In this article, we review two, intertwined tools in the data mining arsenal: correlation and scatter plots.  These tools are fundamental for gauging the relationship (if any) between pairs of data elements (say, the age and income of your customers).  As we’ll soon see, there are good, bad, and ugly things that can happen when we apply a purely computational method like correlation.  My goal is to help you avoid the usual pitfalls, so  you can use correlation and scatter plots effectively in your own work.     Read the article

In the data mining process, where do data scientists like you and me add the most value?  Is it in exploring the data, uncovering anomalies and seeing relationships between elements?  In selecting transformations for the elements to improve their representations for modeling and analysis?  In building sophisticated predictive models?  For my money, the answer is ‘none of the above’.  I believe we contribute the greatest value by framing the problem.  We can do stellar technical work – but if the problem is framed poorly, it’s all a pointless exercise, maybe even solving the wrong problem.  Conversely, even a mediocre model, applied to the right, well-framed problem, will provide immediate benefit to an organization.    Read the article

-- Registering early for such conferences gets you a good discount on the price.  Discovery Corps also has a code [DCIAMX11] you can use during the registration process for another deal.  Hope to see you there!

Judging by the recent posts on numerous web sites, many companies are looking for people with data mining and modeling (DM) skills.  I recently interviewed some candidates for an open position.  Since people in this field are a unique group, and interviewing them can be challenging, I thought you might like to hear about my approach.  When I interview a DM candidate, let’s call her Janet, I want to find out ....

To read the full article from DCI president Tim Graettinger, see our Articles page or go here.