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.
Eine praxisorientierte Einführung in das Data Mining Toolset des SQL Server 2008 und die neuen Data Mining Add-Ins für Office 2007.
Enthält detaillierte Erläuterungen und Beispiele zu allen neuen Data Mining Features des SQL Server 2008.
Gibt präzise Anleitungen zum Arbeiten mit den wichtigsten Data Mining-Algorithmen, (Naive Bayes-, Decision Trees-, Time Series-, Sequence Clustering-, Association- und Neural Network-Algorithmus), zum Data Mining in OLAP Datenbanken und mit SQL Server Integration Services 2008.
Die begleitende Website enthält den kompletten Quellcode zu den Beispielen aus dem Buch.
Produkt-Info
WebSite Associated w/Book
Auflage
Sprache
Verlagsort
Zielgruppe
Produkt-Hinweis
Broschur/Paperback
Klebebindung
Maße
Höhe: 235 mm
Breite: 191 mm
Dicke: 36 mm
Gewicht
ISBN-13
978-0-470-27774-4 (9780470277744)
Schweitzer Klassifikation
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.
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.
