Data Science: Teaching and mastering analytics
August 20, 2013 | Alicia Androich | Comments
Inside Schulich’s Master of Science in Business Analytics program
Data scientists can tell you everything from which customer you’re about to lose to how to best price your products. Using their unique and coveted skill set, they deftly mine golden nuggets from reams of data. A look at who they are and how they work their data-driven magic to help marketers
In September 2012, four students began in Schulich School of Business’ Master of Science in Business Analytics program at York University. It was the inaugural year of the one-year program and, judging by the fact that all its students (except for one starting her PhD) have been hired, it would seem there is a demand in the market. There are 15 students enrolled in the second year of the program with a couple more expected to join.
In addition to learning about analytics and quantitative methods, the students take management classes and spend their last semester doing an analytics project at a company (at which, in the ideal scenario, they’ll get hired on permanently). And there’s a new course called “Analytics Consulting” being added this fall that marries the act of analyzing data with content creation and messaging for clients.
The idea for the program was conceived by Murat Kristal, an associate professor and the program director. The students, he says, have come from a variety of backgrounds – some have MBAs, some have PhDs (one student enrolled for the fall has a PhD in chemistry, another in physics) and some have marketing backgrounds and realize they want to learn more about analysis. The common thread? They like numbers and solving puzzles.
He thinks the buzz around big data and data scientists grew from a gap in the industry when it comes to finding people who can actually do analysis.
Using churn as an example, he explains how big data can go beyond classical marketing research to tell companies how individual consumers are likely to behave. In the past, marketers relied heavily on focus groups to find out which product attributes consumers liked. “With the old marketing research—surveys, focus groups—you have a very small group that you can reach out to and you’re trying to make generalizations to the population.”
Big data, on the other hand, contains so much transactional data from the population that can be analyzed and then help pinpoint an individual. So rather than make inferences about the whole Canadian population based on a 10-person focus group, Kristal says data scientists can “analyze a million customers’ data, then pinpoint whether or not [a specific individual] will buy the next mortgage product that [a bank is] going to offer next week.”