UC-Davis’ MS In Business Analytics

Professor Prasad Naik, co-founder of the MSBA program at UC-Davis. Courtesy photo

Program Name: Master of Science in Business Analytics

School: UC-Davis Graduate School of Management

Length of Program: 10 months

Cost: $55,000, plus an estimated $28,913 in additional costs (food, transportation, etc.), including $4,344 insurance fee

In a world where business schools have strived, often in vain, to reach gender parity in their student ranks, the new Master of Science in Business Analytics program at UC-Davis Graduate School of Management has achieved it and more. The MSBA, which launched this fall in San Francisco with an inaugural cohort of 43, is 55% women, says Hemant Bhargava, program co-founder and academic director and Jerome and Elsie Suran Chair professor in technology management.

“There is this whole thing about lack of women in technology, in Silicon Valley, in analytics,” Bhargava tells Poets&Quants. “So we decided from the beginning we would do something about that.”

Key to the effort to diversify the MSBA class profile, he says, was establishing a balanced left-brain, right-brain curriculum that emphasizes practical materials and effectiveness. Also key was the full scholarship UC-Davis launched, with funding secured by Bhargava through Google, for the top female applicant. “I think in Silicon Valley there is a recognition that this problem needs to be addressed,” he says, “and we said, ‘The only way you’ll employ people in industry is if we produce good graduates.’ And so that is the part we’re working on.

“Fifty-five percent is phenomenal. We did not discriminate in favor of women, but there was a conscious effort to reach out to people across different groups.”


Hemant Bhargava, co-founder and academic director of the new UC-Davis MSBA program

Three years ago, when Bhargava and Professor Prasad Naik began work on what would become the new MSBA, they found high interest across a number of UC-Davis departments, including economics, statistics, and computer science. They decided that while they would build a program just for the GSM — “I think single ownership makes things a lot easier from an administrative perspective,” Bhargava says — they still wanted input from those other departments. In short, they wanted to create stakeholders across the sprawling UC-Davis campus.

So they systematically approached other departments and requested support from key faculty and staff, making the nascent program a truly university-wide effort. “Prasad and I really were the founders of the program, but we got support from across campus,” Bhargava says.

This had three practical effects: first, when developing the program, there was no shortage of really good, expert advice. Second, in the approval process, the program from the start had an enormous number of boosters. And finally, input and help from industry wasn’t far behind.

“We talked to industry and we said, ‘What are the skill sets that you really need?’ and what we heard was very consistent with what I have seen in the last 30 years as an academic working in this field,” Bhargava says. “One, we all recognize the importance of things we call organizational effectiveness — things at the front end of the process like initiative, curiosity, creativity, aptitude, and identifying opportunities, and at the back end things like persuasion, change management, dealing with power and politics in organizations. One message we got was that these things are all really important in doing analytics work  — so we sort of thought of the left-brain, right-brain skills from the very beginning.

“And the second thing we recognized is that even though a lot of excitement around analytics happens around techniques like machine learning and so forth, the real hard work — 80% of the work — tends to be around very mundane data issues: data cleaning, getting data from multiple sources, common semantics. That was something we heard from industry which helped us design the program.”

How is this program different from what else is on the market? “What everybody does is, they do not want to give up on statistics or regression or some new form of data, and so in the end maybe they have one course slapped on about organizational stuff,” Bhargava says. “From the beginning we said we would have a number of courses with issues in identification and structuring of problems, communication of data, organizational politics and so forth. So then the challenge for us was how do we do all this and also provide a good technical education? The way we solved this problem was by adding on a layer of learning by doing, the project practicum, so every student must do a project that runs from the beginning to the end of the program.

“Most schools would give you a project at the end of the last semester or last quarter, and often that project is well-defined and then the students do the work to solve the problem. Instead what we have done is, our projects are actually not going to be well-defined. They’re scoped out with each company, but then the first two months, the students do the front end of the analytics activity, where they understand the business, define objectives, structure the problem, identify what data they want. So currently they are learning those skills as they do the work on the project. And similarly at the end, they’e going to have to go and communicate and persuade the company.

“So what we have done is, our curriculum doesn’t do everything. We have really identified the most important technical things that need to be in the curriculum, and we feel that we will give the students the foundation to pick up these additional pieces of knowledge that they’ll need for their project.”

Who is the ideal applicant and student? “During the admissions process, we picked students who were super strong in one of four skill sets: computing, quantitative analysis, knowledge of business, and organizational effectiveness,” Bhargava says. “And then we will put them in teams in the program, so somebody on the team is going to be capable of taking that next step to gain the additional learning for the team, whatever the subject. And then in their weekly project meeting, everything is discussed — new challenges, new solutions, new difficulties they’ve faced. So the whole curriculum grows much bigger.”

What’s the application process? Are GMATs or GREs required? An essay? Candidates may submit either a GMAT or GRE score. They must also have these prerequisites:

  • Bachelor’s degree from an accredited institution upon enrollment; and
  • Successful completion of coursework in these primary areas: computing (principles and use of programming and problem solving, and basic knowledge of R or Matlab), mathematics (differential calculus, integral calculus, linear algebra), statistics (basic probability, densities and distributions, ordinary least squares, multiple regression).

Admissions requirements include a 300-word essay, two recommendations, and a $125 application fee. Selected candidates will receive an invitation to complete an online admissions video. After completing the video, selected candidates will be invited to an on-campus or video interview.

What are the application deadlines? Round one application deadline is October 11. Round two deadline is November 29, and round three deadline is February 14. Round four deadline is April 18.

What will students learn in the program? What’s the program format? The program is 40 units of graduate courses including a series of project courses over 10 months that are equivalent to 10 units. Courses are divided into four tracks: business, computing, analytics, and a Practicum. Courses for each:

Business: • 401 – Introduction to Business Analytics (2 units)

• 411 – Problem Structuring (2 units)

• 402 – Organizational Issues in Implementing Analytics (2 units)

• 403 – Organizational Effectiveness Workshop (2 units)

Data: • 421 – Data Management (2 units)

• 431 – Data Visualization (2 units)

• 422 – Big Data (2 units)

• 423 – Data Design and Representation (2 units)

Analytics: • 441 – Statistical Exploration and Reasoning (2 units)

• 442 – Advanced Statistics (2 units)

• 452 – Machine Learning (3 units)

• 443 – Analytic Decision Making (3 units)

• 453 – Application Domains (3 units)

Practice: • 461 – Practicum Initiation (2 units)

• 462 – Practicum Elaboration (2 units)

• 463 – Practicum Analysis (2 units)

• 464 – Practicum Implementation (2 units)

What do you expect student outcomes to be? The UC-Davis Career Development team partners with graduates of the MSBA program to pinpoint industries and companies of career interest. The MSBA team works with graduates as well, helping them engage with employers/recruiters. The Career Development office boasts one of the highest placement rates in the U.S. for the UC-Davis full-time MBA program (91% placement) and graduate accounting program (100% placement). The MSBA Practicum course also serves as an avenue for potential job opportunities.

“We expect to place everybody,” Bhargava says. “My feeling is, there is a huge demand, and a lot of the companies on our advisory board, one of the things they want to do is hire our students, so I feel very optimistic about placing them.”

Additionally, because the UC-Davis MSBA is a STEM-certified program, international students can qualify for a 24-month Optional Practical Training Extension after graduation to remain in the U.S. and receive training through work experience.


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