Expert Panel: Data Observability and Reliability at Scale
Webinar Speaker: Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics
Date: Monday, September 28, 2026
Time: 9:00 a.m. PT / 12:00 p.m. ET
Organizations are relying on data more than ever to power analytics, AI, and agents. However, as data environments become increasingly distributed and complex, maintaining trusted, reliable, and continuously available data has become a significant challenge.
TDWI research consistently finds that data quality remains one of the top obstacles to successful AI and analytics initiatives. Without confidence in the accuracy, completeness, timeliness, and reliability of data, organizations increase operational risk, reduce trust in AI outputs, and limit their ability to scale data-driven initiatives. The problem has increased with the growing use of unstructured data.
Join TDWI's VP of Research, Fern Halper, Ph.D., together with industry experts as they discuss how organizations are building data observability and reliability across modern data ecosystems and the practices that support trusted data for AI and analytics.
Topics include:
- The state of data observability today and why it has become essential for analytics, AI, and agents
- Best practices for monitoring data quality (across data types), detecting anomalies, and improving pipeline reliability
- Building end-to-end observability across modern data architectures
- How data observability strengthens trust in AI, reduces operational risk, and supports business-critical decision-making /li>