Expert Panel: From Raw Data to AI-Ready Insights: Building Trust in Modern Analytics
Webinar Speaker: Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics
Date: Monday, April 13, 2026
Time: 9:00 a.m. PT / 12:00 p.m. ET
AI-ready insights depend on trusted, governed, and context-rich data. As organizations expand analytics and AI initiatives, the pressure to deliver reliable, explainable, and production-ready insights has intensified. Yet TDWI research continues to show that data quality remains a persistent stumbling block for analytics and AI. Lineage gaps, inconsistent definitions, fragmented governance processes, and limited observability undermine confidence in both dashboards and AI-driven decisions.
While many enterprises have invested heavily in modern data platforms, the challenge is not simply storing more data, it is ensuring that data is accurate, traceable, well-understood, and governed across its lifecycle. This becomes even more complex with unstructured data. Building trust requires coordinated practices spanning data quality management, metadata and lineage, and governance frameworks.
In this expert panel webinar, we’ll explore how organizations are moving from raw data to AI-ready insights by strengthening the foundation of trust in modern analytics environments. Industry experts will share practical strategies, lessons learned, and emerging best practices for improving data reliability and transparency while enabling innovation at scale. Topics include:
- Why data quality continues to be a barrier to trusted analytics and AI, and how leading organizations are addressing it
- The role of metadata, lineage, and observability in creating context-rich, explainable insights
- Approaches for embedding governance into modern data architectures without slowing innovation
- Strategies for aligning technical data controls with business accountability and stewardship
Date: April 13, 2026
Time: 9:00 am PT
Fern Halper, Ph.D.