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Art of Enterprise Information Architecture, The

Art of Enterprise Information Architecture, The

A Systems-Based Approach for Unlocking Business Insight

Mario Godinez, Eberhard Hechler, Klaus Koenig, Steve Lockwood, Martin Oberhofer, Michael Schroeck

Apr 2010, Paperback, 480 pages
ISBN13: 9780137035717
ISBN10: 0137035713
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Architecture for the Intelligent Enterprise: Powerful New Ways to Maximize the Real-time Value of Information

Tomorrow’s winning “Intelligent Enterprises” will bring together far more diverse sources of data, analyze it in more powerful ways, and deliver immediate insight to decision-makers throughout the organization. Today, however, most companies fail to apply the information they already have, while struggling with the complexity and costs of their existing information environments.

In this book, a team of IBM’s leading information management experts guide you on a journey that will take you from where you are today toward becoming an “Intelligent Enterprise.”

Drawing on their extensive experience working with enterprise clients, the authors present a new, information-centric approach to architecture and powerful new models that will benefit any organization. Using these strategies and models, companies can systematically unlock the business value of information by delivering actionable, real-time information in context to enable better decision-making throughout the enterprise–from the “shop floor” to the “top floor.”

Coverage Includes

  • Highlighting the importance of Dynamic Warehousing
  • Defining your Enterprise Information Architecture from conceptual, logical, component, and operational views
  • Using information architecture principles to integrate and rationalize your IT investments, from Cloud Computing to Information Service Lifecycle Management
  • Applying enterprise Master Data Management (MDM) to bolster business functions, ranging from compliance and risk management to marketing and product management
  • Implementing more effective business intelligence and business performance optimization, governance, and security systems and processes
  • Understanding “Information as a Service” and “Info 2.0,” the information delivery side of Web 2.0

Architecture for the Intelligent Enterprise: Powerful New Ways to Maximize the Real-time Value of Information

Tomorrow’s winning “Intelligent Enterprises” will bring together far more diverse sources of data, analyze it in more powerful ways, and deliver immediate insight to decision-makers throughout the organization. Today, however, most companies fail to apply the information they already have, while struggling with the complexity and costs of their existing information environments.

In this book, a team of IBM’s leading information management experts guide you on a journey that will take you from where you are today toward becoming an “Intelligent Enterprise.”

Drawing on their extensive experience working with enterprise clients, the authors present a new, information-centric approach to architecture and powerful new models that will benefit any organization. Using these strategies and models, companies can systematically unlock the business value of information by delivering actionable, real-time information in context to enable better decision-making throughout the enterprise–from the “shop floor” to the “top floor.”

Coverage Includes

  • Highlighting the importance of Dynamic Warehousing
  • Defining your Enterprise Information Architecture from conceptual, logical, component, and operational views
  • Using information architecture principles to integrate and rationalize your IT investments, from Cloud Computing to Information Service Lifecycle Management
  • Applying enterprise Master Data Management (MDM) to bolster business functions, ranging from compliance and risk management to marketing and product management
  • Implementing more effective business intelligence and business performance optimization, governance, and security systems and processes
  • Understanding “Information as a Service” and “Info 2.0,” the information delivery side of Web 2.0

Foreword by Ron Tolido xix

Foreword by Dr. Kristof Kloeckner xxi

Preface xxiii

Acknowledgments xxix

About the Authors xxxi

Chapter 1 The Imperative for a New Approach to Information Architecture 1

1.1 External Forces: A New World of Volume, Variety, and Velocity 3

1.1.1 An Increasing Volume of Information 3

1.1.2 An Increasing Variety of Information 4

1.1.3 An Increasing Velocity of Information 4

1.2 Internal Information Environment Challenges 5

1.3 The Need for a New Enterprise Information Architecture 5

1.3.1 Leading the Transition to a Smarter Planet 6

1.4 The Business Vision for the Information-Enabled Enterprise 7

1.5 Building an Enterprise Information Strategy and the Information Agenda 12

1.5.1 Enterprise Information Strategy 13

1.5.2 Organizational Readiness and Information Governance 15

1.5.3 Information Infrastructure 16

1.5.4 Information Agenda Blueprint and Roadmap 17

1.6 Best Practices in Driving Enterprise Information Planning Success 19

1.6.1 Aligning the Information Agenda with Business Objectives 19

1.6.2 Getting Started Smartly 19

1.6.3 Maintaining Momentum 20

1.6.4 Implementing the Information Agenda 20

1.7 Relationship to Other Key Industry and IBM Concepts 20

1.8 The Roles of Business Strategy and Technology 22

1.9 References 22

Chapter 2 Introducing Enterprise Information Architecture 23

2.1 Terminology and Definitions 23

2.1.1 Enterprise Architecture 25

2.1.2 Conceptual Approach to EAI Reference Architecture 27

2.2 Methods and Models 36

2.2.1 Architecture Methodology 36

2.2.2 Information Maturity Model 38

2.3 Enterprise Information Architecture Reference Architecture in Context 41

2.3.1 Information On Demand 41

2.3.2 Information Agenda Approach 42

2.3.3 The Open Group Architecture Framework 44

2.3.4 Service-Oriented Architecture and Information as a Service 47

2.4 Conclusion 50

2.5 References 51

Chapter 3 Data Domains, Information Governance, and Information Security 53

3.1 Terminology and Definitions 53

3.2 Data Domains 55

3.2.1 Classification Criteria of the Conceptual Data Model 56

3.2.2 The Five Data Domains 60

3.2.3 Information Reference Model 63

3.3 IT Governance and Information Governance 64

3.4 Information Security and Information Privacy 67

3.4.1 Information Security 67

3.4.2 Information Privacy: The Increasing Need for Data Masking 70

3.5 System Context Diagram 74

3.7 References 74

Chapter 4 Enterprise Information Architecture: A Conceptual and Logical View 77

4.1 Conceptual Architecture Overview 77

4.1.1 Metadata Management Capability 79

4.1.2 Master Data Management Capability 79

4.1.3 Data Management Capability 80

4.1.4 Enterprise Content Management Capability 80

4.1.5 Analytical Applications Capability 81

4.1.6 Business Performance Management Capability 82

4.1.7 Enterprise Information Integration Capability 82

4.1.8 Mashup Capability 85

4.1.9 Information Governance Capability 85

4.1.10 Information Security and Information Privacy Capability 86

4.1.11 Cloud Computing Capability 86

4.2 EIA Reference Architecture–Architecture Overview Diagram 88

4.3 Architecture Principles for the EIA 90

4.4 Logical View of the EIA Reference Architecture 98

4.4.1 IT Services & Compliance Management Services Layer 99

4.4.2 Enterprise Information Integration Services 99

4.4.3 Information Services 99

4.4.4 Presentation Services and Delivery Channels 101

4.4.5 Information Security and Information Privacy 101

4.4.6 Connectivity and Interoperability 101

4.4.7 Business Process Orchestration and Collaboration 101

4.5 Conclusion 102

4.6 References 102

Chapter 5 Enterprise Information Architecture: Component Model 103

5.1 The Component Model 103

5.2 Component Relationship Diagram 105

5.3 Component Description 105

5.3.1 Delivery Channels and External Data Providers 106

5.3.2 Infrastructure Security Component 108

5.3.3 Presentation Services 109

5.3.4 Service Registry and Repository 112

5.3.5 Business Process Services 112

5.3.6 Collaboration Services 113

5.3.7 Connectivity and Interoperability Services 113

5.3.8 Directory and Security Services 114

5.3.9 Operational Applications 114

5.3.10 Mashup Hub 116

5.3.11 Metadata Management Component and Metadata Services 119

5.3.12 Master Data Management Component and MDM Services 121

5.3.13 Data Management Component and Data Services 124

5.3.14 Enterprise Content Management Component and Content Services 129

5.3.15 Analytical Applications Component and Analytical Services 131

5.3.16 Enterprise Information Integration Component and EII Services 134

5.3.17 IT Service & Compliance Management Services 138

5.4 Component Interaction Diagrams–A Deployment Scenario 139

5.4.1 Business Context 139

5.4.2 Component Interaction Diagram 141

5.4.3 Alternatives and Extensions 144

5.5 Conclusion 144

5.6 References 144

Chapter 6 Enterprise Information Architecture: Operational Model 147

6.1 Terminology and Definitions 147

6.1.1 Definition of Operational Model Levels 148

6.1.2 Terms of Operational Aspect 149

6.1.3 Key Design Concepts within Operational Modeling 149

6.2 Context of Operational Model Design Techniques 150

6.3 Service Qualities 152

6.3.1 Example of Operational Service Qualities 152

6.3.2 Relevance of Service Qualities per Data Domain 155

6.4 Standards Used for the Operational Model Relationship Diagram 155

6.4.1 Basic Location Types 155

6.4.2 Inter-Location Border Types 158

6.4.3 Access Mechanisms 158

6.4.4 Standards of Specified Nodes 158

6.4.5 Logical Operational Model Relationship Diagram 167

6.5 Framework of Operational Patterns 168

6.5.1 The Context of Operational Patterns 169

6.5.2 Near-Real-Time Business Intelligence Pattern 169

6.5.3 Data Integration and Aggregation Runtime Pattern 175

6.5.4 ESB Runtime for Guaranteed Data Delivery Pattern 176

6.5.5 Continuous Availability and Resiliency Pattern 179

6.5.6 Multi-Tier High Availability for Critical Data Pattern 181

6.5.7 Content Resource Manager Service Availability Pattern 184

6.5.8 Federated Metadata Pattern 185

6.5.9 Mashup Runtime and Security Pattern 186

6.5.10 Compliance and Dependency Management for Operational Risk Pattern 187

6.5.11 Retention Management Pattern 189

6.5.12 Encryption and Data Protection Pattern 191

6.5.13 File System Virtualization Pattern 194

6.5.14 Storage Pool Virtualization Pattern 195

6.5.15 Automated Capacity and Provisioning Management Pattern 195

6.6 Conclusion 198

6.7 References 198

Chapter 7 New Delivery Models: Cloud Computing 201

7.1 Definitions and Terms 201

7.2 Cloud Computing as Convergence of IT Principles 202

7.2.1 Key Drivers to Cloud Computing 203

7.2.2 Evolution to Cloud Computing 204

7.3 Cloud Computing as a New Paradigm 205

7.3.1 Typical Service Layers in Cloud Computing 205

7.3.2 The Nature of Cloud Computing Environments 207

7.4 Implication of Cloud Computing to Enterprise Information Services 209

7.4.1 Multi-Tenancy 209

7.4.2 Relevant Capabilities of EIS in a Cloud Environment 214

7.5 Cloud Computing–Architecture and Services Exploration 215

7.6 Business Scenario with Cloud Computing 216

7.6.1 Business Context 216

7.6.2 Component Interaction Diagram 217

7.7 Conclusion 221

7.8 References 221

Chapter 8 Enterprise Information Integration 223

8.1 Enterprise Information Integration–Terms, History, and Scope 223

8.2 Discover 224

8.2.1 Discover Capabilities 224

8.2.2 Discover Scenario 227

8.3 Profile 228

8.3.1 Profile Capabilities 228

8.3.2 Profile Scenario 230

8.4 Cleanse 232

8.4.1 Cleanse Capabilities 232

8.4.2 Cleanse Scenario 235

8.5 Transform 236

8.5.1 Transform Capabilities 236

8.5.2 Transform Scenario 237

8.6 Replicate 239

8.6.1 Replicate Capabilities 239

8.6.2 Replication Scenario 242

8.7 Federate 244

8.7.1 Federate Capabilities 244

8.7.2 Federation Scenario 246

8.8 Data Streaming 247

8.8.1 Data Streaming Capabilities 247

8.8.2 Data Streaming Scenario 251

8.9 Deploy 253

8.9.1 Deploy Capabilities 253

8.9.2 Deploy Scenario 254

8.10 Conclusion 256

8.11 References 256

Chapter 9 Intelligent Utility Networks 257

9.1 Business Scenarios and Use Cases of the IUN 258

9.1.1 Increasing Issues Concerning Electrical Energy 258

9.1.2 The Demand for New Business Models 259

9.1.3 Typical Use Cases 261

9.2 Architecture Overview Diagram 263

9.3 The Logical Component Model of the IUN 265

9.3.1 Power Grid Infrastructure 266

9.3.2 Data Transport Network and Communication 266

9.3.3 Enterprise Information Integration (EII) Services 267

9.3.4 Remote Meter Management and Access Services 268

9.3.5 Automated Billing and Meter Data Management 268

9.3.6 Enterprise Asset Management 268

9.3.7 Work Order Entry Component and Mobile Workforce Management 268

9.3.8 Customer Information and Insight with Portal Services 269

9.3.9 Outage Management System 269

9.3.10 Predictive and Advanced Analytical Services 269

9.3.11 Geographic Information System (GIS) 270

9.4 Component Interaction Diagram 270

9.4.1 Component Interaction Diagram: Smart Metering and Data Integration 271

9.4.2 Component Interaction Diagram: Asset and Location Mashup Services 272

9.4.3 Component Interaction Diagram: PDA Data Replication Services 273

9.5 Service Qualities for IUN Solutions 274

9.5.1 Functional Service Qualities 274

9.5.2 Operational Service Qualities 275

9.5.3 Security Management Qualities 275

9.5.4 Maintainability Qualities 276

9.6 Applicable Operational Patterns 277

9.7 Conclusion 278

9.8 References 279

Chapter 10 Enterprise Metadata Management 281

10.1 Metadata Usage Maturity Levels 281

10.2 Terminology and Definitions 282

10.2.1 EIA Metadata Definition 283

10.2.2 What Is Metadata Management? 287

10.2.3 End-to-End Metadata Management 289

10.3 Business Scenarios 289

10.3.1 Business Patterns 289

10.3.2 Use Case Scenarios 290

10.4 Component Deep Dive 291

10.4.1 Component Model Introduction 291

10.4.2 Component Descriptions 292

10.4.3 Component Relationship Diagrams 293

10.5 Component Interaction Diagram–Deployment Scenario 294

10.5.1 Business Context 295

10.5.2 Component Interaction Diagram 295

10.6 Service Qualities for Metadata Management 298

10.7 Applicable Operational Patterns 300

10.8 IBM Technology Mapping 302

10.8.1 IBM Technology Overview 302

10.8.2 Scenario Description Using IBM Technology 303

10.9 Conclusion 305

10.10 References 306

Chapter 11 Master Data Management 307

11.1 Introduction and Terminology 307

11.1.1 Registry Implementation Style 308

11.1.2 Coexistence Implementation Style 309

11.1.3 Transactional Hub Implementation Style 309

11.1.4 Comparison of the Implementation Styles 310

11.1.5 Importance of Information Governance for MDM 311

11.2 Business Scenarios 311

11.3 Component Deep Dive 313

11.3.1 Interface Services 314

11.3.2 Lifecycle Management 314

11.3.3 Hierarchy and Relationship Management Services 315

11.3.4 MDM Event Management Services 316

11.3.5 Authoring Services 316

11.3.6 Data Quality Management Services 316

11.3.7 Base Services 317

11.4 Component Interaction Diagram 318

11.5 Service Qualities 323

11.5.1 MDM Security 323

11.5.2 Privacy 325

11.6 Applicable Operational Patterns 326

11.7 Conclusion 327

11.8 References 328

Chapter 12 Information Delivery in a Web 2.0 World 329

12.1 Web 2.0 Introduction to Mashups 329

12.2 Business Drivers 330

12.2.1 Information Governance and Architectural Considerations for Mashups 335

12.3 Architecture Overview Diagram 336

12.4 Component Model Diagram 338

12.5 Component Interaction Diagrams 340

12.5.1 Component Interaction Diagrams–Deployment Scenarios 343

12.6 Service Qualities for Mashup Solutions 345

12.7 Mashup Deployment–Applicable Operational Patterns 349

12.7.1 Scenario 1: Simple Deployment Model 349

12.7.2 Scenario 2: High Availability Model 350

12.7.3 Scenario 3: Near-Real-Time Model 353

12.8 IBM Technologies 354

12.8.1 Lotus Mashups 355

12.8.2 InfoSphere Mashup Hub 355

12.8.3 WebSphere sMash 355

12.9 Conclusion 356

12.10 References 357

Chapter 13 Dynamic Warehousing 359

13.1 Infrastructure for Dynamic Warehousing 360

13.1.1 Dynamic Warehousing: Extending the Traditional Data Warehouse Approach 361

13.2 Business Scenarios and Patterns 370

13.2.1 Practical Business Applications 371

13.3 Component Interaction Diagrams–Deployment Scenarios 372

13.3.1 Dynamic Pricing in the Financial Industry 372

13.3.2 Addressing Customer Attrition/Churn 377

13.4 Conclusion 381

13.5 References 381

Chapter 14 New Trends in Business Analytics and Optimization 383

14.1 A New Approach to Business Performance Management 384

14.1.1 A Framework for Business Analytics and Business Optimization 385

14.1.2 Performance Metrics 387

14.2 Business Scenario, Business Patterns, and Use Case 387

14.2.1 Banking Use Case 388

14.3 Component Interaction Diagrams–Deployment Scenarios 389

14.3.1 Predictive Analytics in Health Care 390

14.3.2 Optimizing Decisions in Banking and Financial Services–Trading 394

14.3.3 Improved ERM for Banking and Financial Services 397

14.4 Conclusion 402

14.5 References 403

Glossary 405

Index 415

Appendixes can be found online at www.ibmpressbooks.com/artofeia

Appendix A: Software Product Mapping 1

Appendix B: Standards and Specifications 19

Appendix C: Regulations 33

Mario Godinez, Executive IT Architect and IBM Senior Certified IT Architect (SCITA) within IBM’s Worldwide Information On Demand Architecture team, has spent 15+ years helping IBM customers architect and implement complex enterprise solutions.

Eberhard Hechler is an IBM Executive IT Architect and SCITA within the IBM Information Management Advanced Engagement Team and a member of the IBM Academy of Technology.

Klaus Koenig, an IBM Distinguished Engineer, leads major IBM initiatives in Cloud Computing, Green IT, service lifecycle management, and IT process automation.

Steve Lockwood works in the IBM Software Group as an Executive Architect and IBM SCITA and has 20 years experience in building information-related solutions.

Martin Oberhofer works in the IBM Software Group as an Architect for Enterprise Information Architecture with clients worldwide.

Michael Schroeck, a partner and the Global Business Intelligence (BI) and Information on Demand (IOD) Leader for IBM, Global Business Services, specializes in designing and implementing large, complex BI/IOD solutions.

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