More data has been generated and collected in the past few years than in all of human history combined. But all this information is only useful if you know how to analyze it.
Here’s just one example: Every time you plug an address into a GPS app on your phone, you are creating data about where you plan to travel and when. These are two small pieces of a huge data set about commuting patterns that businesses can use to better understand driver behavior and potentially offer up desirable products and services along your route or improve your drive itself.
It takes trained data scientists to make sense of such complex information. It’s no wonder that the global demand for analytics gurus—usually part statistician, part computer programmer—has skyrocketed. The median salary for a data scientist is $116,870, and there are thousands of job openings in the U.S. alone, according to a 2016 report by Glassdoor.
Georgia Tech saw this educational demand coming: Two years ago, the Institute launched a one-year interdisciplinary Master of Science in Analytics program. What sets Tech’s program apart from other analytics degrees offered across the country, says its director Joel Sokol, is that it approaches analytics from three different perspectives: business, engineering and computing. In addition, the intense, one-year focus attracts those already working in industry who want to earn a formal, advanced degree in analytics—some of them even able to do so without interrupting their careers.
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