DALLAS (SMU) – Before spending a week at an SMU/IBM data analytics camp, high school senior Suhas Tatapudi had no idea how much he would enjoy crunching the numbers in large data sets.
“I was mainly interested in medicine,” he said. Tatapudi was one of 20 students from DISD’s Townview Magnet Center chosen by their teachers to participate in an interactive four-day program, the IBM Summer Innovation Camp on Predictive Analytics, co-sponsored by the Richard B. Johnson Center for Economic Studies in SMU’s Dedman College.
A hybrid field, predictive analytics combines statistics, economics, mathematics and business techniques to analyze the large amounts of data analysts call “big data.” This data can include amount of traffic on company websites or frequency of repeat customers. Businesses then use the analyses to explore trends or probabilities and in turn make wise business decisions.
In a 2011 report by international consulting firm McKinsey and Company, researchers found that retailers making decisions based on big data could increase their operating profit margins by 60 percent. McKinsey’s research also predicted a shortage of 190,000 qualified data analysts by 2018.
“The work of skilled data and economics analysts can help create smarter government operations and enable businesses and individuals to make wiser decisions,” said Tom Fomby, professor of economics and director of the Richard B. Johnson Center for Economics in SMU’s Dedman College.