Professional Microsoft® SQL Server® Analysis Services 2008 with MDX

16.1. The Data Mining Process

Wherever you look, people and businesses are collecting data, in some cases without even an obvious immediate purpose. Companies collect data for many reasons, including accounting, reporting, and marketing. Those companies with swelling data stores have executives with many more questions than answers; in this book you have seen how executives can use UDM-based analysis to find the answers they need. This is typically a process in which you know what you are looking for and can extract that information from your UDM. However, there might be additional information in your data that can help you make important business decisions that you are not aware of because you don't know what to look for. Data mining is the process of extracting interesting information from your data such as trends, clusters, and other patterns that can help you understand your data better. Data mining is accomplished through the use of statistical methods, as well as machine learning algorithms. The ultimate purpose of data mining is the discovery of subtle relationships between data items. It can also entail the creation of predictive models. When data mining is successfully applied, rules and patterns previously unknown and potentially useful emerge from heaps of data.

You don't need a vintage coal-mining helmet with a lamp to begin the data mining process (but if you feel more comfortable wearing one, you can likely find one on eBay). What really is required is a problem ...