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Upcoming Webinars

TDWI On-Demand Webinars on Data Management, Analytics, & AI


On Demand

When Automation Meets AI Readiness: Building a Trusted Data Foundation

Join TDWI Research Fellow Donald Farmer and experts from Precisely as we examine how automation of data and processes, especially in SAP environments, directly addresses the readiness challenges that most often derail AI at scale.

Donald Farmer


Proactive Data Security and Governance in the Era of AI

Cal Al-Dhubaib, TDWI Research Fellow, will moderate a conversation with Travis Kaufman and Nikita Gupta from Snowflake on how organizations can design secure, scalable AI architectures that protect sensitive data while enabling innovation.

Cal Al-Dhubaib


Building Agentic and Generative AI: Enterprise Data Foundations and Applications - Insights from TDWI's Q1 Blueprint Report

In this webinar, Fern Halper, Ph.D., VP of research at TDWI, will share findings from TDWI’s new Blueprint Report: Building Agentic and Generative AI: Enterprise Data Foundations & Applications.

Fern Halper, Ph.D.


Expert Panel: Breaking Data Silos: Enabling Access and Interoperability for AI and Analytics

In this expert panel webinar, we’ll explore strategies and technologies that enable interoperability across distributed data environments.

Deanne Larson, Ph.D., DM, CBIP


Future-Proofing Business with Trusted Data: How Improved Data Integrity Holds the Key to AI and Analytics

This session explores how trusted, well-governed, and context-rich data is a critical enabler of modern enterprises.

Prashanth Southekal, Ph.D.


Expert Panel: The Great Data Stack Reset: New Architectures, New Priorities in 2026

Join TDWI research fellow Donald Farmer and industry experts from Reltio as they examine how organizations are redesigning their data architectures to meet 2026 realities.

Donald Farmer


The State of Data Quality

The State of Data Quality webinar will outline what it takes to achieve sound data quality for modern AI demands. This includes the organizational structures, skills, and governance models required to manage data quality at scale, as well as the technical underpinnings such as pipelines, architectures, and tooling that enable safe, effective AI deployment.

Fern Halper, Ph.D.


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