Capping Off Their Master’s in Business Analytics Program
The inaugural class of master’s in business analytics students capped off their program with a capstone experience course that included consulting projects with a variety of regional organizations. Under the direction of Adjunct Professor Phani Kidambi, vice president -analytics & data science -strategy, digital & innovation, Wells Fargo, the student teams put what they had learnedin the classroom to work on real-world problems and solutions ranging from dashboards and databases to machine learning models and websites.
“The program was structured in a way that each course emphasized some stage of the data life cycle; from pulling and cleaning data, to manipulating it for your analyses, to dashboard creation best practices,” said Conor O’Regan ’20, ‘21G, who worked on a project for WaterGrass, a company that has built a database that helps growing nonprofits manage volunteers, donors, events, and more. “The faculty is incredible knowledgeable in this process and was able to prepare us over the span of the program to know exactly what to do when starting a new project in the real world. I found that in each step of the capstone project, while the actual problems I faced were new, they all related back to something I had learned in a previous course and felt ready to take on.”
O’Regan secured a job after graduation as a Data Analyst at the leading-edge Dana Farber Cancer Institute in Boston. He says it is the start of his long-term goal of being able to combine his technical passion of data analytics with his personal passion of “doing ‘good’ work, or work that puts people/the planet before profit. The work I will do for a nonprofit like Dana Farber directly affects people in need of help, which not only leads to more good in the world, but a more fulfilling career on my end.”
Interested in working with a student team of a business analytics project? Contact Nagaraj Bukkapatnam, director of the Center for Business Analytics.
Read more about the MSBA capstone projects:
J&J’s medical devices section deals with bone replacement surgeries focused on Knees and Hips. Inaccurate prediction of part sizes increases cost in production, inventory, and supply chain. This team was assigned with tasks of generating insights from the sample dataset and building machine learning models with higher prediction accuracy. The team accomplished the tasks by building dashboards which showcase quantitative insights on top performers across different variable and identified potential business expansion opportunities. The team also built Machine Learning models which can predict the required part size that reduces the overall cost for this department.
Watergrass offers fundraising, membership, and volunteerism data management services for growing nonprofits concerned with environmental conservation and protection. The students took on this project to draw valuable insights from 15+ years of data from ~30 organizations. They accomplished this by developing individual dashboards for each organization, an aggregated dashboard for Watergrass employees, and engineering a predictive model. As a result, each organization that works with Watergrass will be able to investigate specific questions they have pertaining to their donors/fundraising campaigns and Watergrass will be able to provide a high-level overview of the volunteerism landscape.
EB Capital Markets generates its current financial market reports by performing all its data collection manually and wanted a more interactive client experience. This team evaluated the leading financial APIs and web hosting services to find the best value for EBC where they automated EBC’s data collection via IEXCloud and AlphaVantage and created a proof-of-concept website for clients. EB Capital now has an automatically populated database, and a proof-of- website that can be further developed and launched.
Currently, all the incoming freshmen in the Paul School of Business and Economics are being assigned to their required freshmen classes manually by advisors. This team was tasked with finding a way to assign students more efficiently to predetermined “bundles” of classes. Through a combination of front-end data validation in Excel and an R script that performs the assignment function, the team was able to engineer a process that assigns roughly 90% of the students and eliminates much of the time spent on this tedious task.
J&J’s medical devices section deals with bone replacement surgeries focused on Knees and Hips. Inaccurate prediction of part sizes increases cost in production, inventory, and supply chain. This team was assigned with tasks of generating insights from the sample dataset and building machine learning models with higher prediction accuracy. The team accomplished the tasks by building dashboards which showcase quantitative insights on top performers across different variable and identified potential business expansion opportunities. The team also built Machine Learning models which can predict the required part size that reduces the overall cost for this department.
EB Capital Markets generates its current financial market reports by performing all its data collection manually and wanted a more interactive client experience. This team evaluated the leading financial APIs and web hosting services to find the best value for EBC where they automated EBC’s data collection via IEXCloud and AlphaVantage and created a proof-of-concept website for clients. EB Capital now has an automatically populated database, and a proof-of- website that can be further developed and launched.
Watergrass offers fundraising, membership, and volunteerism data management services for growing nonprofits concerned with environmental conservation and protection. The students took on this project to draw valuable insights from 15+ years of data from ~30 organizations. They accomplished this by developing individual dashboards for each organization, an aggregated dashboard for Watergrass employees, and engineering a predictive model. As a result, each organization that works with Watergrass will be able to investigate specific questions they have pertaining to their donors/fundraising campaigns and Watergrass will be able to provide a high-level overview of the volunteerism landscape.
Currently, all the incoming freshmen in the Paul School of Business and Economics are being assigned to their required freshmen classes manually by advisors. This team was tasked with finding a way to assign students more efficiently to predetermined “bundles” of classes. Through a combination of front-end data validation in Excel and an R script that performs the assignment function, the team was able to engineer a process that assigns roughly 90% of the students and eliminates much of the time spent on this tedious task.