From Chaos to Clarity: Building a Secure, Scalable Data Platform for UT Austin
This interactive learn and design lab outlines the journey of The University of Texas at Austin to overcome data silos and construct a centralized, secure, and scalable data platform in the cloud. Our challenges included fragmentation due to a mainframe-centric data landscape with siloed data from SaaS applications, as well as legacy systems, reporting inefficiencies, user mistrust, and lost opportunities related to analytics. Our solution was implementation of a cloud-based hub-and-spoke model, providing services like data integration, exploration, APIs, analytics, and AI/ML. The impact of this effort has helped us regain user trust, expanded our reporting capabilities by at least tenfold and improved reporting times, enabled data-driven decision-making for better student outcomes, and grown the skills of staff within our department. We’ll explore how trust is being rebuilt with the user community/stakeholders. We’ll also discuss lessons learned, design principles, security considerations, and the evolving role of data governance in the age of AI/ML for data architects facing similar challenges in higher education.
Presenters
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Sreekanth Bhagyanagar
Chief Enterprise Data Architect,
University of Texas at Austin
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Ashoo Shetty
Solutions Architect,
Amazon Web Services
Resources & Downloads
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Poster presentation From Chaos to Clarity
Updated on 10/19/2024