In the last couple of decades, we saw an ‘information revolution’.  Lately, it has been changing the way we think of data.  We already see the early ramifications of this evolution in the data landscape, in the form of highly personalised web portals and micro-targeted advertising. What does this mean for students? What kind of skill-sets will they be expected to have?  

One of the first things taught in introductory analytics courses is "clustering" – an algorithm that can find applications in, for instance, customer segmentation for a marketing campaign.  On what basis do we decide on the number of customer segments? What customer characteristics, or variables, should we use?  Of course, we can fall back on our domain expertise to make such decisions, however, the data science way is to look for data-driven decisions.
 
In this podcast, Associate Professor Manoj Thulasidas from SMU’s School of Information Systems shares his views on the evolving data landscape, and his recent work in data analytics.