Houston Data Management Association

TURNING DATA INTO TRUSTED AI-READY ASSETS

As organizations push to accelerate AI and advanced analytics, one challenge keeps surfacing: we don’t just need more data — we need better context around the data we already have.

In this upcoming DAMA Houston Tech Talk, we’ll explore how strong metadata, lineage, and governance foundations make data more discoverable, understandable, and trustworthy — all critical ingredients for successful AI initiatives.

This session will focus on practical ways teams can improve data context across their analytics ecosystem, helping both technical and business users move faster with more confidence.

WHAT YOU'LL LEARN

Attendees will walk away with a clearer understanding of how to:

• Make BI and analytics more trustworthy by surfacing business and technical metadata directly where data is consumed
• Trace data from source to dashboard using cross-system lineage to support impact analysis, troubleshooting, and transparency
• Improve data discovery with modern, search-driven approaches that help users quickly find the right datasets and assets
• Standardize and govern metrics so teams are aligned on definitions that power reporting and decision-making
• Operationalize data products within domains to balance ownership, quality, and usability
• Prepare for semantic and AI use cases by strengthening the underlying data context layer

This session emphasizes the data management practices and architectural patterns that enable organizations to scale analytics and AI responsibly, and how data cataloging tools such as Atlan are addressing this need.

WHO SHOULD ATTEND

This talk is ideal for:

• Data governance and data management professionals
• Analytics and BI leaders
• Data engineers and architects
• Business intelligence developers
• Anyone involved in making data more usable, reliable, and AI-ready

Whether you're early in your governance journey or scaling enterprise AI initiatives, this session will provide actionable insight into building a stronger foundation for trusted data.