Data Mining with Microsoft SQL Server 2008

Data Mining with Microsoft SQL Server 2008

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by Jamie MacLennan, ZhaoHui Tang, Bogdan Crivat
     
 

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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,

Overview

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.

Product Details

ISBN-13:
9781118080009
Publisher:
Wiley
Publication date:
03/10/2011
Sold by:
Barnes & Noble
Format:
NOOK Book
Pages:
672
File size:
22 MB
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This product may take a few minutes to download.

Meet the Author

Jamie MacLennan is principal development manager of the SQL Server Analysis Services at Microsoft. He has more than 25 patents or patents pending for his work on SQL Server Data Mining, and has written extensively on the data mining technology in SQL Server. ZhaoHui Tang is a principal group program manager at Microsoft adCenter and inventor of Keyword Services Platform. Bogdan Crivat is a senior software design engineer in SQL Server Analysis Services at Microsoft, working primarily on the data mining platform.

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Data Mining With Microsoft SQL Server 2008 1 out of 5 based on 0 ratings. 1 reviews.
Anonymous More than 1 year ago
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