| Data Mining with Microsoft SQL Server 2008 | 
 enlarge | Authors: Jamie Maclennan, Zhaohui Tang, Bogdan Crivat
Publisher: Wiley
Category: Book
List Price: $50.00
Buy New: $29.05
You Save: $20.95 (42%)
Buy New/Used from $29.05
Avg. Customer Rating:   (2 reviews)
Sales Rank: 26235
Languages: English (Original Language), English (Unknown), English (Published)
Media: Paperback
Number Of Items: 1
Pages: 672
Shipping Weight (lbs): 2.1
Dimensions (in): 9.1 x 7.3 x 1.6
ISBN: 0470277742
Dewey Decimal Number: 005.7585
EAN: 9780470277744
ASIN: 0470277742
Publication Date: November 17, 2008
Availability: Usually ships in 1-2 business days
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| Editorial Reviews:
Product Description
Understand how to use the new features of Microsoft SQL Server 2008 for data mining by using the tools in Data Mining with Microsoft SQL Server 2008, which will show you how to use the SQL Server Data Mining Toolset with Office 2007 to mine and analyze data. Explore each of the major data mining algorithms, including naive bayes, decision trees, time series, clustering, association rules, and neural networks. Learn more about topics like mining OLAP databases, data mining with SQL Server Integration Services 2008, and using Microsoft data mining to solve business analysis problems.
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| Customer Reviews:
 A plug-in developer must read December 17, 2008
3 out of 3 found this review helpful
This book was a very useful resource while developing a plug-in algorithm to the SQL Server Data Mining framework. I have had mixed results in the past trying to integrate into the framework, but both this book and the previous SQL Server 2005 version answered all my questions and helped me and my company to create a much improved product offering. With a little bit of time vague requests like "build a recommendation engine" can be turned into crowd pleasers, without having to delve into custom algorithm development and extensive research.
The price tag is a little steep, but the content is well worth it.
 Don't Waste Your Money December 15, 2008
0 out of 7 found this review helpful
This book is typical of titles confined to a single vendor's tool. The focus is on this tool's features, not data mining. Learning the principles of data mining first will make a book like this unnecessary, and help you avoid pitfalls not covered by books like this one.
If you want to understand data mining, I recommend titles such as:
"Data Mining: Practical Machine Learning Tools and Techniques, Second Edition", by Witten and Frank ISBN: 0120884070
or
"Data Mining, Second Edition : Concepts and Techniques, Second Edition", by Han and Kamber ISBN: 1558609016
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