Everybody is buzzing about predictive models, and for good reason – they are sexy! Here’s some advice for people just starting out or interested in predictive models. One size does not fit all – don’t try to force it! Define a goal – why are you building this model? Play, play, and play some more

This past week I’ve had a chance to attend EMC Education Services new class titled  “Data Science and Big Data Analytics.”  The course provides a hands-on practitioner’s approach to the techniques and tools required for Big Data Analytics.  My primary interest in the course was to see if it was really possible to transition an

I couldn’t really think of the right thing to call this entry, and the following titles popped to my mind: Model Scores drive revenue from Big Data Data Monetization revenue Models Model ROI from Big Data, Cloud Data and Everything In-Between Common sense:  big data is a corporate asset.    If your company gives the asset

In my blogs entries, I tend to mention FACTS.   A fact is something that I have actually accomplished. At times, people think that I am being theoretical; however, I tend to tell people when I am being theoretical and when it is something that I have actually accomplished. For example, here are a few “Zimm Facts”:

Big Data Monetization is the thing that every company is looking to do, is doing, or eventually will do. If you haven’t done it yet, you will. If you haven’t explored the possibilities, you will.  If you are still questioning the value of Data Monetization, you should have clicked on the link you just skimmed over. First