Opportunity abounds for people who can extract value from Big Data—complex, overwhelming datasets that can offer predicative insights.
Data has become currency unto itself. Now that corporations have your information, they need people to harness and transform that data into something tangible.
Academia has been a particularly fertile petri dish for companies to develop solutions to understanding their vast quantities of data. In the last 10 years, many top American business schools have sought to incorporate Big Data techniques into their curricula, either through MBA specializations or standalone degrees.
Here’s five US business schools blazing a trail in big data analytics:
1. MIT Sloan
MIT Sloan’s long been a fixture at the data science rodeo and, in many ways, has set the tenor for contemporary data degrees.
Michelle Li, director of MIT Sloan’s Master of Business Analytics Program, says: “Academic excellence in data science and business analytics has always been core strengths of MIT Sloan and the MIT Institute more broadly.
“A critical component of MIT Sloan’s education is being able to combine rigorous theory with real-life business problems. From the globally-recognized Operations Research Center to the Computer Science and Artificial Intelligence Laboratory to the Initiative on the Digital Economy—strong communities of thought leaders within Big Data, Machine Learning, and Artificial Intelligence have allowed MIT Sloan to attract the most talented faculty, students, researchers and companies.”
2. Duke Fuqua
Duke Fuqua’s Master in Quantitative Management (MQM) and Management Science and Technology Management certificates are two stellar examples of more recent programs that give graduates the skills to identify insights, explain the business applications effectively, and help put that information into action.
Senior associate dean Russ Morgan explains:
“We know that every aspect of business is being enhanced by analytics in some way. We are continually in conversations with industry about skills needed in business today [and] we hear again and again from business leadership about the need for people who could not only identify key insights in big data and translate those insights into actionable tactics in a particular business.
“Being able to communicate the insights and the potential impact and actions is a critical piece of being effective in this area.”
The nature of data science creates a certain distance from the insights the data represents. Whereas many programs foster that detachment, the Wharton Customer Analytics Initiative opts for a “Learning by Doing” approach to data, according to Eric Bradlow, Chair of the Marketing Department, Professor of Marketing, and WCAI Co-Director.
“We have been able to utilize these data sets to increase academics’ access to real problems and therefore practical algorithmic solutions to them. We utilize data and the problems of real companies in developing content—online courses, workshops, and datathons—that give our students hands-on experience in analytics.”
4. UCLA Anderson
UCLA Anderson’s slogan “Think in the Next” is embodied by the school’s Easton Technology Management Center, which equips future business leaders to “understand the power of big data analytics regardless of their concentration or industry.”
Faculty Director John Blevins explains: “Big data is a powerful tool business leaders must leverage to make informed, insightful and immediate decisions that enable them to rise above their global competition.
“With over 29% of students coming to Anderson from a technology background and over 32% leaving campus with jobs in the technology field, our campus is globally known as the MBA program where business management and technology leadership come together.”
Insights from algorithmic systems have the potential to offer broad perspectives that benefit companies, consumers, and society at large. Yale’s Centre for Customer Insights’ (YCCI) Big Data projects have embraced issues with far-reaching impacts.
Recent projects have involved collaborations with a fintech firm to select and incentivize front-line customer care professionals; IBM to develop a predictive model for anticipating consumer churn rates in the telco industry; and optimizing resource deployment to improve roadway safety for the TN Highway Patrol.
The truth about socio-technical systems is they can only tell us so much unless they are tempered by consumer insights. A human-centric approach to data seems to be one of the cornerstones of YCCI’s ethos as Director and Professor Management and Marketing Ravi Dhar explains:
“What Yale has tried to do is take an approach that integrates the top-down strategic frameworks with bottom-up analysis of the data.
“For example, the data is excellent at looking at consumer footprints in arms of 4W’s: who, where, when and what. But data requires top down consumer insights framework to answer the fifth W: the why. Without the why, it is hard to generalize the learnings to many situations.”