Data Mining with Microsoft SQL Server 2008
eBook - ePub

Data Mining with Microsoft SQL Server 2008

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Data Mining with Microsoft SQL Server 2008

Book details
Table of contents
Citations

About This Book

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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Yes, you can access Data Mining with Microsoft SQL Server 2008 by Jamie MacLennan, ZhaoHui Tang, Bogdan Crivat in PDF and/or ePUB format, as well as other popular books in Computer Science & Databases. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2011
ISBN
9781118080009
Edition
1
Topic
Computer Science
Subtopic
Databases
Index
Computer Science

Table of contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Dedication
  5. About the Authors
  6. Credits
  7. Acknowledgments
  8. Foreword
  9. Introduction
  10. Chapter 1: Introduction to Data Mining in SQL Server 2008
  11. Chapter 2: Applied Data Mining Using Microsoft Excel 2007
  12. Chapter 3: Data Mining Concepts and DMX
  13. Chapter 4: Using SQL Server Data Mining
  14. Chapter 5: Implementing a Data Mining Process Using Office 2007
  15. Chapter 6: Microsoft NaĂŻve Bayes
  16. Chapter 7: Microsoft Decision Trees Algorithm
  17. Chapter 8: Microsoft Time Series Algorithm
  18. Chapter 9: Microsoft Clustering
  19. Chapter 10: Microsoft Sequence Clustering
  20. Chapter 11: Microsoft Association Rules
  21. Chapter 12: Microsoft Neural Network and Logistic Regression
  22. Chapter 13: Mining OLAP Cubes
  23. Chapter 14: Data Mining with SQL Server Integration Services
  24. Chapter 15: SQL Server Data Mining Architecture
  25. Chapter 16: Programming SQL Server Data Mining
  26. Chapter 17: Extending SQL Server Data Mining
  27. Chapter 18: Implementing a Web Cross-Selling Application
  28. Chapter 19: Conclusion and Additional Resources
  29. Appendix A: Data Sets
  30. Appendix B: Supported Functions
  31. Index