Customer Review

December 28, 2008
Be careful, the first edition is MUCH older. Make sure you get the current 2004 edition.

There are most recent books, but this one is still worth reading first. This is especially true is you are an analyst. Managers of analysts might enjoy Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart or Competing on Analytics: The New Science of Winning, but analysts will need much more detail.

This the best single volume on Data Mining you can buy. As one who mostly teaches methodologies, I like that all the major topics are here: neural nets, market basket, cluster, and trees. But there are also techniques that SPSS and Clementine (the software packages I use) can not do like "link analysis". Also, unlike Larose Discovering Knowledge in Data: An Introduction to Data Mining, the data preparation reads like preparing data for data mining, not a carbon copy of preparing data for statistics. Regarding this issue see the excellent Data Preparation for Data Mining (The Morgan Kaufmann Series in Data Management Systems). I have pretty much concluded that a data mining book that does not make clear that data mining and OLAP are not the same is not a great book. This book has an extended section on just that. It is highly readable and comprehensive.
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