As tuition costs continue to climb and post-graduation employment remains stagnant, canny would-be college students turn an eye to evaluating which degree programs will provide the best return on their educational investment in the form of a solid shot at landing a secure position after picking up their diploma. Increasingly, equally canny colleges are capitalizing on this desire by customizing their offerings to what the labor market is currently seeking. The latest trend? Advanced degrees in the much-talked-about “big data,” which equip graduates to distill huge data sets into valuable B2B or B2C insights on behalf of organizations.
The University of Tennessee is among a growing number of institutions offering data-driven degree programs, which typically go by their more formal and accurate name - business analytics.
“Business analytics is determining the winners and losers in most industries. Ford cites analytics as playing a major role in its turnaround. Many companies such as Amazon, Google and Capital One have built their entire business model around analytics. Companies that see this are looking for the talent needed to integrate business analytics into their business strategy,” says Dr. Kenneth Gilbert, head of UT’s Statistics, Operations and Management Science department. In 2010, UT’s college of business was the first in the nation to launch degree programs in business analytics at the undergraduate, Masters and MBA level. Gilbert, who has been on the faculty at UT since 1980, isn’t as surprised by the growing popularity of business analytics as an area of study as he is by the growth of the data that fuels the need for the degree.
“It has not been a surprise how certain companies have used analytics as a growth strategy. Successful companies have always done that with the latest technical innovations. What is so incredible is the explosion in the amount of data, the velocity of the data, the types of data and the sources of data. There is real-time data from mobile devices, social networks, data sensors and many other sources.”
Haley Hubbard is one of UT’s Master of Science in Business Analytics students. She was drawn to the study of big data because of the career edge she believed it would give her.
“I worked for almost five years in the Forensic Services group at PWC, applying my accounting knowledge to financial investigations and litigations. During my time at PWC, I noticed that there were plenty of talented 'data' people and plenty of the talented 'business' people; however, the people who could do both were extraordinarily valuable to the firm and to my team’s ability to solve problems. That really got my wheels turning, and I started thinking about what other problems I might be able to solve if I knew more about analytics. My passion became clear: I wanted to tell stories from data. And, in order to do that, I knew I needed to add some tools to my tool belt.”
Hubbard credits her analytics education with teaching her that vast swaths of information aren’t useful to decision-making without context or analysis – a perspective that she plans to bring to her post-graduation employment.
“To me, ‘big data’ is more about the questions being asked than the data itself. I’ve learned that data does not provide business insights unless appropriately questioned. Success on ‘big data’ projects requires a thorough understanding of the problem, developing the right questions, harnessing the appropriate amount of data to answer those questions and clearly communicating the solution to the target audience.”
It’s a view shared by Alistair Croll, author of Lean Analytics: Use Data To Build A Better Startup Faster. “With an abundance of information, knowing what to pay attention to is a superpower,” he says. While Croll believes that the mantle of ‘data scientist’ as currently adopted by ambitious analysts will eventually go the way of the hopelessly vague ‘social media expert’ in terms of its utility in distinguishing the competent from the wannabes, the labor market advantage will belong to Hubbard and her peers for the next few years.
“I think anyone can learn to think experimentally and correctly about data, and this data-literate mindset will be ‘table stakes’ for most of tomorrow's jobs. But at the same time, data science requires hard math, engineering and technology skills. For the first few years, it will be experts with past experience who lead until it becomes commonplace or the tools catch up.”
The growth of data and the elevation of analytics into a corporate necessity for organizations of all sizes across all industries fascinates Croll and points to the long-term relevance of a degree in big data, even after the current hype fades.
“One thing that has changed is the liquidity in the job market. Before, a quantitative analyst in New York probably didn't consider working for, say, a dating startup. Today, there's a realization that these skills are portable across industries, which means more and more people are bringing a skill from one vertical into another. This cross-pollination is great for innovation.”
For UT, interest in their business analytics offerings from both industry and students continues to boom. The school recently inked a deal with Caterpillar to do analysis of the real-time sensor data from each piece of equipment sold in the last three years and graduate enrollment in the business analytics faculty has doubled in the last year.
