Table of Contents

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Introduction
17
Part I: SAP’s Enterprise Information Management Strategy and Portfolio
23
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
Part II: Working with SAP’s Enterprise Information Management Solutions
267
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