Big Data Education Hinges On Business, University Partnerships

Academics and companies must join forces to prepare college students for three types of data analytics jobs, says Georgetown professor.

Jeff Bertolucci, Contributor

September 3, 2013

4 Min Read
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Hey, college grad, ever heard of Hadoop? Know anything about statistics? In the coming years, big data skills might help you land a good job.

Data analysis is expected to play a greater role in day-to-day business operations, a development that will require many university graduates to attain at least a basic understanding of big data tools and technologies.

The U.S. Department of Labor predicts a 25% percent growth in the need for analytics-trained workers through 2018. And research firm Gartner estimates that more than 4.4 million big data-related jobs will be created by 2015, but only a third of those will be filled.

Of course, one can quibble with the accuracy or timeline of these projections. But there's no denying the fact that volume, variety and velocity of data -- big and small -- continue to grow, and that organizations increasingly need employees with some degree of data-analysis skills.

[ Do the three V's -- volume, variety and velocity -- really help you understand big data? See Big Data: A Practical Definition. ]

A partnership between academia and business can help accomplish that, according to Georgetown University professor Betsy Page Sigman.

"It's important for universities to partner with companies so that they can stay cutting-edge," Sigman said in a phone interview with InformationWeek. "It's important that (schools) find companies they can have a relationship with so that they can expose their students to new technologies that are out there."

This process is already underway, of course, but in its early stages.

A number of tech companies, particularly those with a vested interest in big data products and services, have been aggressively promoting stronger cooperation between higher education and business in data-related fields.

IBM, for instance, announced last month it's expanding its Academic Initiative by adding nine new educational collaborations to its more than 1,000 partnerships with universities around the world. The tech giant is launching new curricula focusing on big data and analytics at several universities, including Georgetown.

Similarly, database software company Teradata has an online certification training program for students seeking a career in data-focused professions.

That's a good start, but more work is needed. "Educational institutions need to have more of a focus on data," said Sigman, who teaches at Georgetown's McDonough School of Business. Specifically, educators must "get students to understand how to deal with data ... and understand what statistics mean."

In the near future, multiple job categories will likely require some degree of big data know-how.

Sigman points to a recent report from the McKinsey Global Institute, which uses data from the U.S. Bureau of Labor Statistics to divide big data talent into three job categories, which Sigman calls Deep Analytical, Big Data Savvy and Supporting Technology.

Deep Analytical, as its name suggests, includes professions that require extensive knowledge of advanced technology and science, such as database administrators and programmers, mathematicians and operations research engineers. Big Data Savvy consists of business vocations that are more mainstream, including financial analysts, life scientists and survey researchers. The third group, Supporting Technology, consists mostly of software engineers and programmers, computer scientists and system analysts.

Business school graduates fall mostly in the middle category, noted Sigman.

"I want to give our students the big data savvy," she said. "They're not going to do the supporting technologies, for the most part, but some of them will. A lot of them will become business and financial managers or market research analysts ... and some will do operations work in a factory with a lot of data."

Although this growing democratization of big data analytics will help bring data-mining skills to the masses, Sigman said that highly trained data scientists will still be in demand.

"We're still going to need people who understand what's actually being done," she said. "We'll need to have people who really understand statistics."

Making decisions based on flashy macro trends while ignoring "little data" fundamentals is a recipe for failure. Also in the new, all-digital Blinded By Big Data issue of InformationWeek: How Coke Bottling's CIO manages mobile strategy. (Free registration required.)

About the Author

Jeff Bertolucci

Contributor

Jeff Bertolucci is a technology journalist in Los Angeles who writes mostly for Kiplinger's Personal Finance, The Saturday Evening Post, and InformationWeek.

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