Raj Kamath interviewed

on YouTube ↗05m

" summary

Claims that practical adoption starts with data strategy and platform upfront and that most real stacks end up as a hybrid of commercial and open source, not one or the other. Notes that some vendor pairs plug together out of the box while others require custom engineering to integrate to deliver a usable data asset. Recommends treating the architecture as a living roadmap, refreshing priorities as needs shift, and cites rising demand for machine learning and AI as the current driver of new capabilities.

AI-written summary · about

" chapters (5)

1. 0:00How do you build a data stack
2. 1:19Do you have to make special connections
3. 2:23Hybrid approach
4. 3:03Upfront planning
5. 3:49What is a standard

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