Program Name: Master of Science in Business Analytics
School: University of Minnesota’s Carlson School of Management
Length of Program: 12 months
When the Carlson School launched its MSBA three years ago, the most important thing on the mind of Ravi Bapna was that the program he directs turn out data superstars who can speak the language of business. That in mind, the curriculum he designed stands on four main pillars.
“The first pillar is, we take people with STEM backgrounds, with about three years of experience, and we bring them into the business school so that we can first of all ground them in the language of business,” says Bapna, Curtis L. Carlson chair in business analytics and information systems and academic director of the Carlson Analytics Lab. “So we give them functional training and marketing, make sure they do a financial accounting course so that they know the difference between a P&L and a balance sheet. We make sure that they understand that analytics is a team sport, so how to work in teams, and obviously state-of-the-art management principles. That’s one pillar.
“The second pillar that is really important is, we want to make sure that they are technically really good. So they do an an advanced Python programming course, they do a database and data warehousing course, and then they get into big data architectures where they can deal with massive amounts of data.
“The third and I would say the most comprehensive pillar, which we also integrate with our experiential component, is the modeling part, the actual analytics. So we start them off with statistics, but then they do two machine learning courses — one exploratory, the other predictive — and they do a course on causal inference. If you look around at other curriculums, this is something that many miss out on, even companies miss out on: actually designing your data infrastructure in a way to get to causality. The smart companies, the Facebooks, the Googles, the Microsofts of the world get this, but the others don’t.
“So we have a course on causal inference, predictive analytics which is optimization, things like forecasting, assimilation. So this is a very comprehensive, massive toolkit to tackle different problems in terms of dealing with data and getting insights.
“And then all of this really comes together in the fourth pillar, the spring semester when we do a 6-credit, experiential learning project, which involves real clients, real data, real problems. So they have to go through the whole life cycle of applying everything that they’ve learned. That’s there high-level story of the curriculum, so to speak.”
Why did Carlson launch the program? “We started this three years ago with the recognition that businesses are going to be transformed in the short term to be data-driven in their decision-making. It’s almost a perfect storm right now, not just in terms of data but also with huge advances in computing and tools. I think there is finally recognition among senior executives and leaders that going by ‘gut feel’ is just not good enough. You have to leverage the data to get new insights.”
How is it different from what else is on the market? In addition to the spring-semester-long capstone project, the program has an accelerated capstone over a four-week span between summer and fall. “One of the innovations we have done this year for the first time was to take the experiential component and even go deeper in some of the key courses,” Bapna says, explaining how the summer Intro to Analytics course contained a forecasting problem involving a massive data set from a real company. “And even with very limited tools, the students have to use creativity and ingenuity to strategize and tackle the problem. … So we now have a live-case contest within a course, with 16 teams competing to solve a real-life problem.”
Carlson is a leader in teaching cases around analytics, Bapna says. “Harvard does not do this. There’s a huge shortage of cases that come along with rich data sets which can be used broadly to teach interesting questions and methods to answer those questions, and that’s another area of leadership for us.”
Bapna says the Carlson MSBA differs from what’s on the market in three key ways. First, he cites the school’s “long history of excellence” in information sciences, with a department regularly ranked in the top 10 by U.S. News and World Report. “In our own research, we have been doing analytics for eons. This is the language that we speak.”
Second, Carlson boasts “deep relationships’ with 18 Fortune 500 companies, “and we can work that into actual experiential learning components in the curriculum, by having live-case contests inside key courses, by having a 6-credit super-influential capstone project at the end — I haven’t seen other programs, even the ones I admire like CMU or UT-Austin, have that extent of experiential learning.”
Lastly, Bapna says. Carlson’s community is second to none. “We have 30 external mentors,” he says, pointing to senior executives at major corporations who regularly work with student groups. “So we’re truly trying to build a community of excellence in this space.”
Who is the ideal applicant and student? The program is looking for students with STEM — science, technology, engineering, and math — backgrounds who have about three years’ work experience. “We want someone who has a lot of curiosity,” Bapna says, “who has a willingness to learn some pretty advanced technical concepts, but then in the end turns out to be a really good translator between the business folks and the technical folks. The ideal person is someone who really understands how they can match business problems to analytical solutions and actually knows enough to implement them.”
What’s the application process? Are GMATs or GREs required? An essay? Applicants must provide transcripts, take either the Graduate Management Admission Test or the Graduate Record Exam, and have taken at least one one-semester college-level calculus course in which they received a “C’ grade. Applicants also must write a 750-word “Applicant Statement,” submit three letters of recommendation, and be available for an in-person or Skype interview.
Most importantly, applicants must demonstrate proficiency in one or more of the following programming languages: Python, R, C, C++, C#, VB, Java, Pascal, and Fortran. Proficiency can be demonstrated through transcripts, on a resume, or by certificate.
What are the application deadlines? The application deadline for international students — who comprise 88% of the Class of 2017 — is February 1. After February 1, applications from domestic candidates are considered on a space-available basis. “We are still accepting applications for domestic students,” Bapna says. “We have an imbalance, as most of these programs have, which is that a large majority of applicants are from India and China, and it’s our objective to have more balance in the class, so we are trying to reach out to domestic students. We even have scholarships available for qualified domestic students right now.” Effectively, the deadline for domestic students is mid-March, Bapna says.
What will students learn in the program? What’s the program format? Foundational business courses happen in the summer, fall semester is “very intense,” with two machine learning courses, data warehousing and big data courses, and spring, in addition to the capstone project, is when students take advanced analytic courses. “One thing the students really complain about is that they don’t get too much sleep,” Bapna says.
Please describe the capstone project. Students are broken into 16 groups of five to complete 16 different projects, “tackling these really interesting questions for all kinds of companies, from large health insurance companies to multinational manufacturers, you name it.”
What do you expect student outcomes to be? “Spring semester is really all about the project and about the placement,” Bapna says. “Last two years we placed 100% of our students within 90 days of graduation. This year we have a bigger class (80 students) but things are picking up right now.
“We have had 100%, so anything lower than that would be coming up short, but it’s a bigger class and we have more work to do, so we are trying hard. We have been placing students coast to coast, and because the students come from all corners of the world, they are not particularly tied to any geography. So if they find an interesting opportunity in Seattle or the Bay Area or New York or in Virginia with Capital One, or with Walmart in Arkansas, they go there. Our students are pretty flexible.”