Data Quality: The Field Guide Review

Data Quality: The Field Guide
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I like this book quite a bit because although it's not a huge doorstop of a tome in terms of length, it's quite complete and thorough. Some data quality books cover management aspects, some the technical aspects, and some take other angles. This book takes a look at all of the different angles on data quality and sums them up into a very nice package.

One of the things I liked about it is the section on social aspects of data quality, since so many technical people I work with have a great idea but aren't able to implement it for lack of understanding of the social aspects of working on data quality projects. Another is a part where Redman goes through the process of how data quality is tracked over time, to see if things are improving, and the way that he draws a distinction between records that are "perfect", and records that are "usable", which points out some differences that are important. There is even a very relevant section on data quality problems in the US elections of 2000.

The nice thing about this field guide is that it should have everything an organization needs to do some serious data quality work (including even middle management roles and responsibilities). I think it's a very solid book that would be a great addition to data manager's and other tech manager's libraries.

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Can any subject inspire less excitement than "data quality"? Yet a moment's thought reveals the ever-growing importance of quality data. From restated corporate earnings, to incorrect prices on the web, to the bombing of the Chinese Embassy, the media reports the impact of poor data quality on a daily basis. Every business operation creates or consumes huge quantities of data. If the data are wrong, time, money, and reputation are lost. In today's environment, every leader, every decision maker, every operational manager, every consumer, indeed everyone has a vested interest in data quality.Data Quality: The Field Guide provides the practical guidance needed to start and advance a data quality program. It motivates interest in data quality, describes the most important data quality problems facing the typical organization, and outlines what an organization must do to improve. It consists of 36 short chapters in an easy-to-use field guide format. Each chapter describes a single issue and how to address it. The book begins with sections that describe why leaders, whether CIOs, CFOs, or CEOs, should be concerned with data quality. It explains the pros and cons of approaches for addressing the issue. It explains what those organizations with the best data do. And it lays bare the social issues that prevent organizations from making headway. "Field tips" at the end of each chapter summarize the most important points. Allows readers to go directly to the topic of interestProvides web-based material so readers can cut and paste figures and tables into documents within their organizations Gives step-by-step instructions for applying most techniques and summarizes what "works"

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