Rating:
(7 reviews)
Author: Jack E. Olson
ISBN : 1558608915
New from $50.63
Format: PDF, EPUB
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Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality.
* Provides an accessible, enjoyable introduction to the subject of data accuracy, peppered with real-world anecdotes.
* Provides a framework for data profiling with a discussion of analytical tools appropriate for assessing data accuracy.
* Is written by one of the original developers of data profiling technology.
* Is a must-read for any data management staff, IT management staff, and CIOs of companies with data assets.
Direct download links available for Data Quality: The Accuracy Dimension (The Morgan Kaufmann Series in Data Management Systems) [Paperback] Free Download
- Series: The Morgan Kaufmann Series in Data Management Systems
- Paperback: 300 pages
- Publisher: Morgan Kaufmann; 1 edition (January 9, 2003)
- Language: English
- ISBN-10: 1558608915
- ISBN-13: 978-1558608917
- Product Dimensions: 0.6 x 6.3 x 8.8 inches
- Shipping Weight: 14.9 ounces (View shipping rates and policies)
Data Quality: The Accuracy Dimension Free Download
This book is the clearest, most practical book on data profiling and data quality that I have seen. Jack breaks down data quality issues into specific categories, and leaves you with a vision of what to do if you are building a data warehouse. His practical experience shows through very clearly and he talks to the IT developer (the reader) very effectively.
This book is on my very short list of essential reading for data warehouse professionals.
Ralph Kimball
Data Warehouse Author
Concepts and technical approaches for analyzing and improving the usefullness of source data are presented in a well organized and logical sequence. Not quite a roadmap/algorithm for achieving data quality; it's balanced a little more on the conceptual side. The techniques and concepts presented are ones you _will_ want to begin using if you have any data quality issues in your source data (and who doesn't), I guarantee that. As a working ETL developer referencing disparate, low quality data, this book has had an impact on our approach, our results, and our project. Short and to the point, it's an easy study also!
By K. Ambrose
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