Data Warehousing Fundamentals for IT Professionals, Second Edition
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Data warehousing has revolutionized the way businesses in a wide variety of industries perform analysis and make strategic decisions. Since the first edition of Data Warehousing Fundamentals, numerous enterprises have implemented data warehouse systems and reaped enormous benefits. Many more are in the process of doing so. Now, this new, revised edition covers the essential fundamentals of data warehousing and business intelligence as well as significant recent trends in the field.

The author provides an enhanced, comprehensive overview of data warehousing together with in-depth explanations of critical issues in planning, design, deployment, and ongoing maintenance. IT professionals eager to get into the field will gain a clear understanding of techniques for data extraction from source systems, data cleansing, data transformations, data warehouse architecture and infrastructure, and the various methods for information delivery.

This practical Second Edition highlights the areas of data warehousing and business intelligence where high-impact technological progress has been made. Discussions on developments include data marts, real-time information delivery, data visualization, requirements gathering methods, multi-tier architecture, OLAP applications, Web clickstream analysis, data warehouse appliances, and data mining techniques. The book also contains review questions and exercises for each chapter, appropriate for self-study or classroom work, industry examples of real-world situations, and several appendices with valuable information.

Specifically written for professionals responsible for designing, implementing, or maintaining data warehousing systems, Data Warehousing Fundamentals presents agile, thorough, and systematic development principles for the IT professional and anyone working or researching in information management.


PAULRAJ PONNIAH, PHD, with over thirty years of experience as an IT consultant, has worked with such organizations as Texaco, Sotheby's, Blue Cross/Blue Shield, NA Philips, New York-Presbyterian Hospital, Panasonic, and Bantam Doubleday Dell. He specializes in the design and implementation of data warehouse and database systems. Dr. Ponniah has published three successful books and, as Adjunct Professor, continues to teach college courses in data warehousing and database design.


Preface xxv

Part 1 Overview and Concepts 1

1 The Compelling Need For Data Warehousing 3

Chapter Objectives 3

Escalating Need For Strategic Information 4

Failures of Past Decision-Support Systems 9

Operational Versus Decision-Support Systems 11

Data Warehousing—The Only Viable Solution 13

A Simple Concept For Information Delivery 15

The Data Warehousing Movement 17

Evolution of Business Intelligence 18

Chapter Summary 20

Review Questions 20

Exercises 21

2 Data Warehouse: The Building Blocks 23

Chapter Objectives 23

Defining Features 24

Data Warehouses and Data Marts 29

Architectural Types 32

Overview of The Components 34

Metadata in The Data Warehouse 41

Chapter Summary 42

Review Questions 43

Exercises 43

3 Trends in Data Warehousing 45

Chapter Objectives 45

Continued Growth in Data Warehousing 46

Significant Trends 50

Emergence of Standards 64

Web-Enabled Data Warehouse 66

Chapter Summary 69

Review Questions 69

Exercises 70

Part 2 Planning and Requirements 71

4 Planning and Project Management 73

Chapter Objectives 73

Planning Your Data Warehouse 74

The Data Warehouse Project 79

The Development Phases 83

The Project Team 85

Project Management Considerations 90

Chapter Summary 96

Review Questions 96

Exercises 97

5 Defining The Business Requirements 99

Chapter Objectives 99

Dimensional Analysis 100

Information Packages—A Useful Concept 103

Requirements Gathering Methods 109

Requirements Definition: Scope and Content 116

Chapter Summary 119

Review Questions 119

Exercises 120

6 Requirements As The Driving Force For Data Warehousing 121

Chapter Objectives 121

Data Design 122

The Architectural Plan 125

Data Storage Specifications 131

DBMS Selection 132

Information Delivery Strategy 133

Chapter Summary 136

Review Questions 136

Exercises 137

Part 3 Architecture and Infrastructure 139

7 Architectural Components 141

Chapter Objectives 141

Understanding Data Warehouse Architecture 141

Distinguishing Characteristics 143

Architectural Framework 146

Technical Architecture 148

Architectural Types 156

Chapter Summary 160

Review Questions 160

Exercises 161

8 Infrastructure As The Foundation For Data Warehousing 163

Chapter Objectives 163

Infrastructure Supporting Architecture 164

Hardware and Operating Systems 166

Database Software 181

Collection of Tools 184

 Data Warehouse Appliances 188

Chapter Summary 191

Review Questions 191

Exercises 192

9 The Significant Role of Metadata 193

Chapter Objectives 193

Why Metadata Is Important 193

Metadata Types By Functional Areas 203

Business Metadata 207

Technical Metadata 209

How To Provide Metadata 212

Chapter Summary 219

Review Questions 220

Exercises 220

Part 4 Data Design and Data Preparation 223

10 Principles of Dimensional Modeling 225

Chapter Objectives 225

From Requirements To Data Design 225

The Star Schema 232

Star Schema Keys 239

Advantages of The Star Schema 241

Star Schema: Examples 244

Chapter Summary 246

Review Questions 247

Exercises 247

11 Dimensional Modeling: Advanced Topics 249

Chapter Objectives 249

Updates To The Dimension Tables 250

Miscellaneous Dimensions 255

The Snowflake Schema 259

Aggregate Fact Tables 262

Families of Stars 272

Chapter Summary 277

Review Questions 278

Exercises 278

12 Data Extraction, Transformation, and Loading 281

Chapter Objectives 281

ETL Overview 282

ETL Requirements and Steps 284

Data Extraction 286

Data Transformation 295

Data Loading 302

ETL Summary 308

Other Integration Approaches 311

Chapter Summary 313

Review Questions 313

Exercises 314

13 Data Quality: A Key To Success 315

Chapter Objectives 315

Why Is Data Quality Critical? 316

Data Quality Challenges 323

Data Quality Tools 326

Data Quality Initiative 328

Master Data Management (Mdm) 335

MDM Categories 335

MDM Benefits 335

MDM and Data Warehousing 336

Chapter Summary 336

Review Questions 336

Exercises 337

Part 5 Information Access and Delivery 339

14 Matching Information To The Classes of Users 341

Chapter Objectives 341

Information From The Data Warehouse 342

Who Will Use The Information? 349

Information Delivery 356

Information Delivery Tools 360

Information Delivery: Special Topics 366

Chapter Summary 371

Review Questions 371

Exercises 372

15 OLAP in The Data Warehouse 373

Chapter Objectives 373

Demand For Online Analytical Processing 374

OLAP is The Answer 379

OLAP Definitions and Rules 379

OLAP Characteristics 382

Major Features and Functions 382

OLAP Models 393

OLAP Implementation Considerations 398

Chapter Summary 404

Review Questions 405

Exercises 405

16 Data Warehousing and The Web 407

Chapter Objectives 407

Web-Enabled Data Warehouse 408

Web-Based Information Delivery 414

OLAP and The Web 420

Building A Web-Enabled Data Warehouse 421

Chapter Summary 426

Review Questions 426

Exercises 427

17 Data Mining Basics 429

Chapter Objectives 429

What Is Data Mining? 430

Major Data Mining Techniques 439

Data Mining Applications 452

Chapter Summary 459

Review Questions 459

Exercises 460

Part 6 Implementation and Maintenance 461

18 The Physical Design Process 463

Chapter Objectives 463

Physical Design Steps 464

Physical Design Considerations 467

Physical Storage 473

Indexing The Data Warehouse 477

Performance Enhancement Techniques 483

Chapter Summary 486

Review Questions 486

Exercises 487

19 Data Warehouse Deployment 489

Chapter Objectives 489

Data Warehouse Testing 490

Major Deployment Activities 491

Considerations For A Pilot 497

Security 502

Backup and Recovery 504

Chapter Summary 508

Review Questions 508

Exercises 509

20 Growth and Maintenance 511

Chapter Objectives 511

Monitoring The Data Warehouse 512

User Training and Support 515

Managing The Data Warehouse 520

Chapter Summary 524

Review Questions 525

Exercises 525

Answers To Selected Exercises 527

Appendix A: Project Life Cycle Steps and Checklists 531

Appendix B: Critical Factors For Success 535

Appendix C: Guidelines For Evaluating Vendor Solutions 537

Appendix D: Highlights of Vendors and Products 539

Appendix E: Real-World Examples of Best Practices 549

References 555

Glossary 557

Index 565