Big Data Professors Want Your Data Sets

Access to large, relevant data sets is the biggest problem facing business intelligence and data analytics instructors and students, new survey finds.
 Big Data Analytics Masters Degrees: 20 Top Programs
Big Data Analytics Masters Degrees: 20 Top Programs
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Pssst. Hey, got a few petabytes of data to spare? Your local university just might need it.

The biggest challenge in training the next generation of data scientists is finding large data to teach students real-world skills. That's a key finding of the latest State of Business Intelligence survey conducted for Teradata University Network, a Web-based training program for students seeking careers in data-oriented professions.

The survey, the third State of Business Intelligence study since 2009, polled professors at 243 universities in 43 countries, as well as students at 96 universities. It was conducted by a trio of academics, including Xavier University associate professor Thalini Ariyachandra, who discussed the survey results via telephone with InformationWeek. Bill Franks, chief analytics officer for Teradata's global alliance programs, joined in the call.

Although the world is awash in big data, 45% of professors say the top challenge to teaching BI and data analytics is gaining access to large data sets, the survey found. The second biggest challenge is finding students with prerequisite skills (39%); third is finding qualified or available instructors (37%).

[ Want to know about other concerns with big data in schools? Read Big Data's Opportunities, Responsibilities For Education. ]

Well, if there's so much data out there, why can't universities use it?

"We want the kind of data sets that exist in companies, so we can give students some practical, real-world experience," said Ariyachandra. "And getting access to that kind of (data) is still something that is challenging."

"Universities have some samples of data, but it's a challenge to locate pools of large data that you can get access to," added Franks. "A lot of companies are hesitant to give that data out, and it can take quite a bit of effort to anonymize it if you do."

The problem, while significant, isn't exactly new, however.

"I'm an analytics professional by training. I have a master's degree in statistics. In school -- this was years ago, so none of the data was as big as it is now -- the data you used for exercises was very small and artificially clean," Franks recalled.

The study also shows that more students are focusing on business-oriented analytics professions, such as business analyst or IT professional. However, only 16% of students surveyed are considering careers as data scientists.

On the plus side, more schools are adding data science to marketing and statistics courses.

"More academics are providing depth in the kind of statistics and advanced predictive analytics type of skills being offered in courses," said Ariyachandra. "There are more programs in place than two years ago, and there's definitely a lot going on, with academia trying to meet demand for (data scientists)."

For instance, businesses are looking for graduates with practical, hands-on experience with big data sets. Said Ariyachandra: "For academics, the problem is, how do we provide that?"

According to a 2011 study by the McKinsey Global Institute, the U.S. could face a shortage of up to 190,000 data scientists by 2018.

This shortage is part of a larger trend: the dramatic increase in the use of analytics in business, Franks noted.

"Some are calling their programs 'predictive analytics,' some are calling them 'data science,' some are calling them 'data mining,'" he said. "But at the end of the day, all the programs are oriented toward the same general principle: we need people who can go out in industry and help (organizations) analyze their data."

Introductory information systems courses at business colleges are now incorporating analytics, as well as providing a fundamental understanding of BI, added Ariyachandra.

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