Data Mining With Microsoft Sql Server 2008

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Data Mining with SQL Server 2008 shows database analysts, data miners, and developers how to use all of the new features of Microsoft SQL Server 2008 for data mining. The book begins with a quick overview of the SQL Server Data Mining Toolset, showing how these tools can be integrated with Office 2007 to provide a complete, user-friendly platform for mining and analyzing data. The authors next show how to use each of the major data mining algorithms supported by this Microsoft tool, including naive bayes, decision trees, time series, clustering, association rules, and neural networks. The authors also cover mining OLAP databases, as well as data mining with SQL Server Integration Services 2008. The last set of chapters provides in-depth examples of using Microsoft data mining to solve business analysis problems, including building a cross-sales Web application. The authors also cover significant new features for text mining. The companion Website will include the complete sample code and data sets provided in the book.

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Jamie MacLennan is the Principal Development Manager of SQL Server Analysis Services at Microsoft. In addition to being responsible for the development and delivery of the Data Mining and OLAP technologies for SQL Server, he is a proud husband and father of four. Jamie has more than 25 patents and patents pending for his work on SQL Server Data Mining. Jamie has written extensively on the data mining technology in SQL Server, including many articles in MSDN magazine, SQL Server magazine and postings on SQLServerDataMining.com and his blog at http://blogs.msdn.com/jamiemac . This is his second edition of Data Mining with SQL Server. Jamie has been a featured and invited speaker at conferences worldwide, including Microsoft TechEd, Microsoft TechEd Europe, SQL PASS, Knowledge Discovery and Data Mining (KDD) conference, the Americas Conference on Information Systems (AMCIS), and the Data Mining Cup conference. ZhaoHui Tang is a group program manager at Microsoft adCenter Labs, where he manages a number of research projects related to paid search and content ads. He is the inventor of Microsoft Keyword Services Platform. Prior to adCenter, he spent 6 years as a lead program manager in SQL Server Business Intelligence group, mainly focusing on data mining development. He has numerous publications in both academic and industrial journals such as VLDB and SQL Server Magazine. He is a frequent speaker in database and business intelligence conferences. He is a co-author of the book Data Mining with SQL Server 2005. Bogdan Crivat is a Senior Software Design Engineer in SQL Server Analysis Services at Microsoft, working primarily on the Data Mining platform. Bogdan has written various articles on data mining for MSDN, Access/VB/SQL Advisor as well as numerous postings on the SQLServerDataMIning.com web site and on the MSDN Forums. He presented at various Microsoft and data mining professional conferences. Bogdan also blogs about SQL Server data Mining at www.bogdancrivat.net/dm Table of Contents Introduction to Data Mining Applied Data Mining Using Microsoft Excel 2007 DMX and SQL Server Data Mining Concepts Using SQL Server Data Mining Implementing a Data Mining Process Using Office 2007 Microsoft Nave Bayes Microsoft Decision Trees Algorithm Microsoft Time Series Algorithm Microsoft Clustering Microsoft Sequence Clustering Microsoft Association Rules Microsoft Neural Network and Logistic Regression Mining OLAP Cubes Data Mining with SQL Server Integration Services SQL Server Data Mining Architecture Programming SQL Server Data Mining Extending SQL Server Data Mining Implementing a Web Cross-Selling Application Conclusion and Additional Resources Appendix A. Datasets Appendix B. Supported Functions Index