| Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM) | 
| Author: Danette Mcgilvray
Publisher: Morgan Kaufmann
Category: Book
List Price: $54.95
Buy New: $42.34
You Save: $12.61 (23%)
Buy New/Used from $42.34
Avg. Customer Rating:   (6 reviews)
Sales Rank: 129020
Languages: English (Original Language), English (Unknown), English (Published)
Media: Paperback
Number Of Items: 1
Pages: 352
Shipping Weight (lbs): 2.4
Dimensions (in): 10.8 x 8.4 x 0.8
ISBN: 0123743699
Dewey Decimal Number: 658.404
EAN: 9780123743695
ASIN: 0123743699
Publication Date: July 18, 2008
Availability: Usually ships in 1-2 business days
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Product Description
Information is currency. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. In this important and timely new book, Danette McGilvray presents her Ten Steps approach to information quality, a proven method for both understanding and creating information quality in the enterprise. Her trademarked approachin which she has trained Fortune 500 clients and hundreds of workshop attendeesapplies to all types of data and to all types of organizations.
* Includes numerous templates, detailed examples, and practical advice for executing every step of the Ten Steps approach.
* Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices.
* A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from the Ten Step methodology, and other tools and information available online.
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| Customer Reviews: Read 1 more reviews...
Good text on DQ Project Management November 25, 2008
Danette has a lot of experience in planning, managing, and executing data quality programs - I highly recommend this book!
Excellent book for Data Quality professionals October 23, 2008
1 out of 1 found this review helpful
I have read everything Tom Redman and Larry English have written. Their work has been very instructive and has helped me a great deal in my work. In fact, I used their work, as well as that of luminaries like Jack Olsen, to gain approval for an enterprise-wide information quality management program at a Fortune 500 bio-pharmaceutical company. I am now responsible for executing this program and having these responsibilities, there is no reference that I'm finding more useful than Danette McGilvrey's book.
This is not just a book. It is a "How To" manual. Danette's book fills a real gap in the Data Quality literature. If you want to improve your company's data quality management practices through excellence in executing data quality projects, there is nothing else you can read that is quite as practical and hands-on.
Much needed addition September 2, 2008
Danette McGilvray's new book is a welcome addition to the data quality literature. Finding and eliminating root causes of data errors is essential to any data program. And most people "learn quality improvement by doing," following step-by-step instructions--much as someone just learning to cook sticks close to the recipe.
McGilvray does an excellent job of putting quality improvement in context and narrowing her focus. Make no mistake. This book is specially written for project managers, who must lead improvement teams over often-confusing terrain, and for team members who must do the work.
This book is clearly written. It is richly detailed and chock full of templates that will help project teams move rapidly. It gets my heartiest endorsement.
Comprehensive and practical July 31, 2008
A strong--and welcome--addition to the data quality literature. I love the "workbook" format, and commend Ms. McGilvray and her publisher for this informed, important, and most of all helpful Baedeker.
Comprehensive, yet easy-to-understand approach to Data Quality July 28, 2008
1 out of 1 found this review helpful
This book is a practical approach to data quality. I like that it gives many different dimensions to data quality, so that we can easily drill down into why the "data is wrong" by having a common vocabulary.
It's a practical approach to getting the data clean and keeping it that way. It's written in a very approachable way that doesn't talk down to me as a reader. I am very happy with my purchase
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