CUTTING-EDGE CONTENT AND GUIDANCE FROM A DATA WAREHOUSING EXPERTNOW EXPANDED TO REFLECT FIELD TRENDS
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.
Table of Contents:
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
About the Author :
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.
Review :
"... clearly the author is a long-time practitioner and expert in this area. And if this were not enough, the language is clear and precise, and the associated content is easily internalised." (BCS, August 2010)
