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. |
Contents
Data Warehouses Data Marts | 25 |
Myths and Misconceptions | 47 |
What Are Dirty Data? | 69 |
Politics | 93 |
Politics | 116 |
Project Management | 152 |
Data Modeling | 186 |
Case Studies | 210 |
Glossary | 229 |
| 237 | |
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
access tool advanced analysis Ain’t Broke benefits blissful data business analysts business clients business intelligence business rules business units capabilities cause change agents Chapter codes contains the processes cost create data mining data model data quality data values data warehouse endeavor data warehouse sponsor data warehouse success data warehousing success decisions and taking deliverables dirty data employees environment Figure forecasting functional groups game plan goals implement increased independent data marts informational data integration investment involved knowledge areas look management contains MDDB months multidimensional analysis objectives OLAP OLTP operational data operational systems organization organization’s organizational culture organizational structure performance problems process groups project management Project Management Institute project quality queries requirements response right sponsors ROI analysis schedule scope share skills soft ROI solution source data stakeholders stovepipe subject areas successful data warehouse tion transformation ware