Description

Book Synopsis
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.

Table of Contents
1. Introduction to Data Mining.

2. Applied Data Mining Using Microsoft Excel 2007.

3. DMX and SQL Server Data Mining Concepts.

4. Using SQL Server Data Mining.

5. Implementing a Data Mining Process Using Office 2007.

6. Microsoft Naïve Bayes.

7. Microsoft Decision Trees Algorithm.

8. Microsoft Time Series Algorithm.

9. Microsoft Clustering.

10. Microsoft Sequence Clustering.

11. Microsoft Association Rules.

12. Microsoft Neural Network and Logistic Regression.

13. Mining OLAP Cubes.

14. Data Mining with SQL Server Integration Services.

15. SQL Server Data Mining Architecture.

16. Programming SQL Server Data Mining.

17. Extending SQL Server Data Mining.

18. Implementing a Web Cross-Selling Application.

19. Conclusion and Additional Resources.

Appendix A. Datasets.

Appendix B. Supported Functions.

Index.

Data Mining with Microsoft SQL Server 2008

    Product form

    A Paperback / softback by Jamie MacLennan, ZhaoHui Tang, Bogdan Crivat

    £999.99

    Includes FREE delivery

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      Book details

      Publisher John Wiley & Sons Inc
      Published 7 November 2008
      ISBN-13 9780470277744
      978-0470277744
      ISBN-10 0470277742
      Also in:
      Computer networking and communications Database programming

      Description

      Book Synopsis
      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.

      Table of Contents
      1. Introduction to Data Mining.

      2. Applied Data Mining Using Microsoft Excel 2007.

      3. DMX and SQL Server Data Mining Concepts.

      4. Using SQL Server Data Mining.

      5. Implementing a Data Mining Process Using Office 2007.

      6. Microsoft Naïve Bayes.

      7. Microsoft Decision Trees Algorithm.

      8. Microsoft Time Series Algorithm.

      9. Microsoft Clustering.

      10. Microsoft Sequence Clustering.

      11. Microsoft Association Rules.

      12. Microsoft Neural Network and Logistic Regression.

      13. Mining OLAP Cubes.

      14. Data Mining with SQL Server Integration Services.

      15. SQL Server Data Mining Architecture.

      16. Programming SQL Server Data Mining.

      17. Extending SQL Server Data Mining.

      18. Implementing a Web Cross-Selling Application.

      19. Conclusion and Additional Resources.

      Appendix A. Datasets.

      Appendix B. Supported Functions.

      Index.

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