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Data Warehousing: Using the Wal-Mart Model (The Morgan Kaufmann Series in Data Management Systems)
by Paul Westerman
Binding: Paperback, 1st edition, 297 pages
Publisher: Morgan Kaufmann
Weight: 1.32 pound
Dimension: H: 0.75 x L: 9.13 x W: 0.58 inches
ISBN 10: 155860684X
ISBN 13: 9781558606845
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Book Description:
At 70 terabytes and growing, Wal Mart's data warehouse is still the world's largest, most ambitious, and arguably most successful commercial database. Written by one of the key figures in its design and construction, Data Warehousing: Using the Wal Mart Model gives you an insider's view of this enormous project. Continuously drawing from this example, the author teaches you the general principles and specific techniques you need to understand to be a valuable part of your organization's own data warehouse project, however large or small. You'll emerge with a practical understanding of both the business and technical aspects of building a data warehouse for storing and accessing data in a strategically useful way.What further sets this book apart is its focus on the informational needs of retail companies including both market and organizational issues that affect the data's collection and use. If retail is your field, this book will prove especially valuable as you develop and implement your company's ideal data warehouse solution. Written by a member of the team of four engineers who designed and built the Wal Mart Data Warehouse database, a team whose database design was recognized internally in 1991 by Wal Mart with the company's Team Innovational Technical award. Provides essential information for project managers, consultants, data warehouse managers, and data architects. Takes an in depth look at a wide range of technical issues, including architecture, construction approaches, tool selection, database system selection, and maintenance. Addresses issues specific to retail business: vendors, inventory, sales analysis, geography, article categories, and more. Explains how to determine business requirements at the outset of the project and how to develop return on investment analyses after the warehouse has been brought online.


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