Blissful DataAnalyzing information and acting accordingly is a key strategic goal of every business. But vast quantities of data are of little use if they are not structured and kept in such a way as to be readily accessible and applicable. Only optimally organized information can drive maximum productivity. Blissful Data is a reader-friendly book that reveals what it takes to achieve a state of perfect organization within the environment of a successful data warehouse. This timely book will help the reader: * understand how data evolves into information that drives better decision making * recognize the pitfalls, caused by people and politics, that lead to short-sighted solutions and long-term problems * manage data warehousing costs, performance, and expectations effectively * apply project management fundamentals to data warehouse endeavors. Blissful Data includes dozens of examples, as well as case studies illustrating successful, unsuccessful, and disastrous data warehouse strategies. |
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Содержание
What Is a Data Warehouse? Why Should You Care? | 1 |
Data Warehouses Data Marts Whats in a Name? | 25 |
Myths and Misconceptions What Should You Eradicate? | 47 |
What Are Dirty Data? Where Do Dirty Data Come From? | 69 |
Politics Who Owns It Anyway? | 93 |
Politics Whos Going to Pay? | 116 |
Project Management I5 It the Silver Bullet? | 152 |
Data Modeling Why Model the Data? | 186 |
Case Studies Is There a Light at the End of the Tunnel? | 210 |
What Does That Mean Again? | 229 |
References | 237 |
239 | |
About the Author | |
Другие издания - Просмотреть все
Blissful Data: Wisdom and Strategies for Providing Meaningful, Useful, and ... Margaret Y. Chu Недоступно для просмотра - 2004 |
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action additional amounts analysis application areas become benefits better blissful data bring business clients business rules business units called cause Chapter clear codes communication completed consists contains cost create culture data mart data model data warehouse data warehousing databases decisions defined detailed dirty data effort employees endeavor example exist expectations field Figure functional game plan goals groups important improvement increased integration investment involved issues keep knowledge learned look metadata method months move objectives obtain once operational operational systems organization organizational culture performance person problems project management queries REMEMBER reports requirements response risk schedule scope share skills solution specific sponsor structure success tool types understand ware