When it comes to scientific circles, data science may be a new kid on the block, but it’s rapidly become everyone’s best friend. A highly interdisciplinary field that blends statistics, computing, algorithms, applied mathematics, and visualization, data science uses automated methods to gather and extract knowledge from very large or complex sets of data. “Data science is difficult to explain because any way you define it, you’re usually excluding something that is critically important,” said Dana Randall, a professor in Georgia Tech’s School of Computer Science.

Granted, people have been collecting and crunching numbers for a long time, but over the past decade several things have changed, noted Charles Isbell, senior associate dean and a professor in Georgia Tech’s College of Computing. “A lot of data became ubiquitous, algorithmic sophistication has increased dramatically, we can construct complicated models to predict things — and we have the machinery to make it happen. Put all this together, and data science suddenly matters.”

Indeed, instead of being relegated to some niche fields, “data science is becoming pervasive,” agreed Steve McLaughlin, chair of Georgia Tech’s School of Electrical and Computer Engineering (ECE). “There are very few fields in sciences, engineering, humanities, or business that aren’t being drastically impacted by data.”

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