This fall George Mason University will become one of only five universities in the country to offer a data analytics engineering master's degree program, a course of study created to meet a burgeoning demand for professionals who can extract insight from the flood of "big data" collected at a higher rate than it is comprehended.
As part of the graduate program, the university's Volgenau School of Engineering will offer concentrations in applied analytics, data mining, digital forensics, predictive analytics and statistics for analytics — or a combination of two or more concentrations — and conclude with a data analytics capstone course. Just about every Volgenau department is represented in the program, enabling students to approach the degree from any number of avenues.
Most data analytics programs are based in schools of management, not engineering schools. Mason will be the only university on the East Coast north of Raleigh, N.C., to offer a data analytics engineering master's program. No university as far west as Chicago has one.
The Harvard Business Review calls data science "the sexiest job in the 21st century." The New York Times calls data scientists "the magicians of the Big Data era." Mason students will be at the forefront of what some experts are calling "the measurement revolution."
"We tried from an education point of view to cover all of the fundamentals, and we think in doing so we've created an approach that is absolutely unique," says Robert Quinn, founding director of Mason's master's in applied information technology program. "You can't do anything in big data unless you understand the impact of the scope of the data, the scale of the data and the shortness of time to process it. Time, scale and scope mean everything. If you drill down, there's a good reason for calling it data analytics engineering."
"The focus here will be graduating people who can go in and technically solve problems versus managing people who can technically solve problems," says Robert Osgood, director of the master's program in computer forensics and electrical and computer engineering and program director for the data analytics program.
In the past few years, corporations and government agencies have been clamoring for graduates who can offer the kind of expertise that students in the 10-course, 30-credit master's program will be able to provide. The State Council of Higher Education for Virginia approved the program last fall, and the first students will enroll in fall 2014. Mason previously offered a graduate certificate in data analytics.
Stephen Nash, senior associate dean in the Volgenau School and the driving administrative force behind the new program, says that not only will Mason graduate skilled engineers to help fill the surplus of data analytics jobs, companies will seek to enroll their current employees to afford them a more well-rounded grasp of the field.
A McKinsey Global Institute study projects that by 2018 there might be a 50- to 60-percent gap between "deep analytic talent" supply and demand.
"Companies are desperate because data analytics is so critical to being competitive that they want to be able to apply the data they have and be more nimble and have more foresight," Nash says. "They need these people right now. It's hard to get them because it requires training in a lot of areas. It's four or five different degrees you'd have to pull together."
The goal of data analytics is to make sense of massive amounts of data, culled from every aspect of our lives — from shopping habits (think Netflix suggesting a movie you might like) to health statistics to crime trends to weather patterns to any number of applications — and to draw inferences or conclusions from that data to boost efficiency, production or profitability.
It's more about discovery than confirmation. It's about crunching numbers, but more important, it's about digesting them.
"People think that data analytics is some inhuman process," Osgood says. "It's not. It's all about us as human beings taking advantage of what we know and leveraging that information so we can get the most out of ourselves."
Capturing data is not enough. It must be sifted through and interpreted and its hiding-in-plain-sight secrets revealed. Nash compares it to working a jigsaw puzzle without knowing the picture: All of the pieces are in front of you, but can you quickly find what you need and make the crucial connections?
Starting this fall, Mason engineering students will be prepared more than ever to do that.
"In a big data environment, if you think about a bulldozer going through the city dump, everybody is worried about what's in front of the blade," Quinn says. "What is of equal importance is the stuff beside the blade that you pushed aside. It didn't look like it belonged, but you haven't dug deeply enough. It could be what you're looking for, you just don't know enough about it yet.
"You have the potential to know everything about every little piece that's in the pile."
For more information about Mason's data analytics engineering master's program, contact Robert Osgood at rosgood@gmu.edu.
A version of this story appeared on Mason's Newsdesk January 22, 2014.
Write to Preston Williams at pwilli20@gmu.edu