Enhanced descriptions from Syndetics:

most comprehensive, practical guide to designing, building, and implementing a data warehouse on the market today. Barry Devlin--one of the worlds leading experts on data warehousing--is also one of the first practitioners in this area. In this book, he distills the insights and experiences gained over 10 years of designing and building data warehouses. Included are: *An explanation of the optimal three-tiered architecture for the data warehouse, with a clear division between data and information *A full description of the functions needed to implement such an architecture, including reconciling existing, diverse data and deriving consistent, valuable business information *A detailed methodology for building a data warehouse in a way that provides business value and strategic infrastructure at each stage *A high-level approach to justifying the effort involved *A view of the organizational aspects of building and maintaining a warehouse This book will become the key reference for any team undertaking the construction of a data warehouse. It is aimed primarily at the IS managers, architects, and designers involved in this process, as well as the end users having a key role in the ev

Table of contents provided by Syndetics

• Preface (p. v)
• Table of contents (p. vii)
• Table of figures and tables (p. xiii)
• 1 Introduction (p. 1)
• 1.1 Why this book? (p. 2)
• 1.2 Audience (p. 2)
• 1.3 Structure (p. 3)
• Part I The evolution of data warehousing
• 2 The data warehouse--a brief history (p. 7)
• 2.1 Prehistoric times--before the 1980s (p. 9)
• 2.2 The middle ages--mid- to late-1980s (p. 12)
• 2.3 The data revolution--the early 1990s (p. 15)
• 2.4 The era of information-based management--into the 21st century (p. 18)
• 2.5 What is a data warehouse? (p. 20)
• 2.6 Conclusions (p. 21)
• 3 Today's development environment (p. 23)
• 3.1 Fragmented application development (p. 24)
• 3.2 Operational application development (p. 24)
• 3.3 Application-driven decision support (p. 27)
• 3.4 The Info Center (p. 33)
• 3.5 Conclusions (p. 35)
• Part II Principles of data warehousing
• 4 Types of data and their uses (p. 41)
• 4.1 Types of data (p. 42)
• 4.2 Business data (p. 44)
• 4.3 Metadata (p. 52)
• 4.4 Data beyond the scope of the warehouse (p. 57)
• 4.5 Internal and external data (p. 59)
• 4.6 Conclusions (p. 61)
• 5 Conceptual data architecture (p. 63)
• 5.1 Business data architectures (p. 64)
• 5.2 The single-layer data architecture (p. 64)
• 5.3 The two-layer data architecture (p. 67)
• 5.4 The three-layer data architecture (p. 69)
• 5.5 A data architecture for metadata (p. 77)
• 5.6 Conclusions (p. 84)
• 6 Design techniques (p. 87)
• 6.1 Enterprise data modeling (p. 88)
• 6.2 Representing time in business data (p. 97)
• 6.3 Historical data (p. 104)
• 6.4 Data replication (p. 108)
• 6.5 Conclusions (p. 123)
• 7 Introduction to the logical architecture (p. 125)
• 7.1 Business data in the data warehouse (p. 126)
• 7.2 Business data--other considerations (p. 130)
• 7.3 External data (p. 134)
• 7.4 Metadata in the data warehouse (p. 137)
• 7.5 The data warehouse catalog (p. 140)
• 7.6 Operational systems (p. 141)
• 7.7 Data warehouse functionality (p. 145)
• 7.8 Conclusions (p. 148)
• Part III Creating the data asset
• 8 Business data warehouse design (p. 151)
• 8.1 Modeling the BDW--general design (p. 152)
• 8.2 Modeling the BDW--a segmented approach (p. 155)
• 8.3 Modeling the BDW--practical results (p. 161)
• 8.4 The structure of periodic data in the BDW (p. 162)
• 8.5 Archive and retrieval (p. 169)
• 8.6 The role of parallel databases (p. 172)
• 8.7 Conclusions (p. 174)
• 9 Populating the business data warehouse (p. 177)
• 9.1 BDW population--initial considerations (p. 178)
• 9.2 Capture--an introduction (p. 178)
• 9.3 From operational data to the BDW (p. 180)
• 9.4 Six data capture techniques (p. 182)
• 9.5 Output data structures from capture (p. 194)
• 9.6 Apply--an introduction (p. 196)
• 9.7 Apply during BDW creation (p. 197)
• 9.8 Apply during BDW maintenance (p. 201)
• 9.9 Refresh versus update of the BDW (p. 204)
• 9.10 Transformation--an introduction (p. 205)
• 9.11 Transformation in BDW population (p. 212)
• 9.12 BDW population--the overall process (p. 218)
• 9.13 Conclusions (p. 219)
• Part IV Unlocking the data asset for end users
• 10 Designing business information warehouses (p. 223)
• 10.1 Types of business information warehouse (p. 224)
• 10.2 Modeling BIWs (p. 227)
• 10.3 Key influences on BIW design (p. 231)
• 10.4 BIW implementation (p. 234)
• 10.5 Historical data in BIWs (p. 241)
• 10.6 Archive and retrieval in BIWs (p. 244)
• 10.7 Conclusions (p. 245)
• 11 Populating business information warehouses (p. 247)
• 11.1 BIW population--an introduction (p. 248)
• 11.2 Capture from the BDW (p. 249)
• 11.3 Apply to the BIW (p. 250)
• 11.4 Comparing the performance of update and refresh modes of replication (p. 254)
• 11.5 Transformation (p. 255)
• 11.6 BIW population--implementation aspects (p. 259)
• 11.7 Conclusions (p. 260)
• 12 User access to information (p. 261)
• 12.1 The business information interface (p. 262)
• 12.2 Data access (p. 270)
• 12.3 Conclusions (p. 274)
• 13 Information--data in context (p. 275)
• 13.1 The business information guide--an introduction (p. 276)
• 13.2 Requirements for the BIG (p. 277)
• 13.3 The naive and sentimental user (p. 291)
• 13.4 Users of the BIG (p. 294)
• 13.5 Structure of the BIG (p. 296)
• 13.6 DWC population (p. 297)
• 13.7 Conclusions (p. 298)
• Part V Implementing the data warehouse
• 14 Obstacles to implementation (p. 303)
• 14.1 The size and scope of the warehouse (p. 304)
• 14.2 Justifying investment in a data warehouse (p. 305)
• 14.3 Organizational issues (p. 305)
• 14.4 Placement of the BDW and BIWs in the enterprise (p. 306)
• 14.5 Ongoing administration (p. 307)
• 14.6 Conclusions (p. 307)
• 15 Planning your implementation (p. 309)
• 15.1 Segmenting the data warehouse (p. 310)
• 15.2 Staging the warehouse implementation (p. 311)
• 15.3 Kick-starting the implementation process (p. 316)
• 15.4 Coordinating the data warehouse implementation process (p. 329)
• 15.5 Critical success factors (p. 331)
• 15.6 Conclusions (p. 332)
• 16 Justifying the warehouse (p. 335)
• 16.1 The traditional justification approach (p. 336)
• 16.2 Beyond cost avoidance (p. 339)
• 16.3 A new basis for competitiveness (p. 340)
• 16.4 Changing management structures (p. 344)
• 16.5 The automation of marketing (p. 345)
• 16.6 Data warehouse costs (p. 347)
• 16.7 Conclusions (p. 349)
• 17 Organizational implications of data warehousing (p. 351)
• 17.1 From planning to pilot (p. 352)
• 17.2 From initiation to roll-out (p. 358)
• 17.3 Conclusions (p. 362)
• 18 Physical structure of the data warehouse (p. 363)
• 18.1 The data warehouse environment--centralized versus distributed (p. 364)
• 18.2 Aligning the data warehouse with the organizational structure (p. 371)
• 18.3 Subsetting the BDW (p. 377)
• 18.4 Conclusions (p. 378)
• 19 Data warehouse management (p. 379)
• 19.1 Replication administration (p. 380)
• 19.2 From administration to runtime (p. 389)
• 19.3 Process management (p. 392)
• 19.4 Data transfer (p. 394)
• 19.5 Other database support functions (p. 397)
• 19.6 Conclusions (p. 399)
• 20 Looking to the future (p. 401)
• 20.1 A single information source (p. 402)
• 20.2 Distributed information availability (p. 404)
• 20.3 Information in a business context (p. 406)
• 20.4 Automated information delivery (p. 407)
• 20.5 Information quality and ownership (p. 408)
• 20.6 Concluding remarks (p. 409)
• References (p. 411)
• Index (p. 417)

Excerpt provided by Syndetics

I first conceived of the idea of writing a book on data warehousing during a series of 2-day seminars known as the "Information Warehouse MasterClass" that I and a number of IBM colleagues had developed and presented around the world from 1992 to 1994. From the many companies that attended these seminars, one principal requirement was clear: they needed a common definition or architecture for a data warehouse, detailed enough to drive a consistent implementation within their organizations, yet concise enough to allow the whole company to understand and accept it. It was from the MasterClasses and the needs of these companies that I developed the representation and terminology of the data warehouse architecture used in this book. In 1992, only a few real data warehouse implementations existed, each one hand-crafted and custom-built. Today, the vast majority of companies are planning to build or are actually building a data warehouse. While working with these companies over the years, I and other consultants saw the need to develop methodologies that cover the entire implementation process. This process continues to present major difficulties for many data warehouse implementations. I am convinced that companies today need a generalized and rational implementation approach to this complex process. The methodology described in this book is the result of crafting and proving the implementation approach over the years in real warehouse implementation projects. Clearly, I have distilled the material covered here from interactions with many colleagues within IBM, with other consultants working in the field, and most especially from many hours of work with clients. Without their contributions, this book could not have been written. On the other hand, responsibility for any errors or misinterpretations is, of course, mine. It would be impossible to acknowledge by name everybody who has contributed to this book. To name anybody is to run the risk of omitting some valuable contributions; to those people I apologize in advance. However, I would like to especially thank a number of people either individually or collectively, whose support, knowledge, or time made this book possible: the companies I've worked with over the years, especially those who have agreed to be directly referenced here: Martijn Bossenbroek (ABN AMRO), Børre Lunde and Solveig Oien Berg (Gjensidige), and Laura Sager (Whirlpool) the colleagues who have contributed to or reviewed the material: John Bair, Peter Cabena, Ciarán Ennis, Keith Holmes, Edwin Humphreys, Jim McGovern, Paul Murphy, Barry O'Brien, Pat O'Sullivan, Phil Teale, Michael Storey, and Feargal Supple the external reviewers who have added significantly to the book: David Christian, John Kneiling, Eric Rawlins, Richard Rist and Terry Moriarty John Holland and Dónal O'Shea, who introduced the book to Addison Wesley Longman the team at Addison Wesley Longman: Lynne Doran Cote, Katherine Harutunian, Patty Mahtani and especially my editor Susan Middleton Last, but not least, a special word of thanks to my family, Lil, Katherine, Alan and Emma, who have become convinced over the past year that I can exist only in symbiosis with my PC. 1 Barry Devlin August, 1996 Dublin 1 The text of this book was produced entirely in Microsoft Word and the graphics were developed using Lotus Freelance Graphics. 0201964252P04062001 Excerpted from Data Warehouse: From Architecture to Implementation by Barry Devlin All rights reserved by the original copyright owners. Excerpts are provided for display purposes only and may not be reproduced, reprinted or distributed without the written permission of the publisher.

Author notes provided by Syndetics

Barry Devlin--one of the world's leading experts on data warehousing--is also one of the first practitioners in this area. In this book, he distills the insights and experiences gained over 10 years of designing and building data warehouses.
Dr. Barry Devlin is a leading authority in Europe on data warehousing. He defined the Data Warehouse Architecture within IBM Europe in 1985 and contributed to its practical implementation over a number of years. This gives him a unique insight into user demands for information, and the development consequences. Barry has a total of 14 years in the IS business, the last 10 of which have been spent with IBM's International Software Development Laboratory in Dublin. He currently works as a consultant in the IBM Consulting Group in Dublin and is a member of the IBM Academy of Technology.