Details

<p>Preface xxv</p> <p><b>Part 1 Overview and Concepts 1</b></p> <p><b>1 The Compelling Need For Data Warehousing 3</b></p> <p>Chapter Objectives 3</p> <p>Escalating Need For Strategic Information 4</p> <p>Failures of Past Decision-Support Systems 9</p> <p>Operational Versus Decision-Support Systems 11</p> <p>Data Warehousing—The Only Viable Solution 13</p> <p>A Simple Concept For Information Delivery 15</p> <p>The Data Warehousing Movement 17</p> <p>Evolution of Business Intelligence 18</p> <p>Chapter Summary 20</p> <p>Review Questions 20</p> <p>Exercises 21</p> <p><b>2 Data Warehouse: The Building Blocks 23</b></p> <p>Chapter Objectives 23</p> <p>Defining Features 24</p> <p>Data Warehouses and Data Marts 29</p> <p>Architectural Types 32</p> <p>Overview of The Components 34</p> <p>Metadata in The Data Warehouse 41</p> <p>Chapter Summary 42</p> <p>Review Questions 43</p> <p>Exercises 43</p> <p><b>3 Trends in Data Warehousing 45</b></p> <p>Chapter Objectives 45</p> <p>Continued Growth in Data Warehousing 46</p> <p>Significant Trends 50</p> <p>Emergence of Standards 64</p> <p>Web-Enabled Data Warehouse 66</p> <p>Chapter Summary 69</p> <p>Review Questions 69</p> <p>Exercises 70</p> <p><b>Part 2 Planning and Requirements 71</b></p> <p><b>4 Planning and Project Management 73</b></p> <p>Chapter Objectives 73</p> <p>Planning Your Data Warehouse 74</p> <p>The Data Warehouse Project 79</p> <p>The Development Phases 83</p> <p>The Project Team 85</p> <p>Project Management Considerations 90</p> <p>Chapter Summary 96</p> <p>Review Questions 96</p> <p>Exercises 97</p> <p><b>5 Defining The Business Requirements 99</b></p> <p>Chapter Objectives 99</p> <p>Dimensional Analysis 100</p> <p>Information Packages—A Useful Concept 103</p> <p>Requirements Gathering Methods 109</p> <p>Requirements Definition: Scope and Content 116</p> <p>Chapter Summary 119</p> <p>Review Questions 119</p> <p>Exercises 120</p> <p><b>6 Requirements As The Driving Force For Data Warehousing 121</b></p> <p>Chapter Objectives 121</p> <p>Data Design 122</p> <p>The Architectural Plan 125</p> <p>Data Storage Specifications 131</p> <p>DBMS Selection 132</p> <p>Information Delivery Strategy 133</p> <p>Chapter Summary 136</p> <p>Review Questions 136</p> <p>Exercises 137</p> <p><b>Part 3 Architecture and Infrastructure 139</b></p> <p><b>7 Architectural Components 141</b></p> <p>Chapter Objectives 141</p> <p>Understanding Data Warehouse Architecture 141</p> <p>Distinguishing Characteristics 143</p> <p>Architectural Framework 146</p> <p>Technical Architecture 148</p> <p>Architectural Types 156</p> <p>Chapter Summary 160</p> <p>Review Questions 160</p> <p>Exercises 161</p> <p><b>8 Infrastructure As The Foundation For Data Warehousing 163</b></p> <p>Chapter Objectives 163</p> <p>Infrastructure Supporting Architecture 164</p> <p>Hardware and Operating Systems 166</p> <p>Database Software 181</p> <p>Collection of Tools 184</p> <p> Data Warehouse Appliances 188</p> <p>Chapter Summary 191</p> <p>Review Questions 191</p> <p>Exercises 192</p> <p><b>9 The Significant Role of Metadata 193</b></p> <p>Chapter Objectives 193</p> <p>Why Metadata Is Important 193</p> <p>Metadata Types By Functional Areas 203</p> <p>Business Metadata 207</p> <p>Technical Metadata 209</p> <p>How To Provide Metadata 212</p> <p>Chapter Summary 219</p> <p>Review Questions 220</p> <p>Exercises 220</p> <p><b>Part 4 Data Design and Data Preparation 223</b></p> <p><b>10 Principles of Dimensional Modeling 225</b></p> <p>Chapter Objectives 225</p> <p>From Requirements To Data Design 225</p> <p>The Star Schema 232</p> <p>Star Schema Keys 239</p> <p>Advantages of The Star Schema 241</p> <p>Star Schema: Examples 244</p> <p>Chapter Summary 246</p> <p>Review Questions 247</p> <p>Exercises 247</p> <p><b>11 Dimensional Modeling: Advanced Topics 249</b></p> <p>Chapter Objectives 249</p> <p>Updates To The Dimension Tables 250</p> <p>Miscellaneous Dimensions 255</p> <p>The Snowflake Schema 259</p> <p>Aggregate Fact Tables 262</p> <p>Families of Stars 272</p> <p>Chapter Summary 277</p> <p>Review Questions 278</p> <p>Exercises 278</p> <p><b>12 Data Extraction, Transformation, and Loading 281</b></p> <p>Chapter Objectives 281</p> <p>ETL Overview 282</p> <p>ETL Requirements and Steps 284</p> <p>Data Extraction 286</p> <p>Data Transformation 295</p> <p>Data Loading 302</p> <p>ETL Summary 308</p> <p>Other Integration Approaches 311</p> <p>Chapter Summary 313</p> <p>Review Questions 313</p> <p>Exercises 314</p> <p><b>13 Data Quality: A Key To Success 315</b></p> <p>Chapter Objectives 315</p> <p>Why Is Data Quality Critical? 316</p> <p>Data Quality Challenges 323</p> <p>Data Quality Tools 326</p> <p>Data Quality Initiative 328</p> <p>Master Data Management (Mdm) 335</p> <p>MDM Categories 335</p> <p>MDM Benefits 335</p> <p>MDM and Data Warehousing 336</p> <p>Chapter Summary 336</p> <p>Review Questions 336</p> <p>Exercises 337</p> <p><b>Part 5 Information Access and Delivery 339</b></p> <p><b>14 Matching Information To The Classes of Users 341</b></p> <p>Chapter Objectives 341</p> <p>Information From The Data Warehouse 342</p> <p>Who Will Use The Information? 349</p> <p>Information Delivery 356</p> <p>Information Delivery Tools 360</p> <p>Information Delivery: Special Topics 366</p> <p>Chapter Summary 371</p> <p>Review Questions 371</p> <p>Exercises 372</p> <p><b>15 OLAP in The Data Warehouse 373</b></p> <p>Chapter Objectives 373</p> <p>Demand For Online Analytical Processing 374</p> <p>OLAP is The Answer 379</p> <p>OLAP Definitions and Rules 379</p> <p>OLAP Characteristics 382</p> <p>Major Features and Functions 382</p> <p>OLAP Models 393</p> <p>OLAP Implementation Considerations 398</p> <p>Chapter Summary 404</p> <p>Review Questions 405</p> <p>Exercises 405</p> <p><b>16 Data Warehousing and The Web 407</b></p> <p>Chapter Objectives 407</p> <p>Web-Enabled Data Warehouse 408</p> <p>Web-Based Information Delivery 414</p> <p>OLAP and The Web 420</p> <p>Building A Web-Enabled Data Warehouse 421</p> <p>Chapter Summary 426</p> <p>Review Questions 426</p> <p>Exercises 427</p> <p><b>17 Data Mining Basics 429</b></p> <p>Chapter Objectives 429</p> <p>What Is Data Mining? 430</p> <p>Major Data Mining Techniques 439</p> <p>Data Mining Applications 452</p> <p>Chapter Summary 459</p> <p>Review Questions 459</p> <p>Exercises 460</p> <p><b>Part 6 Implementation and Maintenance 461</b></p> <p><b>18 The Physical Design Process 463</b></p> <p>Chapter Objectives 463</p> <p>Physical Design Steps 464</p> <p>Physical Design Considerations 467</p> <p>Physical Storage 473</p> <p>Indexing The Data Warehouse 477</p> <p>Performance Enhancement Techniques 483</p> <p>Chapter Summary 486</p> <p>Review Questions 486</p> <p>Exercises 487</p> <p><b>19 Data Warehouse Deployment 489</b></p> <p>Chapter Objectives 489</p> <p>Data Warehouse Testing 490</p> <p>Major Deployment Activities 491</p> <p>Considerations For A Pilot 497</p> <p>Security 502</p> <p>Backup and Recovery 504</p> <p>Chapter Summary 508</p> <p>Review Questions 508</p> <p>Exercises 509</p> <p><b>20 Growth and Maintenance 511</b></p> <p>Chapter Objectives 511</p> <p>Monitoring The Data Warehouse 512</p> <p>User Training and Support 515</p> <p>Managing The Data Warehouse 520</p> <p>Chapter Summary 524</p> <p>Review Questions 525</p> <p>Exercises 525</p> <p>Answers To Selected Exercises 527</p> <p>Appendix A: Project Life Cycle Steps and Checklists 531</p> <p>Appendix B: Critical Factors For Success 535</p> <p>Appendix C: Guidelines For Evaluating Vendor Solutions 537</p> <p>Appendix D: Highlights of Vendors and Products 539</p> <p>Appendix E: Real-World Examples of Best Practices 549</p> <p>References 555</p> <p>Glossary 557</p> <p>Index 565</p>

<p><b>PAULRAJ PONNIAH, P<small>H</small>D,</b> 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.

<p><b>CUTTING-EDGE CONTENT AND GUIDANCE FROM A DATA WAREHOUSING EXPERT—NOW EXPANDED TO REFLECT FIELD TRENDS</b> <p>Data warehousing has revolutionized the way businesses in a wide variety of industries perform analysis and make strategic decisions. Since the first edition of <i>Data Warehousing Fundamentals</i>, 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. <p>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. <p>This practical <i>Second Edition</i> 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. <p>Specifically written for professionals responsible for designing, implementing, or maintaining data warehousing systems, <i>Data Warehousing Fundamentals</i> presents agile, thorough, and systematic development principles for the IT professional and anyone working or researching in information management.

US