database management systems

The chapters on estimating your organization's cost of having non-quality data make this book a requirement for every Information Resource Management professional's book shelf.

Larry English is one of the few authors in the industry to show you how to work the numbers when it comes to data quality. While others drop hints at why quality is good, Mr. English tells us how to collect the data and how to calculate the true costs of sub-standard data management practices.

As our profession matures we will be called upon to make more explicit business cases for what we recommend to senior management -- Larry has some great methods for us to use. This will save us months of having to figure it out for ourselves.

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.

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.