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Summary: Data Mining Fundamentals
Review: Data Mining conjures up many myths - if you are interested in digging deeper and evaluate if data mining can server your business needs, start with this book.
This book does not go into the depth that could assist readers in performing data mining. This is a starter book that prod in the right direction without any unnecessary fluff.
Data mining is about observing and understanding the data - it is not a straight mathematical or scientific skill set. Specific algorithms can assist in data mining - a significant challenge, very often, is getting and preparing the data to get it to a state where data mining can be performed. This book focuses on the algorithmic side of the equation.
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Summary: Full of errors, poor english, lacks rigor
Review: Did we really need yet another book on data mining? This book lacks rigor; is full of errors and typos; appears to be written for the managers who want to impress other managers by throwing around buzzwords without really understanding what data mining is really about. I would not recommend this book. I returned my copy to the bookstore.
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Summary: Poorly worded. No depth
Review: Dismal notation coupled with incomplete or incoherent explanations make this book frustrating to read.
The author needlessly inserts layers of abstraction, making otherwise simple concepts and formulas unnecessarily time-consuming to understand.
The provided examples do make up for some of the deficiencies of the author's notation and poor wording, but not enough to make this book worth buying. The book covers many topics but does not go into sufficient depth. It's too technical for managers and not rigorous enough for technical professionals wishing to use data mining to solve real problems. If you are new to data mining, you may learn some useful overall concepts, but won't learn enough to apply them effectively. Experts should definitely look somewhere else.
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Summary: Very Good
Review: I am a Data Mining analyst and this Book is the best i have ever read. It should not be considered as an Introductory book to the subject, but for readers on an intermediate level. It has a concise and well written Intro in OLAP and then it elaborates on the different DM techniques. In my opinion this book along with the "Data Preparation for Data Mining" by Dorian Pyle are the 'must have' books for Data Mining Analysts.
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Summary: Impossible to Read
Review: I found this book so difficult to read and the English is so poor that I would not recommened it to anyone. There are many other books on the topic that are worthwhile
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Summary: Deep, comprehensive and practical + data mining software
Review: I learned about Data Mining - Concepts and Techniques from a friend who is a CS professor. He is using this book to teach his graduate and undergraduate classes and he said that the same book is also used by many leading universities such as Cornell, UC Berkeley, Georgia Tech. First I thought this book would be hard for me to follow because I do not have a degree in CS, and I just wanted to have a good comprehensive understanding of most technical data mining methods so I can advise my IT clients (I have read several other general data mining books, and they are not technical enough for me). I was pleasantly surprised by both the depth & scope of this book and its readability. Granted it requires more brain power than some other general books covering data mining and CRMs, but after reading this book, I feel I can talk and act like an expert. The book also has a forward written by Jim Gray. Jim Gray received the A.M. Turing award, widely regarded in industry circles as the Nobel Prize of computer science. In his early career Jim Gray worked with Ted Codd, the father of "relational databases," the modern database model in use today for more
Jim Gray said he learned a lot from this data mining book... There is also a companion software called DBMiner for this book, and one can get hand-on experience for data mining techniques such as association, classification, OLAP visualizer and clustering. I downloaded the software from the web site...
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Summary: The Master piece on Data Mining
Review: I learned so much from this book, and I totally shared what Jim Gray, A.M. Turing Award Winner, who is currently with Microsoft Research said about the book:
"I certainly learned a lot from reading the book. I found it very informative and stimulating, and I expect you will too." This book is for people who want to know how "data mining can uncover what products people buy together as well as suspicious/fraud activities in corporations (including cooking the book so expenses will appear as capital spending)." It does require some brain power to fully appreciate the book.
Enjoy!
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Summary: Litttle relevance to the real world
Review: I picked this book up recently, hoping to learn more about data mining. I am part of a team at a large insurance company that is focusing on customer attrition. Based on my my reading of the blurb on the back of the book, I thought this would help me. Boy, was I wrong. There is very little in this book that is relevant to the real world. Lots of equations but very little application context. Unless you are a math professor, I would skip this one and find something else.
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Summary: Just right
Review: I've been working with Data Warehousing for a few years, and stumbled upon this book here on Amazon a few weeks ago. I was leery at first because of it's obvious textbook price/look, but purchased it anyway, much to my delight. The book provides a very vendor neutral view of Data Warehousing and Data Mining, many data mining ideas and examples are presented throughout the book without any specific programming language used. I feel it allows you to implement the idea in your preferred method. I found the book more than worth the price, in fact I was asked to give a guest lecture/presentation at a University Data Mining class in the Spring and will definitely pull from this book for my presentation. Enjoy!
Rating: 
Summary: a very good book
Review: if you want to have an overview into how exactly data mining is done with a bit of practical flavor and more of the algorithmic inclination this book is for you. But i have been through a better bok so would rate it 4 instead of 5
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