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More About the Author
Product Description
Masaaki Imai, Founder, Kaizen Institute and Bud H. Cox, Managing Director, Kaizen Institute of Japan
The Information Quality Bible for the Information Age!
Bill Inmon, "Father of Data Warehousing", Pine Cone Systems
...very lively reading. This book belongs on the bookshelf of every manager and technician.
Inside This Book
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First Sentence
In this chapter I describe the reason why an organization is-or should be-interested in information quality. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
In this chapter I describe the reason why an organization is-or should be-interested in information quality. Read the first page
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Browse Sample PagesConcordance
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Customer Reviews
Most Helpful Customer Reviews
10 of 11 people found the following review helpful
Format:Paperback
Anyone who has had the pleasure of hearing Larry English speak on the subject of Information Quality will know that he is one of the leading and most passionate advocates of the need for high information quality as the foundation of a profitable business.
As we enter the age of eBusiness,companies can no longer hide their information quality problems from their customers. Successful eBusiness companies will be those who recognise and manage information as their key strategic asset.
This book is essential reading for all who are serious about profitable survival in the information age. Larry writes as he speaks - with knowledge, conviction and pragmatism. This book should be read by all who are concerned about information, whether senior corporate executives, business information managers or IT specialists.
The book is full of practical answers to problems and is of great value whether you are leading a major cross-enterprise information improvement drive or trying to enhance quality within a specific data warehouse or system.
Strongly recommended.
1 of 1 people found the following review helpful
Format:Paperback
This book is inspiring and helping anyone lost in an enterprise data mess who wants to do something about it. Larry gives you a context for action and even has a fair and pragmatic cookbook for making your data quality case. It's well written and comes from a mind with a lot of knowledge in the area. Read it!
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
17 reviews
11 of 11 people found the following review helpful
Excellent ideas for implementing a data quality program
21 July 1999
Format:Paperback
The book is fantastic. English obviously has plenty of front line experience. He doesn't simply state the problem and offer suggestions. He empowers the reader to join the data quality movements by giving them the tools necessary to convince the decision makers that data quality is worth the investment. Chapter Seven, "Measuring Nonquality Information Costs," is worth the price of the book alone, because it gives us a solid ROI model to throw at the bean counters. The writing style is extremely accessable. The book is so well organized that it can be read straight through or employed as a reference.
14 of 15 people found the following review helpful
An important and unique work
25 Feb 2001
Format:Paperback
This is an important and unique work that addresses a big problem: data quality. Why is this a problem? Data warehouses are proliferating at a dizzying rate. Since data warehouses are fed by production databases, many of which are legacy systems, the poor quality of existing data quickly becomes [painfully] apparent. I spent the last half of 2000 bringing data warehouses into production and can attest to this sorry fact. However, the author drives home this point in chapter 1, titled "High Costs of Low-Quality Data" by giving nearly three pages of eye-opening examples from real life. This alone should inspire anyone responsible for data integrity or quality, or who uses data to carefully read this book.
The big question is "what is quality"? Specifically, "what is information quality"? Answers to these basic questions are given early in the book, and sets the tone for what follows. The foundation of data quality is carefully built by how the author applies quality principles to information, which segues into a chapter on improving information quality. It quickly becomes obvious that Mr. English is a Deming fan - although I am more in the Juran camp, I like the way that the author places data and information quality into a recognizable framework.
Things get interesting in the chapters on assessing data and information quality. The two chapters devoted to this subject are strengthened by the chapter on measuring the costs of non quality. This is a great foundation for a business case for data and information quality improvement, which can be expensive.
The rest of the book is a step-by-step approach to getting data quality under control using data reengineering and cleansing; proactive measures for data defect prevention, and how to establish an information quality environment.
Although I found every chapter to be both informative and thought provoking, I particularly liked the concept of information stewardship (this goes far in aligning IT and business, and places roles and responsibilities where they belong), and the chapter on implementing a quality improvement environment. This is especially valuable because it clearly outlines the critical success factors and steps needed to get there.
Who should read this book? Obviously DBAs, data architects and anyone else responsible for designing and implementing data warehouses. It should also be read by key business process owners because they, after all, own the data (or should) and depend on it as the basis for information. In fact, Mr. English's approach and writing make this book highly accessible to non-technical readers, which is probably the book's most valuable aspect. I personally believe that this book is the best on the subject and strongly recommend it.
8 of 8 people found the following review helpful
Deming for data
1 Oct 2004
Format:Paperback
While providing some of the traditional quality assessment measures, Larry English provides a Deming 14-points approach to information quality and continuous data quality improvement. For example, instead or rewarding those who find major quality problems, change the culture to provide quality early in the process. His chapter on "assessing data definition" quality is an important step often neglected. For example, some of us are may be using minimal metadata (perhaps federally mandated standards) that are inadequate for true enterprise wide data definition. The examples included in the book (particularly in "High costs of low quality data") are instructive, and show how someone saturated with thinking about quality (like Larry English), views such simple things as getting a fax at a hotel. If you are planning a data warehouse, this book might fit nicely into the "Enterprise Infrastructure Evaluation" phase in Moss and Atre's "Business Intelligence Roadmap" terminology.
I would have liked more specific methods of detecting low quality in the section on information quality assessment. The final third of the book, on establishing the information quality environment, provides good direction, but seems too optimistic. How does a single database analyst change a corporate culture and how does a small warehouse group influence the quality processes of hundreds of diverse data sources? This is a good, thought-provoking book.
I would have liked more specific methods of detecting low quality in the section on information quality assessment. The final third of the book, on establishing the information quality environment, provides good direction, but seems too optimistic. How does a single database analyst change a corporate culture and how does a small warehouse group influence the quality processes of hundreds of diverse data sources? This is a good, thought-provoking book.
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