From Data Models to Knowledge Graphs: Building an AI-Ready Semantic Model

Watch this on-demand webinar to learn how existing logical data models, business glossaries, and metadata can provide the foundation for AI-ready semantic architecture. In this session, Jon Harrison, Technical Presales at ER/Studio, demystifies the terminology around taxonomies, ontologies, knowledge graphs, and semantic models and explains how these concepts relate to traditional enterprise data modeling. You’ll also see how an Enterprise Logical Data Model can represent important business concepts and relationships, providing a reusable semantic foundation for both enterprise data assets and AI. You’ll Learn ✅ The differences between taxonomies, ontologies, knowledge graphs, and semantic models ✅ How logical data models already capture important semantic information ✅ Where additional semantic precision may be required ✅ How Enterprise Logical Data Models provide a model of the business ✅ How metadata and relationships give AI better business context ✅ How ER/Studio can help build and manage an AI-ready semantic model Whether you are a data architect, modeler, governance professional, metadata leader, or AI stakeholder, this session provides a practical roadmap for connecting established data architecture with emerging semantic AI requirements. Learn more about ER/Studio: https://utm.io/utldA Request a demo or contact our team: https://utm.io/utldE