Veremos el concepto de Enterprise Information Management (EIM), y presentamos un libro de SAP Press que proporciona ejemplos de cómo se utilizan las soluciones EIM de SAP en la actualidad y ofrecer instrucciones técnicas sobre cómo realizar algunas de las tareas EIM más comunes en SAP.
La segunda edición incluye actualizaciones de los capítulos sobre SAP Data Services, SAP HANA, SAP Information Steward, SAP Master Data Governance, SAP Information Lifecycle Management y SAP Extended Enterprise Content Management de OpenText, que se basan en versiones recientes, así como algunas novedades. capítulos sobre soluciones SAP Rapid Deployment, SAP PowerDesigner y SAP Hana Cloud Integration.
Una breve introducción
Cloud, big data y las redes sociales están generando nuevas oportunidades para las empresas que pueden aprovechar los conocimientos basados en información en tiempo real para responder a las preferencias de los clientes, identificar eficiencias operativas y, en algunos casos, crear modelos de negocios completamente nuevos.
Para lograr resultados empresariales transformadores, las empresas mejor administradas tratan la información como un activo corporativo. Se maneja con cuidado, se gobierna cuidadosamente, se usa estratégicamente y se controla sensiblemente.
La gestión eficaz de la información empresarial puede ayudar a que su organización funcione más rápido. Como resultado, puede lograr nuevos resultados comerciales:
- comprender y retener a sus clientes,
- aprovechar al máximo sus proveedores,
- garantizar el cumplimiento sin aumentar su riesgo y
- brindar transparencia interna para impulsar las decisiones operativas y estratégicas
SAP ayuda a las empresas a funcionar mejor y de manera más simple al permitir que la IT administre y optimice más fácilmente la información empresarial. Las soluciones SAP para la Gestión de la Información Empresarial (EIM) proporcionan las capacidades críticas para diseñar, integrar, mejorar, gestionar, asociar y archivar toda la información.
En este artículo hablaremos entonces sobre EIM y explicaremos qué es, por qué es importante para las organizaciones, cómo encaja en la estrategia de SAP y algunos roles de usuario típicos.
Qué es EIM
Ya habíamos hablado sobre EIM en nuestro artículo de Consultoria-SAP: "qué es SAP EIM".
La Gestión de la información empresarial se define como "una disciplina integradora para estructurar, describir y gobernar los activos de información a través de los límites organizativos y tecnológicos para mejorar la eficiencia, promover la transparencia y permitir la visión empresarial".
EIM implica una ejecución estratégica y gobernada de las siguientes disciplinas:
- empresa,
- arquitectura,
- integración de datos,
- calidad de los datos,
- gestión de datos maestros,
- contenido,
- administración,
- y gestión del ciclo de vida.
Aborda la gestión de todo tipo de información, incluidos datos estructurados tradicionales, datos semiestructurados y no estructurados, y contenido como documentos, correos electrónicos, audio, video, etc.
Para optimizar el uso y el costo de administrar la información, primero debemos entender su ciclo de vida. La gestión activa y el gobierno de la información ayudan a evitar los costos asociados con el acaparamiento de información a ciegas. El riesgo de tener demasiada información es tan real como no tener suficiente cuando la necesita.
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Contenido del libro Enterprise Information Management with SAP
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 .
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
The Authors . 583
Index. 591
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 .
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
The Authors . 583
Index. 591
