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HBO and The Ringer's Bill Simmons hosts the most downloaded sports podcast of all time, with a rotating crew of celebrities, athletes, and media staples, as well as mainstays like Cousin Sal, Joe House, and a slew of other friends and family members who always happen to be suspiciously available.
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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
Register for free to be part of the next live session: https://bit.ly/3XB3A8b
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