SPSS Data Mining
"Data mining is the process of discovering meaningful new relationships, patterns, and trends by sifting through data using statistical and mathematical techniques." (1)
Data Mining is a somewhat new concept that is built upon the traditional statistical techniques that everyone learned in their college statistics courses. However, data mining uses these techniques in a much more exploratory manner. Data mining is not like statistical analysis where you are trying to disprove the null theorem. Rather, data mining is more akin to sifting through your data to discover those golden nuggets of information that will make your organization more profitable or effective.
Data mining is used to address many different issues, including marketing analysis, fraud detection, epidemiology, operational efficiency, forecasting trends, employee retention, defining customers and customer preferences, locating potential customers, and much more.
If you have an issue that needs to be analyzed, and data that you believe might support the analysis, you are a candidate for data mining. Typically, a data mining project will use the organization's existing data to address the issues at hand.
Statistics By Greg Black, Inc. performs data mining projects based upon the CRISP-DM (Cross Industry Standard Process for Data Mining) standards. Unless you already have an SPSS data warehouse set up and ready to go, the typical first step is to create your data warehouse. This can take up to as much as 80% of the time spent on the project, but is always time well spent. Once data are compiled and ready, we explore the data, validate the results, and report results to the users.
All Services are $100/hour. If you live in Texas, we add a sales tax, which is 8.25% in Austin, Texas.
(1) data mining definition by the Gartner Group.
