In this chapter you learned about data mining, what it is used for, and what is specific algorithms are available for use in Analysis Services 2005. The most important answer is to the question, "How does it help your business?" If you are now a step or two closer to that answer, you're doing great.
After learning the data mining algorithms in Analysis Services 2005, you drilled down on two, going step-by-step developing Microsoft Decision Trees and Microsoft Clustering Models using data from a relational data source. You also learned about OLAP mining models, where you essentially built a model on top of a cube. With the OLAP mining model you segmented the customers based on Internet Sales, and you were able to utilize the results of that mining model within a cube.
Aside from those off-the-shelf algorithms, Analysis Services 2005 provides a way to plug in your own data mining algorithm and/or data visualization capability (viewer). For details on this, please refer to the SQL Server 2005 product documentation. In a nutshell, you implement certain interfaces so that the server can utilize the results coming out of the algorithm you created. Once you have implemented your algorithm you can expose your data mining algorithm using the server properties. For an in-depth understanding of Data Mining in Analysis Services 2005, please refer to Data Mining with SQL Server 2005 by Jamie MacLenan and ZhaoHui Tang (Wiley, 2005).
In the next chapter you will learn to analyze cube data from client tools other than the ones provided within the Analysis Services 2005. Microsoft Office products are tightly integrated with Analysis Services so you can analyze data from cubes. Microsoft Office products like Microsoft Excel, Microsoft Office web components, and Microsoft Data Analyzer all have the ability to retrieve and present data from Analysis Services in a way that is easy to interpret by users.