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This step-by-step guide offers substantial treatment of the many parts of decision-support applications in business intelligence, with selective groupings of the chapters provided for the business representatives, sponsors, project managers, and core and extended team technicians who will be its main audience. The first half of the book is devoted to development, the second to various specific subjects, including human resource allocation, entry and exit criteria, deliverables, activity dependency, task/subtask, and practical guidelines. Both authors are business owners. Annotation ©2003 Book News, Inc., Portland, OR
More Reviews and RecommendationsLarissa Moss is founder and president of Method Focus, Inc., a consulting firm specializing in business intelligence and data warehousing. She is a frequent lecturer and speaker at conferences in the United States, Europe, and Asia on data warehousing, project management, development methodologies, and organizational and cultural issues. Her articles on these topics are regularly published in magazines such as DM Review and Journal of Data Warehousing. She is coauthor of Data Warehouse Project Management (Addison-Wesley, 2000) and Impossible Data Warehouse Situations (Addison-Wesley, 2003). She is a senior consultant at the Cutter Consortium and one of the authors of their Business Intelligence Executive Reports.
Shaku Atre is president of Atre Group, Inc., a Santa Cruz, CA based consulting organization specializing in business intelligence and data warehousing implementations. She is also the president of Atre Associates, Inc., a systems integration company based in New York City. Previously, she was a partner with PricewaterhouseCoopers, held a variety of management and staff positions at IBM, and served as a faculty member of IBM's prestigious Systems Research Institute. She has authored hundreds of articles as a columnist for Information Week, Computerworld, eWeek and a number of other publications. She is the author of five books including Data Base: Structured Techniques for Design, Performance, and Management, Second Edition (John Wiley & Sons, 1988) and Distributed Databases, Cooperative Processing, and Networking (McGraw-Hill, 1992).
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April 19, 2003: It is refreshing to read a book that presents in-depth techniques for developing a BI application from cradle to grave in a continuous evolutionary process. Various matrices and WBS samples in Part II of the book serve as a quick reference for iterative planning and delivering of decision-support systems.The authors have done a phenomenal job in integrating business, technical,and management aspects of a BI and decision-support system to present an exhaustive set of guidelines. After working with numerous clients and having read Inmon?s Building the Data Warehouse, Kimball?s The Data Warehouse Lifecycle Toolkit as well as various BI white papers, I know that data ETL and data warehouses are a major part of any BI strategy. However, after reviewing the summary of over 20 BI related books, I found that the primary focus of many BI books is normally limited to data presentation and analytical layers only.This book is an exception . I would recommend this book to expert as well as novice DW/BI professionals alike, who may be business users, data analysts, architects, project managers, statisticians,or executive stakeholders.
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April 02, 2003: This is an excellent book and, more importantly, it?s very useful. It?s loaded with specifics and checklists on what to do and how to do it (it also tells you what not to do). It lays out the pitfalls and tells you how to avoid them. The stages and steps outlined in the book are very specific and the authors, with their wealth of experience, tell you how to implement a successful data warehouse. The work breakdown structure (the tasks you need to implement the data warehouse), the deliverables matrix, and entry and exit criteria for each step are very detailed and alone are worth the price of the book. The book will give those responsible for a data warehouse the information they need to establish best practices within their own organization and will give these folks the ammunition and support to ask for the necessary resources to implement a data warehouse.