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Data Quality For The Information Age
Thomas C. Redman

Artech House Publishers, 1997 - 332 pages

average customer review:based on 2 reviews
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Practical Guide to Data Quality

This books brings a perspective to the data quality issue that I had never truly appreciated. More importantly it gives the reader suggestions as to how to understand the impact of poor data on their organizations as well as specific techniques to make it better. I would recommend this to any person who is looking to improve any aspect of their business as most issues will eventually come back to ensuring quality information to internal and external customers.


For both business leaders and information professionals

I found a lot of great material in this book, appealing to my interests in both business leadership and the more technical aspects of data quality. From the perspective of business leadership, I find it to be a very helpful tutorial and overview of the subject of data quality. It covers a lot of ground, ranging from discussions of data quality management concepts to specific suggestions for implementing data quality programs. From the perspective of a consulting professional, I find it to be an excellent reference, with depth in key topics of interest to process, information and quality professionals. In particular, the discussions about the "data life cycle", the technical definitions of data and the "dimensions of data quality" gave me new insights into data quality management and improvement.


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Written by the inventor of many modern techniques for data quality, this book provides anyone responsible for information management in their company with the knowledge necessary to set up a data quality program, make and maintain improvements, and create a discernible business advantage. The author emphasizes practical applications and analyzes quality problems and their impacts, potential solutions and how they are combined to form an overall data quality program. He discusses senior management's role, various methods to make and sustain improvements, and the life-cycle and dimensions of data quality. The book includes case studies, and summaries of main points.


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