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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The most authoritative book on data mining with SQL Server 2008
SQL Server Data Mining has become the most widely deployed data mining server in the industry. Business users—and even academic and scientific users—have adopted SQL Server data mining because of its scalability, availability, extensive functionality, and ease of use.
The 2008 release of SQL Server brings exciting new advances in data mining. This authoritative and up-to-date resource shows how to master all of the latest features, with practical guidance on how to deploy and use SQL Server data mining for yourself.
The author team begins with an introduction to the tools, techniques, and concepts necessary to leverage SQL Server 2008 data mining. The discussion progresses to a thorough look at the details of the SQL Server 2008 data mining algorithms. You'll discover how to integrate SQL Server data mining into other parts of the SQL Server Business Intelligence (BI) suite and extend SQL Server data mining for your own needs. Detailed, practical examples clearly explain how to implement successful data mining solutions with SQL Server 2008.
Data Mining with Microsoft SQL Server 2008 shows you how to:
Apply data mining solutions using Microsoft Excel
Use the data mining Add-ins for Microsoft Office
Understand how, when, and where to apply the algorithms that are included with SQL Server data mining
Perform data mining on online analytical processing (OLAP) cubes
Extend SQL Server data mining by implementing your own data mining algorithms and stored procedures
Use SQL Server Management Studio to access and secure data mining objects
Use SQL Server Business Intelligence Development Studio to create and manage data mining projects
The companion website includes the complete sample code and data sets that are featured in the book.
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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