Data Mining

Data Mining Techniques by Berry and Linoff

It is highly readable and comprehensive, but not especially technical. Read my review of an earlier edition.

 

 

 

 

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Data Analysis Using SQL and Excel

This helped clarify for me what was possible in Excel. You really need to pair it with SQL, which does the heavy lifting. Even then, the author admits there are limits, he dedicates the final chapter to preparing data for a dedicated Data Mining tool. Recommended for the curious Data Miner, or for someone that has to make due with the resources you have.

 

 

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Data Preparation for Data Mining by Dorian Pyle

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). Full review here.

 

 

 

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The Larose Data Mining Trilogy

Discovering Knowledge in Data
by Daniel T. Larose

I have softened my opinion of this book. My original review appears as a post in the blog.

Here is my review on Amazon.

There are two more in the series, but I consider them weaker than the first one.

 

 

 

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Data Mining Methods and Models

 

 

 

 

 

 

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Data Mining the Web

 

 

 

 

 

 

 

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Data Mining with Decision Trees

Strictly for Computer Scientists. Data Mining practitioners won't find much here.

 

 

 

 

 

 

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General Audience Data Mining

The Long Tail

This is an important book. It is certainly the most important general audience book for a Data Mining practitioner. It may be an easy read, but its contents are important for Data Miners. However, it is essentially nontechnical, so a curious consumer would also enjoy it.

 

 

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The Numerati

This book got some poor reviews from technical folks that said they didn't learn anything. I doubt they did. It is a light read that helps explain where Data Mining is headed in various application areas. It is a good choice for a manager that wants to understand what Data Mining is, but not a good choice for that same manager's team that is actually going to do Data Mining. Some managers want a technical book, others don't. This is a light, non-technical, general audience book. When I finished it I sent it to my folks.

 

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Super Crunchers

This book pretends to be something that it is not. It pretends to be a fairly up to date assessment of where "Data Mining" is. It irks me how calculated the author was, choosing the title based on Market Research instead of a title that well describes the content. I still gave it 4 stars, but that was in 2008. I wouldn't rush to get it. What the book DOES do well is explain why organizations often fail to deploy the model. The chapter on medicine does a fine job at this.

 

 

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Competing on Analytics

I don't have a link to a review on this one. I include it because I borrowed a copy from a colleague and read 60% of it. It has become an influential book. It has become required reading for the non-technical managers involved in Data Mining projects. I think it is pretty good, but Data Miners will find the information a little mundane. For the non-technical managers that make up its audience, it might be a little heavy on detail. To his credit Tom Davenport has created a name for himself, and he has grown the business of Data Mining. Will end up on everyone's reading list at one point or another. There is now a follow-up.