Tue, Jun 16 · 11:30 AM CDT
Most organizations don't have a data problem —they have a trust, speed, and scalability problem.
As business demands accelerate and AI adoption increases, legacy data environments are struggling to keep pace. Aging platforms, fragmented architectures, and manual processes often create barriers to delivering trusted data when and where it's needed most.
In this session, we'll explore what data modernization really means and the practical steps organizations can take to transform legacy data estates into modern, governed, cloud-native platforms.
Attendees will gain insight into the key phases of a successful modernization journey — from assessing the current state and defining a future vision to building scalable data foundations, implementing governance by design, and enabling long-term business value.
What You'll Learn
Why organizations are prioritizing data modernization initiatives
How to assess your current data landscape and define a target-state architecture
The critical role of governance, security, and data quality throughout the modernization journey
Best practices for designing, testing, and deploying modern data platforms
How modernization supports advanced analytics, AI, and data product strategies
Strategies for continuously evolving and optimizing your data ecosystem
Who Should Attend
Data Management and Governance Professionals
Data Architects and Engineers
Analytics and BI Leaders
IT and Technology Leaders
Data Strategy and Transformation Teams
Whether you're just beginning to evaluate modernization efforts or actively migrating away from legacy platforms, this session will provide a practical roadmap for building a scalable, trusted, and AI-ready data foundation.
