• November 1, 2014

As Data Proliferate, So Do Data-Related Graduate Programs

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Roger W. Winstead, North Carolina State U.

Despite the recession, students at North Carolina State U.'s Institute for Advanced Analytics have been courted repeatedly by employers.

One hundred and fifty applicants for 30 spots. That was the target as business-school administrators at the University of Texas at Austin laid the groundwork for a new master’s-degree program in business analytics. This past fall, they welcomed the inaugural class: 52 students selected from more than 400 applicants. The average GMAT score was 710, highest of any graduate program at the business school. One-year revenue from the self-funded program is projected to total about $1.7-million.

That strong start is a direct reflection of the “mad dash for talent” among employers trying to extract value from rapidly accumulating troves of data, says Prabhudev Konana, chair of the business school’s department of information, risk, and operations management, which offers the new degree. Students are drawn by the job opportunities and good salaries that big-data degrees can deliver, he says.

It’s not just Texas that is rushing to accommodate the queue of applicants. As data generated by social-media sites and mobile devices proliferate, so, too, do degree and certificate programs designed to train data professionals. The programs represent a blending of disciplines including applied mathematics, statistics, and computer science. Programs are being planted in informatics schools, engineering schools, and cross-disciplinary research centers. Some of them see the possibility of substantial revenues.

Requirements, curricula, and technical expertise among the programs vary widely. And while many are newer than the latest iPhone, there are older programs that have been given fresh coats of paint—new titles and new branding meant to harness intense interest across private industry and government.

“It is totally out of control,” says Jeffrey Camm, head of the department of operations, business analytics, and information systems at the University of Cincinnati, which updated and renamed its decades-old program three years ago. “They are popping up every day,” he says. “There is so much demand that universities are responding. I think there are a lot of variances in the programs, though.”

In June 2012, the Graduate Management Admission Council added a data-analytics section to the GMAT exam, used by most business schools in the admissions process. In 2013, 16 business schools registered new master’s programs in data analytics to receive GMAT scores, bringing the total number of data-analytics and information-management programs at business schools to about 166, says Tracey Briggs, a spokeswoman for the council.

The need for skilled data professionals is real and growing, say the programs’ administrators and faculty members. They cite a 2011 study published by the McKinsey Global Institute that said the United States could face a shortage of as many as 190,000 workers with “deep analytical skills” by 2018.

The study also predicted a work-force gap of 1.5 million managers and analysts with the skills to decipher and translate data patterns for decision-making. Program administrators point to the swell in data-related job postings on technology-focused websites such as Dice.com, and to conversations with recruiters hunting for suitable candidates.

“I think a lot of companies were experimenting with this to begin with,” says Michael Goul, chair of the information-systems department in the business school at Arizona State University, which unveiled a master’s program in business analytics this past fall. “Then it started to get to where if you weren’t in the game, especially during the recession, you were getting your cake eaten by your competitors.”

Last month the School of Information at the University of California at Berkeley started what officials there say is the first all-online master’s degree in information and data science. Its mission, in part, is to produce graduates with an awareness of the social and policy implications of data, says AnnaLee Saxenian, dean of the school. Instruction is being conducted via an online platform designed by the education-technology company 2U Inc.

“We wanted to create our curriculum from the ground up, and we wanted to make it cross-disciplinary in the way that schools of information can,” says Ms. Saxenian.

‘Here to Stay’

One important aspect of working with data is the potential to apply findings to high-impact problems in fields like health care, says Rob Fergus, an assistant professor of computer science at New York University who is helping to oversee a new graduate-level data-science program there.

“Any buzzword-type thing, you always feel like the bubble will pop and then people will be like, ‘Oh, big data, that was the ridiculously overhyped concept back 10 years ago,’” Mr. Fergus says. “I think the fluffy stuff will pop, but the underlying rigorous stuff is here to stay. It really works, and it is used by real companies to make money.”

Established programs are seeing their share of the action. When Kennesaw State University started its master’s program in applied statistics, in 2006, it attracted fewer than 20 students and was an “island of misfit toys,” says Jennifer Lewis Priestley, an associate professor of applied statistics. Today she and her colleagues receive as many as five applications for every slot. The program has a 100-percent job-placement rate, with salaries starting around $75,000, she says.

Michael Rappa, who founded the Institute for Advanced Analytics at North Carolina State University in 2007, says the institute has had visitors from more than 50 colleges and government agencies who came to take notes on the master’s degree in analytics.

“You are in a frenzy period—in the last 12 to 24 months you are just seeing dozens and dozens of programs,” Mr. Rappa says. “What we did, and what I wish universities did more, is start with a clean white board. Use the opportunity to be inventive. Don’t try and reconfigure what it is that you have and make it fit a new set of labels.”

In 2012 the university approved the doubling of the program, to about 80 students.

“We have admitted seven classes now,” Mr. Rappa says. “Each year when I thought, ‘This is really intense,’ the next year it was even more so. Through the recession, when graduates were coming out of college looking at unemployment, our students were being courted left and right with multiple job offers.” Some big-data programs are proving lucrative for their institutions as well. Of the $1.7-million in revenue that the analytics degree at Texas is expected to generate this year, some $600,000 will be profit, to be used by the university and the program for a variety of purposes, says Mr. Konana, the department chair. He expects the program to grow.

Mr. Camm, at Cincinnati, says an uptick in enrollment in his program from 2012 to 2013 generated about $1-million in additional revenue, enough to hire four new faculty members.

“I think these programs are very profitable for universities,” Mr. Camm says. “That is the other reason they are doing it.”

It isn’t just new graduates with good job prospects. The proliferation of data programs creates more competition for top faculty members, too, according to some in hiring positions.

“That is a whole other market. It is extremely competitive right now. To hire a senior faculty member is an expensive ordeal,” Mr. Camm says. “Everybody is scrambling.”

Starting salaries for his new hires reached $135,000, up from $110,000 to $120,000 a few years ago, he estimates.

What’s difficult is securing senior scholars capable of working across disciplines and departments to knit together a coherent curriculum, says Mr. Rappa, of North Carolina State.

“Faculty who possess this kind of talent,” he says, “now find themselves in the envious and humbling position of being the frequent target of university recruiting committees.”

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