IF THIS COURSE [“DATA SCIENCE IN BUSINESS”] CAN HELP OUR STUDENTS HAVE THE ABILITY TO UNDERSTAND THE WHOLE PROCESS, I THINK THEY’RE GOING TO HAVE A REAL EDGE IN THE WORKPLACE,” —ERIC TASSONE, (RIGHT) A DATA SCIENTIST AT GOOGLE WHO HOLDS A UVA LAW DEGREE AND A PH.D. IN BIOSTATISTICS, CO-TEACHES “DATA SCIENCE IN BUSINESS.”
student at University College London, the case has served as a springboard for an ongoing research project aimed at better predicting the lifecycles of social media companies. “If you look back at a once-prominent company like MySpace, its search volume on Google of course exploded but then came down,” Lichtendahl explained. “If you go back and look at the hundred or so social media companies that started up over the last 15 years, they follow these similar rise and fall patterns.” “There really aren’t good statistical models that can put together and capture the pattern we see in these lifecycles,” he added. “So we’re trying to develop a better model.” Though still in development, their model has been proving more accurate than some other competing models, Lichtendahl said. In the course, the case study on Google Trends is meant to teach students about the data science process — from forming a good question and making hypotheses to actually collecting the data. They use a technique called Web scraping to collect the data from Google Trends, and work with it in R — a free, open-source statistical computing language that students use throughout the course. “I realized that students may want to learn R; that people in practice are actually using it like they use Excel — even on Wall Street, there’s a growing contingency of folks who are treating R like it’s Excel in the ’80s or ’90s. It’s their core analytical workhorse,” Lichtendahl said. For their final projects, students work in groups to build their own case — they propose a problem, collect a data set, build a model and make predictions, and then report back on how well their model did. “We look at who asked a really hard question, who found a really great data set to answer that question, and how did
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answering that have an impact on business,” Lichtendahl said. “Did it help somebody think about a new business, or a better way to do something that already exists?” While some students are seeking to master technical skills, for others the course’s value is in exposure to the way data scientists work. Bridging the gap between such scientists and people with business expertise is a challenge in current business practices, Lichtendahl said. He and Tassone believe it is one MBAs can meet if they have enough exposure to the workings of data science. “If this course can help our students have the ability to understand the whole process, I think they’re going to have a real edge in the workplace,” Tassone said. “The data itself is growing, the data scientist role is growing, “If you look back at a and data analyst jobs once-prominent company are growing. If they can develop the ability to like MySpace, its search thoughtfully critique and volume on Google of push back on this work, it’s going to be a better course exploded but environment for everythen came down,” Lichtbody.” endahl explained. “If — Laura Longhine
you go back and look at the hundred or so social media companies that started up over the last 15 years, they follow these similar rise and fall patterns.”