SQL Server™ 2005 Bible

Chapter 44. Data Mining with Analysis Services

In This Chapter

• Overview of the data mining process

• Creating mining structures and models

• Evaluating model accuracy

• Deploying data mining functionality in applications

• Mining algorithms and viewers

• Mining integration with OLAP

Many business questions can be answered directly by querying a database, such as "What is the most popular page on our website?" or "Who are our top customers?" Other, often more important, questions require deeper exploration—for example, the most popular paths through the website or common characteristics of top customers. Data mining provides the tools to answer such non-obvious questions.

The term "data mining" has experienced a great deal of misuse. One of my favorite anecdotes is about a marketing person who intended to "mine" data in a spreadsheet by staring at it until inspiration struck. In this book, data mining is not something performed by intuition, direct query, or simple statistics. Instead, it is the algorithmic discovery of non-obvious information from large quantities of data.

Analysis Services implements algorithms to extract information addressing several categories of questions:

• Segmentation: Groups items with similar characteristics. For example, develop profiles of top customers or spot suspect values on a data entry page.

• Classification: Places items into categories. For example, determine which customers will respond to a marketing campaign or which e-mails are likely spam.

• Association: Sometimes ...