How the University of Minnesota Athletics built a unified data layer to drive fan engagement with AWS

Every ticket sold to a University of Minnesota athletic event changes hands an average of three times. Multiply that figure by the more than one million people passing through the university’s turnstiles each year, and you begin to see the scale of the transactional data that the University of Minnesota Athletics Department (Minnesota Athletics) manages.

Twenty years ago, these interactions would’ve been difficult, if not impossible, to trace. Today, digital ticketing leaves behind a detailed data trail that can drive revenue and strengthen fan engagement.

Minnesota Athletics had access to all that data, but lacked a way to bring it together. Even answering simple questions, like how many tickets were sold and who received them, required hours of cross-platform data wrangling.

In less than a year, the department replaced that complexity with a scalable data lake built on Amazon Web Services (AWS). The new data architecture—which gives the department full visibility into ticketing transactions and digital behavior—was built by a small internal team, without requiring a complete overhaul of their existing systems.

Minnesota Athletics: The “front porch” of the university

Minnesota Athletics supports more than 600 student athletes across 22 varsity programs. The department operates out of the university’s flagship campus in the Twin Cities—one of the largest in the Big Ten.

While on-campus pride for the Gophers runs strong, the department’s reach extends far beyond the university. According to Travis Cameron, associate athletic director and chief revenue officer at Minnesota Athletics, only about half of season ticket holders are alums. The other half are local residents and longtime Gophers fans.

This broad appeal in university athletics, along with other on-campus public events, positions Minnesota Athletics as the “front porch” of the institution. “The athletic department is where the general public connects with the university,” explained Cameron.

While the department had a solid digital ecosystem to track and analyze key metrics around these events with third-party software platforms, including ticketing and transactional data, gameday and in-venue mobile entertainment, and website digital behavior, the tools were loosely connected, and data was shared in only one direction. They worked well enough to operate day to day, but not to answer bigger questions about fan behavior or engagement.

A vision-driven approach to a unified data layer on AWS

With a goal to own and manage its data to build stronger fan relationships with real-time data analysis, Minnesota Athletics set out to create a centralized data layer. This architecture would ultimately bring together data from every available source and deliver insights without the need to rebuild workflows each time a new initiative came along. The concept of a data lake emerged naturally from that vision.

To start, the team reached out to the university’s central IT department. Because the University of Minnesota already had an agreement with AWS, provisioning moved quickly. “We started asking questions, and just like that, we were up and running,” said Cameron.

AWS made sense for several reasons. Its pay-as-you-go pricing allowed the department to start small and scale gradually, without committing to long-term contracts or overhauling existing tools. And, importantly, the team maintained full control of their data. “The administration saw the ROI almost immediately,” said Cameron. “The speed at which we were able to get this up and running was quite impressive.”

The team was also strategic in its implementation plan: its initial focus was solely on modernizing ticketing data in a data lake. This refined launch helped show value early, gain buy-in, and avoid scope creep while laying the foundation for more advanced use cases.

Building a secure, flexible system with a small internal team

With architectural support from AWS, Minnesota Athletics completed its initial data modernization platform in less than eight months with a lean, three-person team. AWS’s guidance was instrumental in establishing the centralized system and helping the team build it securely and reliably. Together, they established credential management and designed built-in redundancy to prevent common delivery issues, like missed data transfers or inconsistent file timing.

At a high level, the modernized data architecture uses Amazon Simple Storage Service (Amazon S3), AWS Lambda, AWS Glue, Amazon CloudWatch, and AWS Secrets Manager, Ticketing data is transferred from the university’s vendor into a private Amazon S3 environment. Access is tightly managed using AWS Secrets Manager and secure file transfer protocol (SFTP), supporting credential security and data integrity from the start. As files arrive, AWS Lambda and AWS Glue automatically clean the data, remove duplicates, and standardize formats, leaving the records structured and ready for analysis.

To avoid missed data due to timing issues, the system includes automatic redundancy checks that compare new data against vendor archives and backfill any gaps. Each stage has its own Amazon S3 bucket with built-in versioning for rollback or reuse.

“Our goal was to put off making any irreversible changes,” said Cameron. “AWS is good at allowing that.” Now that the system is live, it runs in the background without manual intervention.

The impact of centralizing university athletics fan data

One of the first major outcomes of this project was a predictive pricing model for football season. The team tested it last year to forecast demand and price inventory more effectively. Even in a down year, the model projected a 3-5 percent lift in revenue and helped minimize losses. It now serves as the foundation for ongoing pricing and yield strategies.

With the ticketing data lake in place, Minnesota Athletics is expanding into new initiatives. One is a golden record project to create a single, unified customer profile by linking data across tickets, concessions, retail, and donations. This initiative will help the department better understand individual behavior, engagement, and value.

“It feels like everything we want to do is attainable,” Cameron said. “Now it’s about setting priorities and getting it done.”

Lessons from the Minnesota Athletics playbook

For other universities looking to take on a project like this, Cameron has a few key pieces of advice:

1. Start with a clear, narrow vision for phase one. “You have to be clear about what you want to accomplish,” he said. For Minnesota Athletics, that meant focusing only on ticketing data at the start. The team didn’t try to build a perfect system all at once; they solved one problem well and built from there.
2. Scope out how to get to your goal, what it will take, and how to tie it back to ROI. He says that even if a project doesn’t have a direct return, it’s important to connect the investment to something that does.
3. Leverage any existing campus AWS agreements. “Contact your IT department, find out if you’re an AWS campus, and start engaging with them,” he said. “Talk about how to get from point A to point B.”
4. Know that small teams can succeed. Minnesota Athletics future-proofed its data landscape with a three-person team. What matters more is having a clear vision, internal buy-in, and the commitment to see it through.

A strong foundation for future growth

With a centralized data infrastructure now in place, Minnesota Athletics is better positioned to make data-driven decisions that deepen fan engagement, increase revenue, and support the future of college sports.

Using AWS, the department built a secure, flexible system that makes it simpler to access and use their existing data—helping them make smarter decisions and build stronger connections with fans.

Learn how AWS helps institutions and athletic departments build secure, scalable solutions. Contact AWS today.

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