Organizations are moving quickly to adopt AI, but even the most advanced AI initiatives depend on something much more fundamental: trusted, well-understood data.
When data is spread across multiple platforms, business definitions are inconsistent, relationships are undocumented, or critical context exists only as tribal knowledge, AI may be able to access the data—but that doesn’t mean it can interpret it correctly.
Join Angela Eberle, Senior Solutions Architect, ER/Studio, on September 10 for a practical webinar exploring five questions every organization should be able to answer before scaling AI initiatives.
Through practical examples and a live ER/Studio demonstration, Angela will show how data modeling, business definitions, relationships, mappings, and metadata can provide the foundation AI initiatives need.
The session will also highlight new capabilities in ER/Studio 21.1 designed to help organizations better leverage their data architecture and metadata for AI.
You’ll Learn How To:
