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Summary: This book has a companion web site at www.data-miners.com
Review: Visit this site to learn more about data mining and to see an outline and excerpts from the book Find out why Ralph Kimball, writing in DBMS magazine, says "I am indebted to Michael Berry and Gordon Linoff for their wonderful new book, Data Mining Techniques for Marketing, Sales, and Customer Support." and David Stodder, editor of Database Programming and Design, calls the book "excellent" and says it "has a ring of authenticity" and is "refreshingly free of over-hyped methodology."
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Summary: An excellent conceptual description of an important topic.
Review: When I started data mining (over 25 years ago)after graduating from MIT, neither the name nor the techniques existed. I had to develop both concepts and approaches that were then applied to situations as varied as evaulating the US SBA for the Federal Government to mapping the market for and product requirements of ATM machines for a Fortune 500 to developing a strategy to export shoes (leading to a tripling of industry exports) for the Commerce Dept. to predicting the lodging demand in Orlando, FL during the gas crisis for a series of majorinvestors to making sense of survey data for a major credit card company. The approach accurately described the situation in all of these cases and led to major management decisions. The authors go beyond what I used in those days, describing a series of techniques and their applicability - through easily understood case studies. This is not only an intelligent book, it is a very easy read. It doesn't go into mathemetical complexities because that is unnecessary. There are many treatises available on those subjects. Just surf the web to find some of them. This book provides the information required by managers, leaders, and entrepreneurs to understand their marketplaces and customers. Having run many companies and turned around a lot more, it is clear that this understanding is often sorely missing. Once gained, sharp increases in profitability usually result. The trick is something like an "aha" effect, an invention. The data is stored in a person's unconscious and, through predictable processes, pops out somewhat on demand. Data mining is the process of causing similar "aha's" to pop out of the unconscious, the collective memory, of a company. I recommend this book highly as a way to gain an effective understanding of how to do this.
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Summary: Too many unnecessary details
Review: While the authors provide a very comprehensive overview of data mining, they do go into too many details and as a result many critical points are lost. The authors are clearly motivated and therefore they discuss all they know in data mining. They should have selected some of the key points and elaborated on them.
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