The analytics revolution has arrived, present in everything from business to public health to the weather. Partly driven by the explosion of widely available data, it requires not just technological adaptation but new ways of thinking. Recognizing this, American University considers big data a research area worthy of multidisciplinary investment and included it as part of the AU 2030 project.
Discovering Big Data
The Kogod School of Business is launching a new Master of Science in Analytics program (MSAn), directed by Assistant Professor Frank Armour. He has a background in information technology and computer science, and his interests include enterprise architecture. Armour's more recent focus on analytics stems from a conference he attended featuring Doug Cutting, a co-creator of the open-source software framework Hadoop.
"I had heard about the idea of big data, and when he spoke I was just so fascinated. I got such an intellectual interest in it that I decided to just research it a lot more, and venture into the field," he says. "Then I had an opportunity to teach an undergraduate business analytics course here, so one thing led to another. And now I consider myself an analytics professor."
Analytics is Trending
A 2013 U.S. Chamber of Commerce Foundation report contained a mind-blowing factoid: 90 percent of the world's data at that point had been produced in the previous two years. "We have all of this digital information out there that we didn't have before. Or, we had it, but we weren't able to do anything with it," he says. "And hardware and software advances now allow us to be able to analyze and manipulate this data. Whereas, in years past, we just didn't have the firepower."
Any business can now use this information to create a competitive advantage. He delineates between "decision-based organizations" and "hunch-based organizations." The more companies can learn about their customers, the easier it is to understand the marketplace. And it's not just confined to big data, as analytics can be used by smaller companies with smaller data sets, he says.
"I think what we're seeing is that there's a subset of businesses—for example, Google, Amazon, and Netflix—using this very efficiently to make predictions for better customer service," Armour says. Yet other businesses haven't been as successful in utilizing analytics. "One of the key things that they're struggling with is getting the right people resources. Right now there's just a dearth of people who really, truly know analytics."
The Role of Humans
The human component is vital. It's not just about operating the software, he says. It's about knowing the "analytic life cycle," which includes framing the business problem correctly, identifying and gathering the right data, running the proper analytics model, and effectively analyzing your results. "If you get that business problem wrong up front, you can do a beautiful analysis, but you're analyzing the wrong problem. Or you can spend terrible amounts of time just churning, because you don't know how to interpret the data," he says.
The analytics master's program will teach students this entire process, he explains. And while he anticipates MSAn attracting a wide variety of applicants, he expects some student professionals who plan to use analytics in their current jobs. "We're seeing more and more companies that are embedding analytics into job roles and functions," he says.
Spreading the Word
Through mastery of analytics, capable professionals can turn into sought-after experts. During the 2012 presidential and congressional campaigns, Nate Silver achieved rock star status with his FiveThirtyEight blog at the New York Times. Through his knowledge of polling, Silver delivered razor-sharp analysis and extremely accurate election forecasting. He then landed a presumably lucrative perch at ESPN. Armour enjoyed Silver's Times columns, and he emphasizes his ability to explain the polls. FiveThirtyEight didn't just rely on number-crunching, but provided illustrative visual graphics and lucid writing.
The analytics field has taken the sports world by storm, with many pro teams incorporating advanced metrics to evaluate players. Yet, as evidenced by the popular book and movie Moneyball, this has created a culture clash. Statheads get frustrated with anti-analytics traditionalists, characterizing them as Luddites. But Armour says this is a challenge facing all analytics professionals.
"If I print out the results to you and hand you the results, and you're just looking at these numbers and graphs, you might have no idea what it is that I am talking about. Then you're just going to reject it because you don't understand it. And I don't blame you," he says. "You've got to present the information in a user-friendly manner, but then you need to make sure you show them statistically and otherwise why they should believe you."
Life and the Outdoors
Armour mostly grew up in Upstate New York. Though his father worked at IBM, he initially shunned a career in computers and got his bachelor's degree in psychology. But after taking a programming course, he eventually earned his master's degree in computer science. His Ph.D. from George Mason University is in information technology, with a specialization in software engineering.
Now living in Ashburn, Va., his passion for the outdoors includes gardening, fishing, hiking, biking, and traveling. And numbers and stats are present in another hobby: baseball. A longtime New York Yankees fan, he's fascinated by the link between sports and analytics.