Data Quality Assessment Paperback – May 14 2007
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This is one of those books that marks a milestone in the evolution of a discipline. Arkady's insights and techniques fuel the transition of data quality management from art to science -- from crafting to engineering. From deep experience, with thoughtful structure, and with engaging style Arkady brings the discipline of data quality to practitioners. David Wells, Director of Education, Data Warehousing Institute
About the Author
Arkady Maydanchik is a recognized practitioner, author, and educator in the field of data quality and information integration. He is a frequent speaker at conferences and seminars, and teaches data quality courses through the Data Warehousing Institute and through his company, Data Quality Group LLC.
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Most Helpful Customer Reviews on Amazon.com (beta)
With this in mind, it is easy to see why I was so pleased and surprised to find someone had written a book about the subject; especially as thoughtful and insightful a one as Quality Data Assessment.
Arkady Maydanchik brings years of experience and first-hand knowledge to the table, while organizing it into a logical, sequential and, most important, understandable manual. This book goes into the typical causes of data degradation as well as how to find it and begin the process of fixing it.
You can't even begin to fix your data until you have a clear picture of what's going on "in there", so data assessment is the first and maybe the most important step in achieving data consistency and reliability. If your work involves data assessment, migration creation or maintenance, you should have this book on your shelf. It's that simple.
But wait, there's more. This is just the first volume in a set of data assessment and cleaning processes, tips, tricks and tools books that will be forthcoming. I'm told that the second volume in this series will be published in October 2008. I know it sounds incredibly geeky, but I can hardly wait.
I especially liked portions of Chapter 8. They lay out a process for actually creating business rules, another one of those nettlesome tasks that people underestimate.
This book introduces the reader on a very high level precisely, but always easy to understand into several methods and techniques that can be applied to a data quality assessment project. It should be part of the toolbox for everyone concerned about data quality.
I bought the book after hearing Maydanchuk speak. Both the speach and the book are well organized and useful.
The book has a bit more than I found useful about how to organize your findings. I use his ideas all the time, but have not used his database at all. Shame on me!
The English is quaint in spots. What the heck!
Data quality is not fully established domain of knowledge so you can encounter many people with different opinions what data quality really is.
I think that this book very well summarizes knowledge of data quality domain both theoreticaly but more importantly practically. Author is long time practicioner and it is certain that he uses his knowledge troughout the book not just describing some theory unused or impossible to use in practice.
I also appreciate the style of writting. Author is trying to be clear about what he states, gives examples..
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