How The Ohio State University modernized their data foundation with AWS

For many higher education institutions, critical data is trapped in disconnected systems, making it nearly impossible to get a unified view of students, faculty, and operations. The Ohio State University transformed their data infrastructure by migrating to Amazon Web Services (AWS), reducing critical data processing times by 50% while creating a unified data environment. Glenn E. Donaldson Jr., chief architect and director of Enterprise Architecture, Integration Enablement, and Data Engineering at Ohio State’s Office of Technology and Digital Innovation, recently shared how his team transformed the university’s data landscape from a “spaghetti database” into a unified, scalable platform powered by AWS services.

Breaking down data silos

The Ohio State University faced a challenge familiar to many large institutions: critical data trapped across disconnected systems spanning departments (such as human resources (HR) and finance) and enterprise systems (such as Salesforce and ServiceNow). This made it challenging for different departments to access the same data. For example, not every office could access important data that the enrollment team used daily.

“How can we take the student data and have it accessible to everyone who needs it while still ensure individual privacy? That was the key business question,” Glenn noted. The university’s legacy on-premises Oracle-based operational data store (ODS) for student data, serving them since their 2008–2009 PeopleSoft Campus Solutions implementation, had reached its limitations as institutional needs evolved.

Reimagining data architecture with AWS

Rather than merely migrating systems, Ohio State’s leadership recognized an opportunity to fundamentally reimagine their data architecture. The PeopleSoft migration became the catalyst for building what Glenn calls a “scalable, extensible data foundation.”

Glenn’s team selected Amazon Redshift as their central data repository, replacing their on-premises Oracle infrastructure. They paired it with Apache Airflow for workflow orchestration and AWS Glue to simplify and accelerate data pipelines.

The team also implemented a medallion architecture—a data organization pattern using bronze, silver, and gold layers representing raw, refined, and curated data. Raw data lands in an Amazon Simple Storage Service (Amazon S3) data lake, and refined and curated data lives in Amazon Redshift. AWS security and governance frameworks underpin every layer, centralizing and federating trusted data across the institution.

The result: a unified data environment that eliminated artificial barriers between data domains and created new opportunities for institutional insight.

Measurable results demonstrate the power of AWS infrastructure

The results demonstrate the transformative power of AWS services for higher education:

• Data processing reduced from 6 hours to 3 hours
• Course and student data processing reduced from hours to minutes
• First unified data environment since the mid-1990s, with all primary data domains and enterprise resource planning (ERP) systems consolidated in Ohio State’s Reporting and Analytics Environment (RAE) on Amazon Redshift

These improvements fundamentally enhance the university’s ability to respond to student needs, support faculty research, and make data-driven decisions at an institutional scale.

Architecture that enables innovation

The Ohio State University’s AWS powered architecture reflects strategic thinking extending far beyond immediate needs. Their unified environment now includes PeopleSoft Student systems, Workday HR and Finance data, Learning Management Systems, Salesforce, ServiceNow, Cornerstone OnDemand, and an expanding list of institutional systems.

The university’s medallion architecture with bronze, silver, and gold data layers on AWS creates sophisticated data governance while maintaining accessibility. This approach means that stakeholders can access information at appropriate refinement levels while maintaining institutional governance standards. Glenn’s team developed robust governance processes aligned with AWS best practices: “Do we need real-time or batch; what is the system? Do they have APIs? What is the frequency of need? Daily, weekly, or hourly?” These standardized questions support consistent approaches regardless of integration complexity.

The human element of cloud transformation

Converting over 600 users to the new AWS powered system within 6 months required more than technical expertise; it demanded institutional leadership and vision. The team’s 3-month change management process included extensive educational webinars and proactive stakeholder engagement. “The biggest hurdles to the change would be education, not technology,” Glenn reflects. His key lesson was to move faster on customer engagement and address concerns upfront. This human-centered approach separated their successful AWS migration from the kinds of failed projects that plague many institutions.

AI and advanced analytics drive future-ready architecture

Ohio State’s AWS foundation positions them for adopting emerging technologies and advanced analytics. The university is exploring Model Context Protocol (MCP) enabling technology, creating personal workspaces where faculty and staff can use AI tools tied to their specific work contexts.

Current applications include room utilization heatmaps for hospital facilities and connecting faculty research with genomic data through federated security systems. Glenn envisions personal workspaces where MCP and large language model (LLM) technologies enable secure collaboration with researchers at other institutions.

The university’s approach demonstrates how strategic AWS architecture enables innovation, positioning Ohio State to adopt emerging technologies based on institutional needs.

Key lessons for higher education leaders

Ohio State’s AWS transformation offers critical insights for higher education leaders:

• Start with strategic vision – View your cloud migration as an opportunity to build comprehensive data infrastructure and break down data silos, not merely move systems. Ohio State’s success stems from using AWS services to create scalable, extensible foundations. The AWS Cloud Adoption Framework (AWS CAF) helps institutions develop strategic cloud adoption plans aligned with business goals.
• Invest in change management – Technical implementation represents only part of the challenge. Extensive stakeholder education and proactive concern resolution prove essential for AWS adoption success. EDUCAUSE has numerous resources related to change management.
• Build for extensibility – Design AWS architectures with future capabilities in mind. Ohio State’s medallion architecture and governance frameworks demonstrate how universities can prepare for emerging technologies while maintaining oversight. The AWS Well-Architected Framework provides comprehensive guidance on designing architectures with future capabilities in mind.
• Embrace continuous improvement – Ohio State’s ongoing optimization approach, reducing processing times from 6 hours to 3, then continuing improvements, reflects the mindset necessary for sustained cloud transformation.

The path forward for higher education

Ohio State’s transformation from “spaghetti database” to AWS powered data foundation demonstrates that strategic modernization is essential for institutional competitiveness. The results have already sparked new collaboration: campus researchers with complex datasets and management systems of their own have reached out to Glenn’s team. “They’re now interested in working together and we’ll advise them or even do this work,” Glenn notes—a direct outcome of building a foundation others want to build on.

Glenn’s roadmap extends that foundation further: expanding medallion architecture artifacts to accelerate new system integrations from months to weeks, implementing data virtualization and zero-ETL approaches to reduce data movement overhead, and enabling AI across institutional functions through MCP and LLM technologies.

For higher education leaders, the question isn’t whether to modernize, it’s how quickly you can build a scalable, AWS powered data foundation that positions your institution to serve students and advance your mission more effectively.

The AWS advantage in higher education

Glenn Donaldson and his team have proven that strategic data modernization creates possibilities far beyond technical improvements—from breaking down silos to enabling AI-powered collaboration across the institution. For higher education leaders, the roadmap is clear: build a scalable, extensible data foundation now, and your institution will be positioned to serve students, support faculty, and advance your mission more effectively for years to come.

To learn more, contact your AWS account team or visit our AWS for Education solutions page.

DISCLAIMER: This content is not to be viewed as an endorsement by Ohio State of Amazon and its products or services.

Further reading

• Amazon Redshift best practices in the Developer Guide
• Guidance for Data Lakes on AWS
• Analytics on AWS