DataEngBytes 2023 - MEL-T2-02 - Vikas Rajput
summary
Data engineering shifts from slow, centralized conformance toward fast, iterative AI-assisted loops that cut months of dev time to days by handing routine code and integration tasks to GitHub Copilot while keeping engineers in the decision loop. A unified stack like Microsoft Fabric shows a working build: embedded model ops, governance hooks and content-generation paths that accelerate delivery. Expect to define guardrails, bake responsible‑AI checks into pipelines, and replicate stacks across vendors rather than rebuild every component.
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chapters (9)
- 0:00AI and data engineering intro
- 1:26Human exploration history
- 5:18Data platforms challenge
- 8:54AI for data engineers: build vs buy
- 13:29From autopilot to co-pilot
- 15:55AI loops possibilities
- 18:24AI guardrails and controls
- 20:32GitHub Copilot & Microsoft Fabric demos
- 22:58Closing & Q&A
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