Architecting the Trusted University: A Blueprint for Data Quality and Modernization

Can you provide trusted reports to University Leadership? Do you have quality insights to drive data-informed decisions? Most importantly, as you prepare for large-scale system modernization, are you confident you aren't bringing "dirty" and redundant data into your new environment?

Higher education is entering a transformative era where the promise of advanced analytics and institutional intelligence is hindered by the "Data Paradox": a landscape of siloed legacy systems, inconsistent constituent records and a fundamental lack of trusted data. Join our experts for a strategic deep-dive into the architectural framework for the "Trusted University." We will explore how to bridge the gap between fragmented information and institutional excellence through robust Master Data Management, Automated Data Quality and end-to-end Data Lineage.

Key Learning Objectives:

• Creating the "Golden Record": Learn how AI-powered data platforms automate the discovery, cleansing and mastering of constituent data to provide a 360-degree view of the student lifecycle
• Preparing for Modernization: Discover strategies to profile and standardize your data before migration, ensuring your next-generation systems are built on a foundation of "clean" and reliable data
• Automating Stewardship: See how natural-language-driven tools allow non-technical staff to take ownership of data quality rules and monitoring without manual coding
• Data Readiness: Explore how to assess and govern data readiness to ensure trusted, high-quality data supports analytics, reporting and modernization initiatives

Why You Should Care: As the "demographic cliff" approaches, the ability to deliver personalized student experiences and trusted institutional reports is no longer a luxury—it is an existential imperative. Attendees will walk away with a proven roadmap to move beyond "dirty data" into a secure, production-grade environment that drives measurable outcomes.

• CIOs, CTOs, and Chief Data Officers, VPs of Research and Research Administrators, IT Architects and CRM/System Admins, etc.
• Anyone responsible for the accuracy, reliability or strategic use of institutional data