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Free ebooks
 Free database ebooks SQL Data Mining with SQL Server 2005
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 1 - Introduction to Data Mining - Data mining is a key member in the Business Intelligence (BI) product family, together with Online Analytical Processing (OLAP), enterprise reporting and ETL.2 - OLE DB for Data Mining - In this chapter, you take a closer look at the OLE DB for Data Mining specification, an industry standard initialized by Microsoft and supported by a number of data mining vendors. 3 - Using SQL Server Data Mining - This chapter will review the Analysis Services toolset and provide techniques to effectively create and analyze mining models. 4 - Microsoft Naive Bayes - The Naive Bayes algorithm enables you to quickly create models that provide predictive abilities and also provide a new method of exploring and understanding your data. 5 - Microsoft Decision Trees - In this section, we will have a closer look at the principles of the Microsoft Decision Trees algorithm. 6 - Microsoft Time Series 7 - Microsoft Clustering 8 - Microsoft Sequence Clustering - In this chapter, you will learn how to analyze navigation sequences and organize sequences into natural groups based on their similarities, using the Microsoft Sequence Clustering algorithm. 9 - Microsoft Association Rules - The process of finding these patterns, called market basket analysis, is accomplished using the Microsoft Association Rules algorithm, described in this chapter. 10 - Microsoft Neural Network 11 - Mining OLAP Cubes 12 - Data Mining with SQL Server Integration Services - In this chapter, we will first give you an introduction to SSIS. We will then teach you how to perform data mining tasks in SSIS environment. 13 - SQL Server Data Mining Architecture - This chapter discusses, in some detail, the architecture of Analysis Services and, in particular, the data mining side of things. 14 - Programming SQL Server Data Mining - In this chapter, you review programming interfaces and object models that make it easy to write data mining applications using Analysis Services. 15 - Implementing a Web Cross-Selling Application - In this chapter, we will help you to solve this business problem using data mining techniques. 16 - Advanced Forecasting Using Microsoft Excel - In this chapter, we explain how that works by implementing an advanced forecasting tool for Excel. 17 - Extending SQL Server Data Mining - This chapter will briefly describe the potential and mechanisms developing plug-in algorithms and viewers. Download free ebooks on sql:Data Mining with SQL Server 2005
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