You Can’t Scale Without Scalable Processes!
Last week, we were 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
Catch the full replay: https://mavenanalytics.io/mavens-of-data/vector-dbs-knowledge-graphs-data-fabric-and-why-process-still-rules
Happy Learning!
Maven Analytics is an award-winning learning platform where individuals and teams build new skills, showcase work, and connect with experts around the world.
We’ve helped 2M+ people build job-ready data literacy & AI skills, master tools like Excel, SQL, Power BI, Tableau and Python, and build the foundation for successful careers.
Start building life-changing skills for FREE at mavenanalytics.io.
Source
