- Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems
- Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer support
- The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining
- More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining
- Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis
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Average Customer Review:
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27 of 28 found the following review helpful:
 The first book on Data Mining everyone should readMay 03, 1999
By Gustavo Denicolay
It covers almost every aspect of data mining. It is clear, precise, goes to the point, and sometimes goes into some depth. If you are a marketing person, it will give you a very refined idea of what can be done with data mining, and what does it involves for your company ( remember the first thing you need is DATA!!). If you are an academic person, you will get a general idea of the different kinds of data analysis. You won't see any formulae or algorithms, after reading this book look for details somewhere else.
26 of 27 found the following review helpful:
Author's commentApr 20, 2005
By Michael Berry
"data mining author"
Although this book was not written as a text book, we have noticed that it is frequently used that way. For the benefit of instructors, we have collected some exercises and datasets that can be used in the classroom or for self study. These can be found at www.data-miners.com/companion.
23 of 25 found the following review helpful:
 Depends what you want this book forApr 01, 2001
By Alex
This book gives an overview of what data mining is and the tools available to perform it; Market Basket Analysis, Memory Based Reasoning, Automatic Cluster Detection, Link Analysis, Decision Trees, Artificial Neural Networks. Genetic Algorithms are also included, which, while not a data mining tool, are being used to train neural nets.In each case the authors describe the principles behind the tool, its strengths and weaknesses and applications were it is applicable. The authors give tips on what data preparation is required for the tool, both in terms of data "massaging", (which is required for neural nets) and indicate were it is important to select training sets that have approximately equal proportions of "good" & "bad" outcomes, in order for the tool to predict correctly. The descriptions include simple examples of the tool to give an overview of how the tool works. But as the title indicates, this book is for users who are considering using data mining tools. It does not describe how to use particular applications, neither does it include code examples (pseudo or actual) if you are interesting in developing your own tools. The book is easy to read and includes many examples from their experience of data mining in the real world.
18 of 19 found the following review helpful:
 Good Introduction book, not limited to MarketingDec 09, 1997
By crozas@adv.es
The authors explain in a detailed way the most popular Data Mining techniques. The topics about Neuronal Networks, Decision Trees, Market-Basket Analysis and Memory-Based Reasoning are excellent. I think the topic Genetic Algorithms could be a bit more developed, but for the beginner is a good first overview. I have missed a topic about fuzzy logic. Given that the 90% of Data Mining projects are based on Marketing (1:1), the book is absolutely suitable for starting with these concepts, although I feel the book can be used in any other field (Just-In-Time Inventory, Demand Forecasting, Supply Value Chain, etc.)
In my opinion, it was very useful for my work and I considered it as a reference book.
50 of 62 found the following review helpful:
An excellent conceptual description of an important topic.Aug 28, 1999
By Stuart A. Lichtman
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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