Erika-Kirsten Easton

As organizations increasingly rely on data-driven strategies and AI-powered tools, the ability to effectively manage data assets has never been more critical. This presentation will explore what Transport Canada has been doing to deploy an enterprise approach to data and analytics. Walk away with tactics on how to:

• Build robust data asset management practices that can significantly enhance analytical insights and unlock the full potential of artificial intelligence.
• Avoid data silos and inconsistent metadata, and build organizational data governance through better data cataloging, lineage tracking, and quality controls.
• Align data management practices with business goals and AI strategies to drive innovation and operational efficiency.

Enable faster AI model development, improved accuracy, and greater scalability with well-managed data environments