Data Mining with SQL Server 2005

I was really impressed with this book. It had a great introduction to demystify the typic of data mining. Since the learning curve on this topic is so high, these first few chapters are essential. It then immediately jumps into a practical example to help the reader bring it all together. The chapters get progressivily more difficult through the book and there's a chapter for each of the algorithms. The author team did a fantastic job and I'd highly recommend it.

Some people commented on the poor editing: typos & some wrong pictures. True. (It detracts, but you can figure it out easily) Some stated that it is not a good general overview of Data Mining. True (though it has a bit of a summary) Some stated that is doesn't discuss business applications in detail. Yes, (it only makes brief reference to them). Some stated that it is very vendor specific. Hello, read the title - SQL 2005. It is a must read for anyone who wants to take maximum advantage of SQL Server 2005 Data Mining. It goes thru all the algorithms, tells you how each one works, how to tune them & how to embed them into your applications. It compliments the Books On-Line materials, tutorials & sample code that ship with the product. (interesting how people pay for a textbook & never bother to read the copous amount of materials that ships with the product.) It does give you a bit of background in DM, & does walk you thru using the tools (SSMS & BIDS) used to create & administer the Data Mining. It doesn't talk about using the Data Mining Viewer controls in Visual Studio 2005. It is an easy read & very informative. Especially if you go to the trouble of downloading the samples & data from the web site & actually build the models with the book & step thru the code. While it isn't really an indepth treatment of DMX in the way that "George Spofford's MDX Solutions" is for MDX. It does give you more than enough examples to be able to create, train & predict from the models. It also gives enough to embed your DM models into your applications, Use them from Excel & take full advantage of the DM built-into SQL Intergration Services. If you want an DM Overview for business use - check out Barry Lindof's book

This is a great data mining book for database developers/DBAs, especially for those who are using SQL Server database. There are simple and clear explanations of several popular data mining algorithms,plus lots of examples about how to solve business problems using these algorithms, code examples for SQL Server. This book is a must for those who wants to use SQL Server data mining for their projects. There are still some editing errors in the book.

I wouldn't normally review my own book, but I think the previous reviewer missed the point. This book is clearly about data mining in the context of the features of SQL Server 2005. It does not pretend to be anything else, and pretty much states so directly in the title. If you are looking for a generic, vendor neutral "all-up" book about data mining, its methods and applications, you're right, this book is not that book. However, if you want to learn about the data mining features of SQL Server 2005, how they work, how to use them and exploit them for your own analyses and applications, this is the book to read.

There are precious few books written about Data Mining and this is the only one about SQL Server 2005 specifically. Beyond its originality, it is concise and well written. The first chapter is an introduction to Data Mining and it details exactly how Data Mining can be used in many different application scenarios. The remainder of the book is a detailed examination of all the new features and algorithms available in SQL Server 2005. It contains practical and relevant examples in an easy to read and intuitive style. Even though the basic concepts involving Data Mining remained the same between SQL Server 2000 and 2005, there were significant enhancements made to the number and complexity of the data mining algorithms and the tools used to interpret data mining results. Without the inside knowledge provided in this book, even seasoned data mining users may miss some important opportunities. I would strongly encourage anyone even remotely interested in data mining to get this book and start discovering how data mining can separate their applications from all the others.