Higher Education’s Big (Data) Bang: Part One


“We’re really at this stage in the last two years, where more data has been produced than ever before in human history,” Spohrer said. “It has become a new natural resource. An amazing natural resource.”

Spohrer and IBM, of course, would be the spin doctors Reed referred to in his keynote speech. IBM now has more than 1,000 university partnerships related to Big Data, including with Georgetown University, Northwestern University, and the University of Missouri.

In January, IBM donated their supercomputer called Watson, which famously beat long-standing champs on the game show Jeopardy in 2011, to Rensselaer Polytechnic Institute. Watson has 15 terabytes of memory and can read 200 million pages of text in three seconds.

With Big Data being comprised of so much information, it takes that kind of computing power to analyze and make sense of it all.

Indiana University’s Big Red II, one of the 50 fastest University-owned supercomputers in the world, can crunch a quadrillion pieces of data every second. In order for a human being to perform the same level of calculations, it would require the person to complete a calculation every second of every day for 31 million years.

The purpose of the Big Data that’s processed by these enormous and costly machines varies, but a primary one is helping universities continue their role as society’s go-to source of research and knowledge.

“With the ability to process huge amounts of data at an almost unimaginable speed, they have become an essential tool in expanding the frontiers of knowledge, addressing the world’s most critical issues and probing the most fundamental questions about the universe in which we live,” Michael McRobbie, IU’s president and former CIO, said when the computer was unveiled.

Universities also use Big Data technology to analyze their own student and faculty information — things like learning trends, financial aid statistics, and teaching costs.

At Wichita State University, for example, this kind of data is used to predict which students will succeed at the college before they are ever admitted.

Harper would call this “medium data,” but it is the kind of rapidly growing amount of information that learning analytics companies like Civitas Learning argue is also “Big Data.”

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