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. |
From inside the book
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Page 2
... goal of optimally organized information? What are the pitfalls and barriers that must be overcome? What tools, best practices, and guidelines are available to increase chances of success? What can be learned from others who have ...
... goal of optimally organized information? What are the pitfalls and barriers that must be overcome? What tools, best practices, and guidelines are available to increase chances of success? What can be learned from others who have ...
Page 3
... goal of maximum productivity with blissful data can triumph over their competition. Thus, blissful data provide a competitive advantage. All organizations need blissful data to be victorious into the future. I know what you may be ...
... goal of maximum productivity with blissful data can triumph over their competition. Thus, blissful data provide a competitive advantage. All organizations need blissful data to be victorious into the future. I know what you may be ...
Page 18
... goal. Such change also involves “integration.” New roles and responsibilities need to be combined with existing ones. Integration of data, business rules, and requirements means breaking down age-old barriers and frequently overcoming ...
... goal. Such change also involves “integration.” New roles and responsibilities need to be combined with existing ones. Integration of data, business rules, and requirements means breaking down age-old barriers and frequently overcoming ...
Page 19
... goals and objectives of EDM and FLPT were not in synch. The goals Why Couldn't Some Data Warehouses Fly? 19.
... goals and objectives of EDM and FLPT were not in synch. The goals Why Couldn't Some Data Warehouses Fly? 19.
Page 20
Margaret Y. Chu. of EDM and FLPT were not in synch. The goals for the data warehouse expansion and the forecasting project should have been tied, yet they were handled as two separate projects. Without a common clear goal or definition ...
Margaret Y. Chu. of EDM and FLPT were not in synch. The goals for the data warehouse expansion and the forecasting project should have been tied, yet they were handled as two separate projects. Without a common clear goal or definition ...
Contents
Data Warehouses Data Marts | 25 |
Myths and Misconceptions | 47 |
What Are Dirty Data? Where Do Dirty Data Come From? | 69 |
Politics | 93 |
Politics | 116 |
Project Management | 152 |
Data Modeling | 186 |
Case Studies | 210 |
Glossary | 229 |
About the Author | 245 |
Other editions - View all
Blissful Data: Wisdom and Strategies for Providing Meaningful, Useful, and ... Margaret Y. Chu No preview available - 2004 |
Common terms and phrases
action additional already amounts analysis application areas become benefits better blissful data bring business clients business rules business units called cause Chapter clear codes communication completed 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 look measurement metadata method months 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