Editorial Review:
A comprehensive guide to quality improvement from the leading expert in information and data warehouse quality.
Each year, companies lose millions as a result of inaccurate and missing data in their operational databases. This in turn corrupts data warehouses, causing them to fail. With information quality improvement and control systems, like the ones described in this book, your company can reduce costs and increase profits from quality information assets. Written by an internationally recognized expert in information quality improvement, Improving Data Warehouse and Business Information Quality arms you with a comprehensive set of tools and techniques for ensuring data quality both in source databases and the data warehouse. With the help of best-practices case studies, Larry English fills you in on:
* How and when to measure information quality.
* How to measure the business costs of poor quality information.
* How to select the right information quality tools for your environment.
* How to reengineer and cleanse data to improve the information product before it reaches your data warehouse.
* How to improve the information creation processes at the source.
* How to build quality controls into data warehouse processes.
AUTHORBIO: Larry P. English is the leading international expert in the field of information and data warehouse quality. He is a columnist for Data Management Review and a featured speaker at numerous Data Warehousing Conferences. Larry chairs Information Quality Conferences held around the world.
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Customer Reviews
Average Customer Rating: 
The bible of IQ  2006-05-16
To me it is the bible of information quality. Larry explains information quality in all its aspects and everybody who descide to step into this area should not read but study this book. This is a very good pylon on your journey with information quality.
I strongly recomend this book to others having deep interest in this area and open to understand that information quality is not a data cleansing or data assessment only.
Book is written at excellent form.
Deming for data  2004-10-01
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.
Answers Business Executives Concerns on Data Warehousing 2003-09-04
Data warehousing conjures many myths - both technical and business. Seldom is a marriage of business and technical skills more necessary than in data warehousing implementations.Many data warehousing books wax on the technical issues and requirements - such as data extraction, modeling etc. These are important and bring great benefits to any implementing team. However, till recently, there has not been a good book to follow through on the data warehousing implementation. The business benefits and how it can be enhanced from data warehousing are discussed in Larry English's book. Many reader, will no doubt, have data warehousing implementations and will want to enhance the investment. This is the book for you. Understanding the business is an almost primordial instinct that a data warehouse designer must have. Mr. English's book will enhance on this instinct and also give tips on cutting cost and finding areas of additional business value. Please let me know if you found this review helpful - contact me if you have any questions or suggestions. Thank you.
This is a "must-have" guide 2003-01-24
Some books belong on a shelf in the library; not this one! As a quality practitioner, this book stays on my desk where it belongs - in active use! "Improving Data Warehouse and Business Information Quality" is a 518 page source of enlightenment and should be considered mandatory reading; not only for Data Warehouse professionals but for every knowledge worker and business manager. This book "delivers the goods" and then goes the extra mile by transcending industries and corporate levels to promote a deep understanding of quality concepts. Not only does Larry use relevant examples to show causes and effects of poor quality, he also shares practical advice that is meaningful and can be readily implemented. Larry's writing style and human component make reading this book very enjoyable and thought provoking. I have used this book for over four years and found no other book to be as relevant and useful.
Data is an Asset 2001-04-17
I have been an information systems professional for several years now and I am happy to see that there is finally a focus on data as the asset it truly is. If I could put "certified data" on the Balance sheet as a separate line item, I would. I have been reading your book "Improving Data Warehouse and Business Information Quality" over the past several weeks and I have this ear-to-ear grin that some peers find disturbing. (Why does he get so excited about data?) High Quality Data=success.
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