Customer Reviews

Data Preparation for Data Mining (The Morgan Kaufmann Series in Data Management Systems)

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2 star:		(1)
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I've had the pleasure of listening to Dorian speak at seminars and even sharing a few brief words with him in person. When he mentioned to me last year that he was working on this book I had no idea how thorough and complete it would be. In fact, I remember wondering to myself how anyone could get their hands around this difficult, yet important aspect of data mining. I'm in awe! Anyone in the trenches will immediately understand the value of this book. Those just getting started in data mining will probably have no idea how much simpler their job just became. My only criticism of this book is that its title obscures that fact that there is a wealth of general data mining information contained within it - practical well beyond the data preparation phase. To understand why and how certain data preparation techniques work is to go a long way towards appreciating subtleties throughout the rest of the data mining process. Thanks Dorian!

This book is simply great, it provides the best practices about the essence of data mining : data preparation

Any analyst knows that 80% of data mining time is spent in data preparation, nevertheless most authors focus on the remaining 20% : techniques and tools, where the value is more "visible"

The truth is that this value is unavaillable, unless you get data prepared, and that's the difficult job

Dorian book's allows you to understand this obscure process through a great analytical process. Strongly recommended

The book "Data Preparation for Data Mining" is not a common Data Mining book. Nowdays a classical Data Mining book contains a metodology how to solve class of standard problems. This means more a set of prescriptions and receipts for elaborating various solutions to customer loyality, retention etc.
The book by Dorian Pyle is different.It is not a Data Mining book, because as the authors claims, Data Mining is only a part of wider subject, which he calls Data Exploration. He shows us wider spectrum of various subjects considering data than you can find in other books. He gives us a good background that helps to recognize the source of problems with data. Some subjects are not to find in other sources. They come directly from author's reach experience. To summarise - the autor of the book managed to describe the whole subject area considering data, that is not to find in other books on this topics. To achive that knowledge we should read many other publications from different areas.

Anyone who practices data mining lives the issues discussed in this book. The book dissects and explains important data challenges.

Dorian communicates far more than knowledge about the nomenclature of the problems. His focus is instead on the trade-offs one makes while wrestling with data issues. He provides sage counsel on how the practioner can address data for the specific types of analytical problems one faces.

I own about 15 data mining books, this is the one that I use the most.

I was in the market for some information on how to scale data before using it with a neural network. After trying to wade through material that was somewhat inaccessible to my feeble brain, this book saved me. I was able to implement a simple scaling system in less than 2 hours. I later asked one of the econometricians at my company if I had done the scaling properly, and he said I did! This book is simple to understand, and best of all, it was correct!!

There are more books available now on data mining preparation but Pyle's book is the best one :
- very clear
- covering all the important topics to need to learn about
- based on many examples and advices coming from real life
To buy absolutely

I started to work in Data Mining about 7 years ago. I have read many books about this subject and nearly all of them have similar approaches and stress the importance of the data preparation but they all, except one, just discuss lightly this subject. I don't know any book that deal with data preparation as Pyle's book does. Each topic is discussed in-depth. This is a very clear and enjoyable book. I have tested all concepts and the results are amazing.

Chapter 11 introduces the Data Survey topic in which techniques based in Shannon's Information Theory are showed. These information theory approaches are simply wonderful and gives to the Data Mining subject the bases to get models that extract complete relevant information from the data.

I recommend this book to anyone who wants to work seriously with Data Mining.

I have been helping folks learn Clementine - a data mining package - for several years. I have read a number of related books, but never got to this one until recently. That was a mistake. This may be an important book for you if you are new to Data Mining, even if, especially if, you already have expertise in statistics and/or data base technology.

Although I still believe if someone is brand new to the field that they begin with Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, this should be the second book that they read. Far too many books in this area read like statistics books (notably Data Mining Methods and Models).

Statistics training can be of enormous benefit to data miners, but leads to certain predictable errors. Not only that, many data miners already have statistics training and that just compounds the likelihood that they will make these mistakes when the book author fails to show the difference clearly. Pyle performs consistently well in this regard. He consistently focuses on the kinds of problems data miners are likely to see in their work.

To give just a couple of examples: Few variables will be already stored as continuous, normally distributed variables; principle components analysis might sometimes be a problematic way to eliminate predictors and even be dangerous; missing versus "empty" data; constantly present non-linearity.

His practice data set has a real variety of variable types, and dozens of predictors. If you are figuring out if Data Mining can help you, start with the Berry/Linoff book. But .. if you are about to begin in earnest read this book. Then, time permitting; start reading specific books on modeling or software. For instance, another Larose book has good, detailed coverage of algorithms, and some information on Clementine. Discovering Knowledge in Data: An Introduction to Data Mining

This book covers the topic of data preparation very thoroughly.However, it includes source code that won't compile. The book comes up short in referencing the source code that is included on the CD to the various methods that are described in the book. If you don't care about the source code, the book is good. But, if you're a programmer as I am, you expect the source code to work!

As the old saying goes, Garbage In, Garbage Out (GIGO). "Data Preparation for Data Mining" is the remedy for this pervasive, age-old problem. There are so many different aspects to data quality, it boggles the mind. Mr. Pyle addresses each one in detail, with clear examples and explanations.

The book is well-written and more importantly, understandable. It should be required reading for every researcher and modeler BEFORE they begin their careers. The way data is prepared and aggregated determines the picture one gets from the data. It must be done correctly from the start, or all downstream processing and conclusions are suspect.

The CD that comes with the book is pretty much useless, but aside from that caveat, this is a great book. Buy it - you won't be disappointed.