Overview

The new edition of the classic bestseller that launched the data warehousing industry covers new approaches and technologies, many of which have been pioneered by Inmon himself In addition to explaining the fundamentals of data warehouse systems, the book covers new topics such as methods for handling unstructured data in a data warehouse and storing data across multiple storage media Discusses the pros and cons of relational versus multidimensional design and how to measure return on investment in planning data warehouse projects Covers advanced topics, including data monitoring and testing Although the book includes an extra 100 pages worth of valuable content, the price has actually been reduced from $65 to $55

Full Product Details

Author:   W. H. Inmon
Publisher:   John Wiley & Sons Inc
Imprint:   John Wiley & Sons Inc
Edition:   4th edition
Dimensions:   Width: 18.80cm , Height: 3.80cm , Length: 23.60cm
Weight:   0.748kg
ISBN:  

9780764599446

ISBN 10:   0764599445
Pages:   576
Publication Date:   11 October 2005
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order  
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Table of Contents

Preface xix Acknowledgments xxvii Chapter 1 Evolution of Decision Support Systems 1 The Evolution 2 The Advent of DASD 4 PC/4GL Technology 4 Enter the Extract Program 5 The Spider Web 6 Problems with the Naturally Evolving Architecture 7 Lack of Data Credibility 7 Problems with Productivity 9 From Data to Information 12 A Change in Approach 14 The Architected Environment 16 Data Integration in the Architected Environment 18 Who Is the User? 20 The Development Life Cycle 20 Patterns of Hardware Utilization 22 Setting the Stage for Re-engineering 23 Monitoring the Data Warehouse Environment 25 Summary 28 Chapter 2 The Data Warehouse Environment 29 The Structure of the Data Warehouse 33 Subject Orientation 34 Day 1 to Day n Phenomenon 39 Granularity 41 The Benefits of Granularity 42 An Example of Granularity 43 Dual Levels of Granularity 46 Exploration and Data Mining 50 Living Sample Database 50 Partitioning as a Design Approach 53 Partitioning of Data 53 Structuring Data in the Data Warehouse 56 Auditing and the Data Warehouse 61 Data Homogeneity and Heterogeneity 61 Purging Warehouse Data 64 Reporting and the Architected Environment 64 The Operational Window of Opportunity 65 Incorrect Data in the Data Warehouse 67 Summary 69 Chapter 3 The Data Warehouse and Design 71 Beginning with Operational Data 71 Process and Data Models and the Architected Environment 78 The Data Warehouse and Data Models 79 The Data Warehouse Data Model 81 The Midlevel Data Model 84 The Physical Data Model 88 The Data Model and Iterative Development 91 Normalization and Denormalization 94 Snapshots in the Data Warehouse 100 Metadata 102 Managing Reference Tables in a Data Warehouse 103 Cyclicity of Data — The Wrinkle of Time 105 Complexity of Transformation and Integration 108 Triggering the Data Warehouse Record 112 Events 112 Components of the Snapshot 113 Some Examples 113 Profile Records 114 Managing Volume 115 Creating Multiple Profile Records 117 Going from the Data Warehouse to the Operational Environment 117 Direct Operational Access of Data Warehouse Data 118 Indirect Access of Data Warehouse Data 119 An Airline Commission Calculation System 119 A Retail Personalization System 121 Credit Scoring 123 Indirect Use of Data Warehouse Data 125 Star Joins 126 Supporting the ODS 133 Requirements and the Zachman Framework 134 Summary 136 Chapter 4 Granularity in the Data Warehouse 139 Raw Estimates 140 Input to the Planning Process 141 Data in Overflow 142 Overflow Storage 144 What the Levels of Granularity Will Be 147 Some Feedback Loop Techniques 148 Levels of Granularity — Banking Environment 150 Feeding the Data Marts 157 Summary 157 Chapter 5 The Data Warehouse and Technology 159 Managing Large Amounts of Data 159 Managing Multiple Media 161 Indexing and Monitoring Data 162 Interfaces to Many Technologies 162 Programmer or Designer Control of Data Placement 163 Parallel Storage and Management of Data 164 Metadata Management 165 Language Interface 166 Efficient Loading of Data 166 Efficient Index Utilization 168 Compaction of Data 169 Compound Keys 169 Variable-Length Data 169 Lock Management 171 Index-Only Processing 171 Fast Restore 171 Other Technological Features 172 DBMS Types and the Data Warehouse 172 Changing DBMS Technology 174 Multidimensional DBMS and the Data Warehouse 175 Data Warehousing across Multiple Storage Media 182 The Role of Metadata in the Data Warehouse Environment 182 Context and Content 185 Three Types of Contextual Information 186 Capturing and Managing Contextual Information 187 Looking at the Past 187 Refreshing the Data Warehouse 188 Testing 190 Summary 191 Chapter 6 The Distributed Data Warehouse 193 Types of Distributed Data Warehouses 193 Local and Global Data Warehouses 194 The Local Data Warehouse 197 The Global Data Warehouse 198 Intersection of Global and Local Data 201 Redundancy 206 Access of Local and Global Data 207 The Technologically Distributed Data Warehouse 211 The Independently Evolving Distributed Data Warehouse 213 The Nature of the Development Efforts 213 Completely Unrelated Warehouses 215 Distributed Data Warehouse Development 217 Coordinating Development across Distributed Locations 218 The Corporate Data Model — Distributed 219 Metadata in the Distributed Warehouse 223 Building the Warehouse on Multiple Levels 223 Multiple Groups Building the Current Level of Detail 226 Different Requirements at Different Levels 228 Other Types of Detailed Data 232 Metadata 234 Multiple Platforms for Common Detail Data 235 Summary 236 Chapter 7 Executive Information Systems and the Data Warehouse 239 EIS — The Promise 240 A Simple Example 240 Drill-Down Analysis 243 Supporting the Drill-Down Process 245 The Data Warehouse as a Basis for EIS 247 Where to Turn 248 Event Mapping 251 Detailed Data and EIS 253 Keeping Only Summary Data in the EIS 254 Summary 255 Chapter 8 External Data and the Data Warehouse 257 External Data in the Data Warehouse 260 Metadata and External Data 261 Storing External Data 263 Different Components of External Data 264 Modeling and External Data 265 Secondary Reports 266 Archiving External Data 267 Comparing Internal Data to External Data 267 Summary 268 Chapter 9 Migration to the Architected Environment 269 A Migration Plan 270 The Feedback Loop 278 Strategic Considerations 280 Methodology and Migration 283 A Data-Driven Development Methodology 283 Data-Driven Methodology 286 System Development Life Cycles 286 A Philosophical Observation 286 Summary 287 Chapter 10 The Data Warehouse and the Web 289 Supporting the eBusiness Environment 299 Moving Data from the Web to the Data Warehouse 300 Moving Data from the Data Warehouse to the Web 301 Web Support 302 Summary 302 Chapter 11 Unstructured Data and the Data Warehouse 305 Integrating the Two Worlds 307 Text — The Common Link 308 A Fundamental Mismatch 310 Matching Text across the Environments 310 A Probabilistic Match 311 Matching All the Information 312 A Themed Match 313 Industrially Recognized Themes 313 Naturally Occurring Themes 316 Linkage through Themes and Themed Words 317 Linkage through Abstraction and Metadata 318 A Two-Tiered Data Warehouse 320 Dividing the Unstructured Data Warehouse 321 Documents in the Unstructured Data Warehouse 322 Visualizing Unstructured Data 323 A Self-Organizing Map (SOM) 324 The Unstructured Data Warehouse 325 Volumes of Data and the Unstructured Data Warehouse 326 Fitting the Two Environments Together 327 Summary 330 Chapter 12 The Really Large Data Warehouse 331 Why the Rapid Growth? 332 The Impact of Large Volumes of Data 333 Basic Data-Management Activities 334 The Cost of Storage 335 The Real Costs of Storage 336 The Usage Pattern of Data in the Face of Large Volumes 336 A Simple Calculation 337 Two Classes of Data 338 Implications of Separating Data into Two Classes 339 Disk Storage in the Face of Data Separation 340 Near-Line Storage 341 Access Speed and Disk Storage 342 Archival Storage 343 Implications of Transparency 345 Moving Data from One Environment to Another 346 The CMSM Approach 347 A Data Warehouse Usage Monitor 348 The Extension of the Data Warehouse across Different Storage Media 349 Inverting the Data Warehouse 350 Total Cost 351 Maximum Capacity 352 Summary 354 Chapter 13 The Relational and the Multidimensional Models as a Basis for Database Design 357 The Relational Model 357 The Multidimensional Model 360 Snowflake Structures 361 Differences between the Models 362 The Roots of the Differences 363 Reshaping Relational Data 364 Indirect Access and Direct Access of Data 365 Servicing Future Unknown Needs 366 Servicing the Need to Change Gracefully 367 Independent Data Marts 370 Building Independent Data Marts 371 Summary 375 Chapter 14 Data Warehouse Advanced Topics 377 End-User Requirements and the Data Warehouse 377 The Data Warehouse and the Data Model 378 The Relational Foundation 378 The Data Warehouse and Statistical Processing 379 Resource Contention in the Data Warehouse 380 The Exploration Warehouse 380 The Data Mining Warehouse 382 Freezing the Exploration Warehouse 383 External Data and the Exploration Warehouse 384 Data Marts and Data Warehouses in the Same Processor 384 The Life Cycle of Data 386 Mapping the Life Cycle to the Data Warehouse Environment 387 Testing and the Data Warehouse 388 Tracing the Flow of Data through the Data Warehouse 390 Data Velocity in the Data Warehouse 391 “Pushing” and “Pulling” Data 393 Data Warehouse and the Web-Based eBusiness Environment 393 The Interface between the Two Environments 394 The Granularity Manager 394 Profile Records 396 The ODS, Profile Records, and Performance 397 The Financial Data Warehouse 397 The System of Record 399 A Brief History of Architecture — Evolving to the Corporate Information Factory 402 Evolving from the CIF 404 Obstacles 406 CIF — Into the Future 406 Analytics 406 Erp/sap 407 Unstructured Data 408 Volumes of Data 409 Summary 410 Chapter 15 Cost-Justification and Return on Investment for a Data Warehouse 413 Copying the Competition 413 The Macro Level of Cost-Justification 414 A Micro Level Cost-Justification 415 Information from the Legacy Environment 418 The Cost of New Information 419 Gathering Information with a Data Warehouse 419 Comparing the Costs 420 Building the Data Warehouse 420 A Complete Picture 421 Information Frustration 422 The Time Value of Data 422 The Speed of Information 423 Integrated Information 424 The Value of Historical Data 425 Historical Data and CRM 426 Summary 426 Chapter 16 The Data Warehouse and the ODS 429 Complementary Structures 430 Updates in the ODS 430 Historical Data and the ODS 431 Profile Records 432 Different Classes of ODS 434 Database Design — A Hybrid Approach 435 Drawn to Proportion 436 Transaction Integrity in the ODS 437 Time Slicing the ODS Day 438 Multiple ODS 439 ODS and the Web Environment 439 An Example of an ODS 440 Summary 441 Chapter 17 Corporate Information Compliance and Data Warehousing 443 Two Basic Activities 445 Financial Compliance 446 The “What” 447 The “Why” 449 Auditing Corporate Communications 452 Summary 454 Chapter 18 The End-User Community 457 The Farmer 458 The Explorer 458 The Miner 459 The Tourist 459 The Community 459 Different Types of Data 460 Cost-Justification and ROI Analysis 461 Summary 462 Chapter 19 Data Warehouse Design Review Checklist 463 When to Do a Design Review 464 Who Should Be in the Design Review? 465 What Should the Agenda Be? 465 The Results 465 Administering the Review 466 A Typical Data Warehouse Design Review 466 Summary 488 Glossary 489 References 507 Articles 507 Books 510 White Papers 512 Index 517

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Author Information

William H. Inmon is the acknowledged ""Father of Data Warehousing"" and a partner in www.billinmon.com, a Web site featuring information on data warehousing and related technologies. He has written more than 40 books on database and data warehousing technologies, and is a frequent speaker (and often the keynote) at major conferences.

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