Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM) | 
 enlarge | Author: Danette Mcgilvray
Publisher: Morgan Kaufmann
Category: Book
List Price: $54.95
Buy New: $44.59
You Save: $10.36 (19%)
New (24) Used (7) from $43.83
Avg. Customer Rating:  4 reviews
Sales Rank: 237797
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
Shipping: International shipping available
Condition: Brand New, Perfect Condition, Please allow 4-14 business days for delivery. 100% Money Back Guarantee, Over 1,000,000 customers served.
|
| Similar Items:
|
| Editorial Reviews:
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.
|
| Customer Reviews:
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
 Practical new book on data quality (projects) July 25, 2008
1 out of 1 found this review helpful
At first when I recieved this book over in The Netherlands (much quicker than estimated by the way!) I thought it would become a little hard to read. This was because of the big size and amount of pages (289) of the book.
But when I looked further into the book it became clear that it was a thoroughly, but very well readable book. The writer has found a way to describe difficult things in an easy and understandable way.
By the way; the writer (Danette MacGilvray) years ago got into the field of Data Quality because she worked on a assignment at Hewlett-Packard. It was this project where worked together with "consultant" Larry English and got inspired and educated by him and his TIQM-method.
By using many bulletpoints, easy steps and sub-steps, examples, check-lists, boxes and templates this book has become easy and fun to read from A-Z. On the other hand, when in you're daily practice you have to deal with a diffucult IQ or Data Quality problem this book comes in als handy, because it is very good for reference-purposes.
The book's own website (http://www.books.elsevier.com/companions/d9780123743695) with lots of material makes this all complete.
With her Ten Steps approach (based on years of experience in the work field of Danette) the writer has found a way to specify and bullet-point the most important data issues in you're company, get the fundings you need and break down difficult data quality projects in 10 steps.
Not only is the book based on her own experience, this book is also a blend of experience and proven techniques from people from the Information or Data Quality field like Larry English (Improving Data Warehouse and Business Information Quality: Methods for Reducing Costs and Increasing Profits), Jack Olson (Data Quality: The Accuracy Dimension (The Morgan Kaufmann Series in Data Management Systems), Tom Redman (Data Quality: The Field Guide) and Gwen Thomas.
So by reading this you get the best of all!
I work as a Data proces & quality manager in an home shopping business, so we are a "data intensive organisation". I think I will use this book (and the 10 steps) quite often.
|
|
|
