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Data Quality: The Field Guide
 
 
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Data Quality: The Field Guide [Paperback]

Thomas Redman PhD (Author)
4.8 out of 5 stars  See all reviews (10 customer reviews)

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Book Description

1555582516 978-1555582517 January 11, 2001 1
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 interest
Provides 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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Customers buy this book with Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM) $47.40

Data Quality: The Field Guide + Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM)


Editorial Reviews

From the Publisher

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.

About the Author

PhD, President, Navesink Consulting Group

Product Details

  • Paperback: 256 pages
  • Publisher: Digital Press; 1 edition (January 11, 2001)
  • Language: English
  • ISBN-10: 1555582516
  • ISBN-13: 978-1555582517
  • Product Dimensions: 9.2 x 6.9 x 0.6 inches
  • Shipping Weight: 1 pounds (View shipping rates and policies)
  • Average Customer Review: 4.8 out of 5 stars  See all reviews (10 customer reviews)
  • Amazon Best Sellers Rank: #99,378 in Books (See Top 100 in Books)

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Customer Reviews

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Average Customer Review
4.8 out of 5 stars (10 customer reviews)
 
 
 
 
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Most Helpful Customer Reviews

11 of 11 people found the following review helpful:
5.0 out of 5 stars Complete and Thorough, July 27, 2004
By 
D. Allen "DQM" (Richmond VA, USA) - See all my reviews
(REAL NAME)   
This review is from: Data Quality: The Field Guide (Paperback)
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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6 of 6 people found the following review helpful:
4.0 out of 5 stars Good Practical Advice, August 8, 2004
This review is from: Data Quality: The Field Guide (Paperback)
Good practical advice for improving data quality. Covers the most common data quality problems. Well written. Some other sources to look at online:


http://www.dmreview.com
http://www.datalever.com
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6 of 7 people found the following review helpful:
5.0 out of 5 stars Extremely Helpful, March 8, 2001
By A Customer
This review is from: Data Quality: The Field Guide (Paperback)
This book gives excellent insight to the practical issues associated with data quality. The book gives some great suggesions on how businesses can improve performance through a focused approach to managing information. I enjoyed reading it, and have actually begun to use some of the ideas presented in the book in my current job.
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Inside This Book (learn more)
First Sentence:
"Some think that no two words can cause a chief executive officer's eyes to glass over faster than ""data quality"" (and this applies to heads of government agencies, leaders of nonprofit organizations, etc.)." Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
information chain management, data supplier management, erred data, data quality efforts, new information chains, data quality program, data quality systems, responsibility for data quality, billing chain, data quality levels, data resource data, data quality management, data council, postal standard, data quality improvement, poor data quality, improving data quality, data quality problems, data culture, supplier manager, decision chain, chain owner, field tips, data creation, future errors
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Field Tip, The Field Guide, Second-Generation Characteristics, Information Age, United States, The New York Times, Chinese Embassy, Data Laboratories, Joseph Juran, Time Period Figure, Are These Prices Correct, Chief Information Officers Are Stuck, Internet Users Wonder, Recognizing Social Issues, Coms Better Make Sure They Are, Identifiers Key, Marketers Need, Sense Clear
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