist Intelligence Unit

Poorly Managed Information Leads to Inefficiency and Risk

© SAP 2009 / Page 4

ComplianceFailures

Lower Profits

LowProductivity

50% to 70% of ERP implementations are reported as “challenged” in part to data integrity and/or data

accuracy problems.”

― Adaptive Growth, Inc.

90% of all businesses still do not have sufficient policies in place to meet data

governance regulations.”― IT Policy Compliance Group

“

“

“

Challenges to Effectively Managing InformationHow Does This Impact IT?

Top issuesHow 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?

Inconsistent Data Across Different SilosImpacts Business Results and Increases Costs

Data Managed in Silos

Finance Sales

Plant

Departments create and store their own data

Data inconsistencies, redundancies, and errors impact business results and increase costs

Manage Information as a Strategic AssetReduce Inefficiencies and Deliver Trusted Information

Enterprise Information Management

Finance Sales

Plant

Enterprise-Wide Reusable Information

Each information asset is readily understood, available and trusted

Formal information architecture to identify, share and govern all data

SAP Provides A Complete Approach To EIMEncompassing People, Process & Technology

Create Monitor

Enterprise Information Management

Executive Sponsor

Line of BusinessOwners

IT

Data Steward

Data Integration & Quality

Management

Master Data Management

Content & InformationLife-Cycle

Management

Data WarehouseManagement

PR

OC

ES

SP

EO

PLE

TE

CH

NO

LOG

Y

Cleanse Integrate Manage Govern Archive

SAP Provides Best-In-Class EIM SolutionsDeliver Information That Is Complete, Accurate, and Accessible

Data Integration & Quality Management:SAP BusinessObjects Data ServicesSAP BusinessObjects Data FederatorSAP BusinessObjects Text AnalysisSAP BusinessObjects Data InsightSAP Data Migration services

Master Data Management:SAP NetWeaver Master Data Management

SAP Master Data Governance for FinancialsSAP Data Maintenance by Vistex

Enterprise Data Warehousing:SAP NetWeaver Business Warehouse

SAP NetWeaver Business Warehouse AcceleratorSAP BusinessObjects Rapid Marts

SAP BusinessObjects Metadata Management

Content & Information Lifecycle Management:SAP NetWeaver Information Lifecycle ManagementSAP Extended ECM by Open TextSAP Document Access by Open TextSAP Archiving by Open Text

1. Why Enterprise Information Management2. Data Services: One tool for data integration and data quality

management3. Metadata Management: Impact and lineage to prove trustworthiness of

your data4. Some data services use cases in an SAP environment5. Wrap-up

Agenda

SAP BusinessObjects Data Services

One Runtime Architecture

One Development User Interface

One Metadata Repository

One Administration EnvironmentOne Set of Connectors

Data Services

Improve

Deliver

Transform

Access

Runtime Architecture

Metadata Repository

Development User Interface

Administration and Connectors

Runtime Architecture

Metadata Repository

Development User Interface

Administration and Connectors

Data Integrator XI R2

Data Quality XI R2

Data Services is the first single tool for data integration and data quality

SAP ERP, SAP CRM, SAP Master Data

Management (MDM), SAP NetWeaver BI, …

SOA

Shared MetadataImpact Analysis

Data Lineage

Dat

a pr

ofili

ng

Data Services Architecture

DataServicesEngine

Data Auditing

Data Validation

DataCleansing

RealTime

Batch

Files, XML,Mainframe, Excel, etc.

Oracle, SQL, DB2, etc.

PeopleSoft, Oracle Apps, Siebel, etc.

SAP R/3, SAP ERP,SAP NetWeaver BI

Query, Reporting,Analysis,

and Dashboards

Data Migration, Synchronization, …

SAP NetWeaver BI

OracleDB2Sybase & IQSQL ServerInformixTeradataODBCMySQLNetezzaHP NeoView

JD EdwardsOracle AppsPeopleSoftSiebelSalesforce.comSAP NetWeaver BISAP R/3

– ABAP– BAPI– IDoc

Text delimitedText fixed widthEBCDICXMLCobolExcelHTTPJMSSOAP(Web Services)

ADABASISAMVSAMEnscribeIMS/DBRMSBoth direct and change data

Enterprise-Wide Data Access

Broad connectivity to databases, applications, legacy, file formats, and unstructured data

Any text file type32 languages

Support for structured and unstructured data

Databases Applications Files/Transport Mainframe(with partner) Unstructured Data

Data Integrator : Enterprise-class Data Integration platform

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 lineage

Agility and ease-of-useSingle easy to use development interface to build, test,and deployWeb-based administration and management Collaboration features for team development

Deliver extreme ETL scalabilityParallelized processing down to the transform levelGrid computing for high availability and throughputServices-based architecture enabling right-time data deliveryPowerful prepackaged transformations

Explore, transform, and move data anywhere, at any frequency

Increase Value of Data Assets with Data Quality

Measure and analyze data through data assessment and continuous monitoring

Cleanse and enhancecustomer and operational data anywhere across the enterprise

Match and consolidatedata at multiple levels within a single pass for individuals, households, or corporations

Improve and automate the delivery of direct mail and goods

Data Cleansing examples : Customer Data (name)

Maggie.kline@future_electronics.com

Margaret Smith-Kline phd

FUTURE Electronics

5/23/03

101 6th ave

manhattan

ny

10012

001124367

Salutation: Ms.First name: MargaretLast name: Smith-KlinePostname: Ph. D.Match standards: Maggie, Peg, PeggyGender: Strong FemaleCompany name: Future ElectronicsAddress 1: 101 Avenue of the AmericasCity: New YorkState: NYZIP+4: 10013-1933Email: maggie.kline@future_electronics.comSSN: XXX-XX-XXXXDate May 23, 2003

Input record Output record

Data Cleansing examples : Product Data (Universal Data Cleanse)

Description

Kallkyle screw

test steel plate 20 x 35 mm

wire 23.33 x 40.50 cm

34 x 60 mm steel plate

steel plate 34,0 60 mm

34.0 x 60,0 mm steel plate

34 x 60 mm steel plate?

plate

steel plate

Input Parsed output

Product Dimension Type Form

screw Kallkyle

plate 20x35 mm steel test

wire 23.33 x 40.50 cm

plate 34 x 60 mm steel

plate 34 x 60 mm steel

plate 34 x 60 mm steel

plate 34 X 60 mm steel

plate

plate steel

Matching and Consolidation example

Ms. Margaret Smith-Kline Ph.D.

Future Electronics

101 Avenue of the Americas

New York NY 10013-1933

maggie.kline@future_electronics.com

May 23, 2003

Name: Ms. Margaret Smith-Kline Ph.D.

Company name: Future Electronics Co. LLC

SSN: 001-12-4367

Purchase date: 5/23/2003

Address: 101 Avenue of the Americas

New York, NY 10013-1933

Latitude: 40.722970

Longitude: -74.005035

Fed code: 36061

Phone: (222) 922-9922

Email: maggie.kline@future_electronics.com

Inpu

t rec

ords

Consolidated record

Maggie Smith

Future Electronics Co. LLC

101 6th Ave.

Manhattan, NY 10012

maggie.kline@future_electronics.com

001-12-4367

Ms. Peg Kline

Future Elect. Co.

101 6th Ave.

New York NY 10013

001-12-4367

(222) 922-9922

5/23/03

Data Services in action

Profile

Access

Cleanse Validate

Deliver

1. Our vision of information management2. Data Services: One tool for data integration and data quality

management3. Metadata Management: Impact and lineage to prove trustworthiness

of your data4. Some data services use cases in an SAP environment5. Wrap-up

Agenda

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

© SAP 2008 /

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.

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

Metadata Management Architecture

Custom Attributes Annotations, Metapedia

ConsolidateIntegrate

Audit

Business Metadata

1. Our vision of information management2. Data Services: One tool for data integration and data quality

management3. Metadata Management: Impact and lineage to prove trustworthiness of

your data4. Some data services use cases in an SAP environment5. Wrap-up

Agenda

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 systemsNo extracts for external processing required

Virtually undetectable presence that provides:Global address correction and standardization Comprehensive duplicate detectionConvenient record searching

Supported versionsSAP CRM: Releases 4.0 and 5.0 SAP ERP Central Component: Release 5.0 and 6.0SAP R/3 4.6C

Examples

Potential Duplicates Identified!

Review the Corrected and Fielded Information

Scenario 2: Load SAP NetWeaver BW

SAP NetWeaver 7.0 Business Warehouse

DataSource

InfoSource

PSA

Reporting Layer (Architected Data Marts)

Business Transformation Layer Operational

Data S

tore

Data Propagation Layer

Harmonization Layer

Corp. Mem-

ory

Data Acquisition Layer

Data Services

Order Management

Get easy access to data stored in non-SAP sources

Replace database connectivity with Rapid Mart application understanding

Include data cleansing and validation rules before loading data

Standardize, correct, and enhanceMatch and consolidateValidate against validation rules before loading into SAP NetWeaver BI

Scenario 3: Data Migration for SAP

Traditional Steps

SAPERP

LEGACYSYSTEM(S) ?

Provisionof data

“Let’s cross the fingersand hope it loads …

It is crucial to identify the right partner with the right expertise for your data migration project.

But attention:Data migration is far from easy.

Lack of experienceMigration project plan is unrealisticData quality issues/lack of confidence in the data You need to extend the consultants time for the SAP ERP project

Why?

More than 80% of data migration projects run over time and/or over budget. Cost overruns average 30%. Time overruns average 41%.Bloor, 2007

80% of organizations … will underestimate the costs related to the data acquisition tasks by an average of 50 percentGartner, Data Warehouse Infrastructure for Growth and Change

Analysts

Upload

SAP Data Migration ServicesEnd-to-End Solution for Data Migration

SAPERP

LEGACYSYSTEM(S)

SAPDATA MIGRATION

SERVICESFrameworkTemplatesMethodologyToolsExpertise

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 projectIndustry-leading BusinessObjects Data Services platform benefits data migration and delivers many additional benefits in information management

Pre-built framework and tools reduce the need for custom scripts and deliver data insights more quickly and consistently

Engage business users early with better access to data quality and metricsThe right tools combined with the

right methodology and powerful expertise – That’s SAP Data

Migration Service

SAP Data Migration Framework Based on BusinessObjects Data Services

Data Governance Visualization

Project Management Summary MetricsTrack % quality and progress over time against projectmilestones

Business users/Data Steward reportsShow detailed data exceptions requiring resolution for each SAP Business Objects, e.g., Customer, including reconciliationexceptions

Migration Framework Staging

Cleanse, Harmonize, Reconcile

SAP Business Object Validation LibraryLibrary of DS objects to validate the data pre-load.The metrics created from this process drive the Data Governance Engine

XML, flat file

Oracle Apps, PeopleSoft, JDEdwards, Siebel

Legacy

Extract & transform to

SAP structures

SAP

SAP Load: XML, IDOC,

File

Post load reconciliation

BUSINESS

IT

Data Exceptions &

DQ Metrics

1. Our vision of information management2. Data Services: One tool for data integration and data quality

management3. Metadata Management: Impact and lineage to prove trustworthiness of

your data4. Some data services use cases in an SAP environment5. Wrap-up

Agenda

7 Key Points to Take Home

Data is spread throughout systems and applications in the enterpriseYou need a broad connectivity to all source systemsDon‘t 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 data quality issues

The quality of data will vary among source systemsStandardize, cleanse, and enrich data before loading into the target applications

Avoid duplicate dataFind 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 metadataMetadata gives insight in where the data comes from and how it was transformed

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