In this episode, we’re joined by Terry Dorsey, Senior Data Architect & Evangelist at Denodo, to unpack the conceptual differences between terms like data fabrics, vector databases, and knowledge graphs, and remind you not to forget about the importance of structured data in this new AI-native world!

What You'll Learn:

• The difference between data fabrics, vector databases, and knowledge graphs — and the pros and cons

• Why organizing and managing data is still the hardest part of any AI project (and how process design plays a critical role)

• Why structured data and schemas are still crucial in the age of LLMs and embeddings

• How knowledge graphs help model context, relationships, and “episodic memory” more completely than other approaches
  
  

If you’ve ever wondered about different data and AI terms, here’s a great glossary to check out from Denodo: https://www.denodo.com/en/glossary