AI governance begins with high-quality data. Clean, consistent, and well-documented data ensures AI models are reliable, unbiased, and explainable. By tracking data lineage, monitoring quality metrics, and visualizing them in tools like Tableau, organizations can reduce risk, improve compliance, and build trust in AI-driven insights. Simply put: better data quality = more responsible, transparent, and trustworthy AI

Agenda

TUG intro and Speaker intro (5 mins)

"Data Quality for AI Governance" (30 mins)

Q&A (10 mins)