With an emphasis on hands-on learning, the Binghamton University MS Data Analytics program collaborates with a number of organizations to provide students with team-based data analysis projects. These projects are one of the most invaluable experiences of the program, as it gives students a chance to work with real-world datasets to glean insights and provide strategic recommendations.
The projects take place in the two practicum courses, with a goal of ensuring that students understand the curriculum of the program through the framework of problem-solving. This allows them to put the knowledge and skills they learned in the program to the test in a real-world setting.
If your organization is interested in teaming with our students for a project, you can learn more and apply for a project at this link.
While the projects offered differ from year to year, they are guaranteed to help students learn how to use their data analysis expertise in beneficial ways.
Recent projects include:
- Analyzing data from a major investment bank on business-to-business sales to assess the current state of the market, derive insights and recommend strategies to increase business.
- Working with a major automobile manufacturer to build predictive models to forecast sales trends. Students analyzed aggregate relationships between actions along the purchase funnel and conversion signals, such as lead generation and sales.
- Analyzing data from a local hospital on heart-related operating room costs. Students used information such as itemized consumables per case, duration, type of case and time to find relationships in outcomes such as length of stay and physician efficiency.
- Working with a regional financial institution to determine the pandemic’s effect on transaction volumes at physical branch locations. This information helped determine how customer channel usage (physical branch visits, online banking, etc.) has changed since the start of the pandemic, and if those changes will continue after the pandemic, affecting future banking trends.
- Analyzing purchase data from a top software company to identify product recommendation strategies to fulfill consumer shopping needs. Students looked at products that were frequently purchased together to strategize ways for the company to make more effective purchase recommendations to customers.
- Analyzing data from the City of Syracuse on water billing, rental registry certificates and parcel data to create predictive models of what properties are likely to be rentals.
