How can a car-sharing company figure out the best spots to park vehicles, or an electric utility forecast the demand for power? The solution today often involves crunching terabytes, and sometimes petabytes, of data. Whether retail, telecom, or health care, businesses in almost every sector are hoping to innovate and increase profits by analyzing immense data sets.
Obtaining data is easy; it can come from a huge variety of automated sources, including RFID tags, mouse clicks, or sales receipts. And the analytic software systems — such as SAS Institute’s eponymous SAS and IBM’s SPSS — that are required to work with this data are getting better, says Michael Hasler, director of a new M.S. in Business Analytics program at the University of Texas at Austin. But what’s missing are the people: “You need to take these large unstructured data sets, clean them up, and find insights, but there’s a shortage of talent to do that work,” says Hasler.
By 2018, the United States is projected to face a shortfall of as many as 190 000 experts who can make sense of big data, according to the McKinsey Global Institute. Universities are now trying to fill the gap with advanced degree programs that aim to produce graduates who can provide useful information and communicate it to business leaders and clients.