Technology: Is Data Mining Misguided?

When I read this article I see the clear confusion regarding the expectations of data mining technologies and how they should interact with statistical methodologies. The purpose of data mining should be to create a classification (think of a list of items going in a particular order 1, 2, 3,4, 5...). This calssification is based on a value that is express as a probability. Once you have a good measurement tool (this is waht data mining should do for you), then you apply statistical techniques (distribution, cluster, cause and effect analysis, correlation) to determine the areas that should "group" together (using relevant discrete and numerical variables, including but not limited to the data mining value obtained). Once you have determine the areas you want to study, then you use the data mining value (and other variables) and statistical methods to make your recommendations. Again, the process is: 1. variables, 2. data mining models, 3. determination of areas of classification, 4. statistical methods, and 5. recommendations.

The change management is to get users of data mining to understand that it is a process and that for it to work you need to invest resources (mostly time and technology).