Data science has gone from the preserve of geeky engineers to one of the most preeminent and sought-after proficiencies in a business manager’s toolbox. One recent study from the Graduate Management Admission Council, which runs the GMAT, said that demand for business school graduates in data analytics roles had outstripped demand for them to work in consulting and investment banking functions — their traditional forte.
Clever data analysis promises to fundamentally change the way companies make decisions. The ever-growing amount of data means there is a rising need for managers who can pull good information out of the mess, and turn insight into action.
Examples include marketeers or salespeople combing through customer data to create more targeted ads and pitches, but beyond that, data science is transforming the work of businesses in all industries, from finance and banking to retail and transportation.
Data science MBAs on the rise
As a result of the widespread embrace of data science, business analytics courses are cropping up on MBA programs at a rapid rate, and schools are launching standalone master’s programs too. Of 209 business schools surveyed recently by Kaplan Test Prep, an education services company, 72 percent said they offered courses in the subject.
INSEAD Business School of France and Singapore last year overhauled its MBA syllabus to include focuses on data science and fintech, for example.
And already this year, a number of US-based business schools — including the University of Michigan’s Ross School of Business, the University of San Diego and the University of Virginia’s Darden School of Business — have launched MBA concentrations in Business Analytics or specialized degrees in the field.
MBA students will need a thorough education in the art of data science, given the growing prevalence and importance of it in the corporate world. This includes the economics of analytics, its strategic ramifications and the more technical content, such as how to use algorithms, says Cornell Johnson assistant professor Shawn Mankad.
He teaches two courses for MBAs that are data-science focused: one on databases and SQL systems; the other on machine learning — a form of artificial intelligence in which computer systems are trained to “learn” by spotting patterns in massive data sets.
“There is a strong need in business for leaders who understand all dimensions of analytics in an enterprise environment,” Mankad says.
Learning to work with data scientists
In addition to lectures and classroom discussions, Cornell MBA students analyze several datasets on their own throughout a semester to gain hands-on experience of the full analytics process: from querying, cleaning, exploring and visualizing data, to exploring several machine learning algorithms and selecting the best one to predict a business outcome.
“These exercises reveal insights about how to work with statisticians and data scientists,” says Mankad, which is now essential for effective management.
At UC Berkeley’s Haas School of Business, finance and strategy lecturer Gregory La Blanc says he does not expect most MBAs to become true data scientists. “But we do expect them to know enough to be able to build and manage teams of data scientists, to design business strategies around data, and design organizations that make all of their decisions using data and experimentation,” he says.
He adds: “The ideal MBA serves as the interface between the technical and the non-technical members of the team.”
Read the source article in FindMBA.