Listen to "Making Sense of Ontologies, Knowledge Graphs, and Semantic Layers" on Spreaker.
In Part 2 of our three-part series on building trusted AI with enterprise data, AI Data Bites (Powered by Denodo) explores why connecting AI to enterprise data is no longer enough. For AI to deliver reliable answers and informed decisions, it needs to understand the business meaning, relationships, and context behind the data.
Host Neha Gurudatt is joined by Kevin Bohan, Director of Product Marketing at Denodo, to unpack the differences between ontologies, knowledge graphs, and semantic layers, and explain how they work together to provide trusted business context for analytics and AI.
Topics Covered:
- Why data access alone isn't enough for trusted enterprise AI
- What ontologies, knowledge graphs, and semantic layers mean and how they differ
- Why AI needs business definitions, relationships, and governance to deliver reliable answers
- How AI is bringing renewed importance to semantic context and connected knowledge
- Why business context needs to extend across distributed enterprise data environments
- How data products become more discoverable, understandable, trusted, governed, and reusable
- How organizations can bring hidden business context to the surface with semantic and graph-based capabilities
Why This Episode Matters
As enterprises move from dashboards to AI copilots and autonomous agents, the ability to access data is only part of the equation. AI also needs to understand what that data represents, how it connects, and which business rules and policies apply.
Discover why creating a trusted layer of business meaning across distributed data environments is becoming essential to building AI-ready enterprises.
🎧 Join us for this episode of AI Data Bites (Powered by Denodo) to unlock the power of model neutrality.
