1 Introducing Enterprise Information Management

25

1.1 Defining Enterprise Information Management

25

1.1.1 Example of Information Flow through a Company

28

1.1.2 Types of Information Included in Enterprise Information Management

31

1.2 Common Use Cases for EIM

33

1.2.1 EIM for Operational Initiatives

33

1.2.2 EIM for Analytical Use Cases

35

1.2.3 EIM for Information Governance

36

1.3 Common Drivers for EIM

36

1.3.1 Operational Efficiency as a Driver of EIM

37

1.3.2 Information as an Organizational Asset

39

1.3.3 Compliance as a Driver of EIM

40

1.4 Impact of Big Data on EIM

41

1.5 SAP’s Strategy for EIM

43

1.6 Typical User Roles in EIM

44

1.7 Example Company: NeedsEIM Inc.

45

1.7.1 CFO Issues

46

1.7.2 Purchasing Issues

47

1.7.3 Sales Issues

47

1.7.4 Engineering and Contracts Issues

47

1.7.5 Information Management Challenges Facing NeedsEIM Inc.

47

1.8 Summary

48

2 Introducing Information Governance

49

2.1 Introduction to Information Governance

50

2.2 Evaluating and Developing Your Information Governance Needs and Resources

52

2.2.1 Evaluating Information Governance

53

2.2.2 Developing Information Governance

58

2.3 Optimizing Existing Infrastructure and Resources

59

2.4 Establishing an Information Governance Process: Examples

60

2.4.1 Example 1: Creating a New Reseller

62

2.4.2 Example 2: Supplier Registration

63

2.4.3 Example 3: Data Migration

66

2.5 Rounding Out Your Information Governance Process

70

2.5.1 The Impact of Missing Data

70

2.5.2 Gathering Metrics and KPIs to Show Success

72

2.5.3 Establish a Before-and-After View

76

2.6 Summary

76

3 Big Data with SAP HANA, Hadoop, and EIM

77

3.1 SAP HANA

77

3.1.1 Business Benefits of SAP HANA

78

3.1.2 Basics of SAP HANA

81

3.1.3 SAP HANA Components and Architecture

82

3.1.4 SAP HANA for Analytics and Business Intelligence

85

3.1.5 SAP HANA as an Application Platform

86

3.1.6 SAP Business Suite on SAP HANA

86

3.1.7 SAP HANA and the Cloud

87

3.2 SAP HANA and EIM

89

3.2.1 Data Modeling for SAP HANA

89

3.2.2 Data Provisioning for SAP HANA

89

3.2.3 Data Quality for SAP HANA

94

3.3 Big Data and Hadoop

96

3.3.1 The Rise of Hadoop

96

3.3.2 Introduction to Hadoop

98

3.3.3 Hadoop 2.0 Architecture: HDFS, YARN, and MapReduce

99

3.3.4 Hadoop Ecosystem

101

3.3.5 Enterprise Use Cases

105

3.3.6 Hadoop in the Enterprise: The Bottom Line

107

3.4 SAP HANA and Hadoop

109

3.4.1 The V’s: Volume, Variety, Velocity

109

3.4.2 SAP HANA: Designed for Enterprises

109

3.4.3 Hadoop as an SAP HANA Extension

109

3.5 EIM and Hadoop

110

3.5.1 ETL: Data Services and the Information Design Tool

111

3.5.2 Unsupported: Information Governance and Information Lifecycle Management

111

3.6 Summary

112

4 SAP’s Solutions for Enterprise Information Management

113

4.1 SAP PowerDesigner

115

4.2 SAP HANA Cloud Integration

118

4.2.1 SAP HANA Cloud Integration for Process Integration

119

4.2.2 SAP HANA Cloud Integration for Data Services

120

4.3 SAP Data Services

120

4.3.1 Basics of SAP Data Services

121

4.3.2 SAP Data Services Integration with SAP Applications

123

4.3.3 SAP Data Services Integration with Non-SAP Applications

127

4.3.4 Data Cleansing and Data Validation with SAP Data Services

128

4.3.5 Text Data Processing in SAP Data Services

130

4.4 SAP Replication Server

133

4.4.1 SAP Replication Server Use Cases

133

4.4.2 Basics of SAP Replication Server

134

4.4.3 Data Assurance

136

4.4.4 SAP Replication Server Integration with SAP Data Services and SAP PowerDesigner

136

4.5 SAP Data Quality Management, Version for SAP Solutions

137

4.6 SAP Information Steward

139

4.6.1 Data Profiling and Data Quality Monitoring

141

4.6.2 Cleansing Rules

143

4.6.3 Match Review

146

4.6.4 Metadata Analysis

147

4.6.5 Business Term Glossary

148

4.7 SAP NetWeaver Master Data Management and SAP Master Data Governance

149

4.7.1 SAP NetWeaver Master Data Management

150

4.7.2 SAP Master Data Governance

151

4.8 SAP Solutions for Enterprise Content Management

154

4.8.1 Overview of SAP’s ECM Solutions

156

4.8.2 SAP Extended Enterprise Content Management by OpenText

160

4.8.3 SAP Document Access by OpenText and SAP Archiving by OpenText

164

4.9 SAP Information Lifecycle Management

165

4.9.1 Retention Management

169

4.9.2 System Decommissioning

170

4.10 Information Governance in SAP

173

4.10.1 Information Governance Use Scenario Phasing

174

4.10.2 Technology Enablers for Information Governance

176

4.11 NeedsEIM Inc. and SAP’s Solutions for EIM

179

4.12 Summary

181

5 Rapid-Deployment Solutions for Enterprise Information Management

183

5.1 Rapid-Deployment Solutions for Data Migration

184

5.1.1 Introduction to Data Migration

185

5.1.2 Data Migration Rapid-Deployment Content

187

5.1.3 Getting Started with Rapid Data Migration Rapid-Deployment Content

189

5.1.4 SAP Accelerator for Data Migration by BackOffice Associates

196

5.2 Rapid-Deployment Solutions for Information Steward

197

5.2.1 Information Steward Rapid-Deployment Solution Content

198

5.2.2 Getting Started with Information Steward Rapid-Deployment Solution Content

201

5.3 Rapid-Deployment Solutions for Master Data Governance

203

5.3.1 Master Data Governance Rapid-Deployment Solution Content

204

5.3.2 Getting Started with SAP Master Data Governance Rapid-Deployment Solution Content

206

5.4 Summary

207

6 Practical Examples of EIM

209

6.1 EIM Architecture Recommendations and Experiences by Procter and Gamble

209

6.1.1 Principles of an EIM Architecture

210

6.1.2 Scope of an EIM Enterprise Architecture

212

6.1.3 Structured Data

213

6.1.4 The Dual Database Approach

214

6.1.5 Typical Information Lifecycle

216

6.1.6 Data Standards

220

6.1.7 Unstructured Data

221

6.1.8 Governance

223

6.1.9 Role of the Enterprise Information Architecture Organization

228

6.2 Managing Data Migration Projects to Support Mergers and Acquisitions

228

6.2.1 Scoping for a Data Migration Project

229

6.2.2 Data Migration Process Flow

231

6.2.3 Enrich the Data Using Dun and Bradstreet (D&B) with Data Services

236

6.3 Evolution of SAP Data Services at National Vision

236

6.3.1 Phase 1: The Enterprise Data Warehouse

236

6.3.2 Phase 2: Enterprise Information Architecture—Consolidating Source Data

238

6.3.3 Phase 3: Data Quality and the Customer Hub

239

6.3.4 Phase 4: Application Integration and Data Migration

242

6.3.5 Phase 5: Next Steps with Data Services

242

6.4 Recommendations for a Master Data Program

243

6.4.1 Common Enterprise Vision and Goals

243

6.4.2 Master Data Strategy

243

6.4.3 Roadmap and Operational Phases

244

6.4.4 Business Process Redesign and Change Management

244

6.4.5 Governance

244

6.4.6 Technology Selection

245

6.5 Recommendations for Using SAP Process Integration and SAP Data Services

246

6.5.1 A Common Data Integration Problem

246

6.5.2 A Data Integration Analogy

247

6.5.3 Creating Prescriptive Guidance to Help Choose the Proper Tool

248

6.5.4 Complex Examples in the Enterprise

249

6.5.5 When All Else Fails…

250

6.6 Ensuring a Successful Enterprise Content Management Project by Belgian Railways

251

6.6.1 Building the Business Case

251

6.6.2 Key Success Factors for Your SAP Extended Enterprise Content Management by OpenText Project

257

6.7 Recommendations for Creating an Archiving Strategy

261

6.7.1 What Drives a Company into Starting a Data Archiving Project?

261

6.7.2 Who Initiates a Data Archiving Project?

262

6.7.3 Project Sponsorship

263

6.8 Summary

266

7 SAP PowerDesigner

269

7.1 SAP PowerDesigner in the SAP Landscape

270

7.1.1 SAP Business Suite

270

7.1.2 SAP HANA Cloud Platform

270

7.1.3 SAP Information Steward, SAP BusinessObjects Universes, and Replication

270

7.2 Defining and Describing Business Information with the Enterprise Glossary

271

7.2.1 Glossary Terms for Naming Standards Enforcement

272

7.2.2 Naming Standards Definitions

273

7.3 The Conceptual Data Model

273

7.3.1 Conceptual Data Elements, Attributes, and Data Items

274

7.3.2 Separation of Domains, Data Items, and Entity Attributes

275

7.3.3 Entity Relationships

275

7.3.4 Best Practices for Building and Maintaining an Enterprise CDM

276

7.4 Detailing Information Systems with Logical and Physical Data Models

278

7.4.1 Scope

278

7.4.2 Structure and Technical Considerations

279

7.5 Canonical Data Models, XML Structures, and Other Datastores

280

7.6 Data Warehouse Modeling: Movement and Reporting

282

7.7 Link and Sync for Impact Analysis and Change Management

284

7.7.1 Link and Sync Technology

284

7.7.2 Impact Analysis Reporting

287

7.8 Comparing Models

288

7.9 Summary

290

8 SAP HANA Cloud Integration

291

8.1 SAP HANA Cloud Integration Architecture

292

8.1.1 SAP HANA Cloud Platform

294

8.1.2 Customer Environment On-Premise

294

8.1.3 SAP HANA Cloud Integration User Experience

295

8.2 Getting Started with SAP HANA Cloud Integration

297

8.2.1 Blueprinting Phase

297

8.2.2 Predefined Templates

298

8.2.3 Setting Up Your HCI Tenant

299

8.2.4 Setting Up Your Datastore

300

8.2.5 Creating a New Project

301

8.2.6 Moving a Task from a Sandbox to a Production Environment

304

8.3 Summary

305

9 SAP Data Services

307

9.1 Data Integration Scenarios

307

9.2 SAP Data Services Platform Architecture

309

9.2.1 User Interface Tier

310

9.2.2 Server Tier

313

9.3 SAP Data Services Designer Overview

314

9.4 Creating Data Sources and Targets

318

9.4.1 Connectivity Options for SAP Data Services

318

9.4.2 Connecting to SAP

321

9.4.3 Connecting to Hadoop

323

9.5 Creating Your First Job

324

9.5.1 Create the Data Flow

324

9.5.2 Add a Source to the Data Flow

325

9.5.3 Add a Query Transform to the Data Flow

325

9.5.4 Add a Target to the Data Flow

325

9.5.5 Map the Source Data to the Target by Configuring the Query Transform

326

9.5.6 Create the Job and Add the Data Flow to the Job

327

9.6 Basic Transformations Using the Query Transform and Functions

327

9.7 Overview of Complex Transformations

330

9.7.1 Platform Transformations

330

9.7.2 Data Integrator Transforms

332

9.8 Executing and Debugging Your Job

336

9.9 Exposing a Real-Time Service

337

9.9.1 Create a Real-Time Job

338

9.9.2 Create a Real-Time Service

340

9.9.3 Expose the Real-Time Service as a Web Service

342

9.10 Data Quality Management

343

9.10.1 Data Cleansing

345

9.10.2 Data Enhancement

366

9.10.3 Data Matching

369

9.10.4 Using Data Quality beyond Customer Data

386

9.11 Text Data Processing

388

9.11.1 Introduction to Text Data Processing Capabilities in SAP Data Services

389

9.11.2 Entity Extraction Transform Overview

391

9.11.3 How Extraction Works

392

9.11.4 Text Data Processing and NeedsEIM Inc.

394

9.11.5 NeedsEIM Inc. Pain Points

394

9.11.6 Using the Entity Extraction Transform

396

9.12 Summary

403

10 SAP Information Steward

405

10.1 Cataloging Data Assets and Their Relationships

406

10.1.1 Configuring a Metadata Integrator Source

407

10.1.2 Executing or Scheduling Execution of Metadata Integration

409

10.2 Establishing a Business Term Glossary

410

10.3 Profiling Data

413

10.3.1 Configuration and Setup of Connections and Projects

414

10.3.2 Getting Basic Statistical Information about the Data Content

417

10.3.3 Identifying Cross-Field or Cross-Column Data Relationships

422

10.4 Assessing the Quality of Your Data

425

10.4.1 Defining Validation Rules Representing Business Requirements

427

10.4.2 Binding Rules to Data Sources for Data Quality Assessment

431

10.4.3 Executing Rule Tasks and Viewing Results

433

10.5 Monitoring with Data Quality Scorecards

437

10.5.1 Components of a Data Quality Scorecard

439

10.5.2 Defining and Setting Up a Data Quality Scorecard

441

10.5.3 Viewing the Data Quality Scorecard

448

10.5.4 Identifying Data Quality Impact and Root Cause

452

10.5.5 Performing Business Value Analysis

454

10.6 Quick Starting Data Quality

461

10.6.1 Assess the Data Using Column, Advanced, and Content Type Profiling

462

10.6.2 Receive Validation and Cleansing Rule Recommendations

462

10.6.3 Tune the Cleansing and Matching Rules Using Data Cleansing Advisor

464

10.6.4 Publish the Cleansing Solution

465

10.7 Summary

465

11 SAP Master Data Governance

467

11.1 SAP Master Data Governance Overview

468

11.1.1 Deployment Options

470

11.1.2 Change Request and Staging

471

11.1.3 Process Flow in SAP Master Data Governance

473

11.1.4 Use of SAP HANA in SAP MDG

475

11.2 Getting Started with SAP Master Data Governance

476

11.2.1 Data Modeling

476

11.2.2 User Interface Modeling

478

11.2.3 Data Quality and Search

478

11.2.4 Process Modeling

480

11.2.5 Data Replication

481

11.2.6 Key and Value Mapping

481

11.2.7 Data Transfer

483

11.2.8 Activities beyond Customizing

483

11.3 Governance for Custom-Defined Objects: Example

484

11.3.1 Plan and Create Data Model

484

11.3.2 Define User Interface

489

11.3.3 Create a Change Request Process

494

11.3.4 Assign Processors to the Workflow

495

11.3.5 Test the New Airline Change Request User Interface

496

11.4 Rules-Based Workflows in SAP Master Data Governance

497

11.4.1 Classic Workflow and Rules-Based Workflow Using SAP Business Workflow and BRFplus

498

11.4.2 Designing Your First Rules-Based Workflow in SAP Master Data Governance

505

11.5 NeedsEIM Inc.: Master Data Remediation

508

11.6 Summary

511

12 SAP Information Lifecycle Management

513

12.1 The Basics of Information Lifecycle Management

515

12.1.1 External Drivers

516

12.1.2 Internal Drivers

516

12.2 Overview of SAP Information Lifecycle Management

516

12.2.1 Cornerstones of SAP ILM

517

12.2.2 Data Archiving Basics

518

12.2.3 ILM-Aware Storage

523

12.2.4 Architecture Required to Run SAP ILM

527

12.3 Managing the Lifecycle of Information in Live Systems

529

12.3.1 Audit Area

529

12.3.2 Data Destruction

532

12.3.3 Legal Hold Management

532

12.4 Managing the Lifecycle of Information from Legacy Systems

534

12.4.1 Preliminary Steps

534

12.4.2 Steps Performed in the Legacy System

536

12.4.3 Steps Performed in the Retention Warehouse System

537

12.4.4 Handling Data from Non-SAP Systems During Decommissioning

539

12.4.5 Streamlined System Decommissioning and Reporting

539

12.5 System Decommissioning: Detailed Example

542

12.5.1 Data Extraction

543

12.5.2 Data Transfer and Conversion

548

12.5.3 Reporting

555

12.5.4 Data Destruction

559

12.6 Summary

562

13 SAP Extended Enterprise Content Management by OpenText

563

13.1 Capabilities of SAP Extended ECM

565

13.1.1 Data and Document Archiving

566

13.1.2 Records Management

567

13.1.3 Content Access

568

13.1.4 Document-Centric Workflow

568

13.1.5 Document Management

568

13.1.6 Capture

569

13.1.7 Collaboration and Social Media

569

13.2 How SAP Extended ECM Works with the SAP Business Suite

570

13.3 Integration Content for SAP Business Suite and SAP Extended ECM

572

13.3.1 SAP ArchiveLink

572

13.3.2 Content Management Interoperability Standard and SAP ECM Integration Layer

574

13.3.3 SAP Extended ECM Workspaces

575

13.4 Summary

582