There is a danger here, the easy use of GUI tools on large amount of data available is tempting and which makes users tempt to use black box methodologies available in the tools to solve their business problems. They mistakingly assume data mining is all about using a tool and running the data on the tool, this can be very hazardous and dangerous as actions are taken on business decisions.

Little knowledge is dangerous while applying powerful models.

Since the underlying logic used for model building in automated tools are unknown (their internal assumptions are unclear). Therefore it is very easy to do it in the wrong way assuming it is the right solution. Such mistakes are still made in companies.

People sometimes might argue that there is always a simpler solution to problems. I am the person who belives in Occam’s Razor, which means simplest explanation is always the best way. This means the interpretation of the model and the final solution should be as simple as possible. However,  method of arriving at solution must be as detail as possible taking every factor, element into consideration. Analysts must not make the mistake of over simplyfying the method and make too many assumptions.

A lot of knowledge workers believe that predictive modeling process can be automated by using tools and statistical software. These software are certainly useful but cannot replace the intellectual  of the analyst.

The processof building the model must be as detailed as possible, it has to tried & tested on various data and measured by various parameters. All possible factors must be considered while building the model.

Therefore Analyst must understand the underlying algorithm , process of arriving score, model design etc.

More on such articles regarding online marketing, data mining, data modeling can be found at http://www.praveenkodur.com/blog