Powering Up Your Power BI Development Workflow with Microsoft Fabric Notebooks

on YouTube ↗52m

" summary

Demonstrates that Microsoft Fabric Notebooks give zero setup access to Python/PySpark and built‑in tools so Power BI workflows run faster: uses pandas, pyspark.pandas, the data Wrangler low‑code UI, GitHub/Edge CoPilot, and ydata profiling to produce a full data quality report in about five lines of code. Uses semantic link to pull measures and tables from a semantic model in roughly ten lines, trains an ML experiment and makes predictions in the same notebook — the demos run end‑to‑end.

AI-written summary · about

" chapters (11)

1. 0:00Introduction to fabric
2. 2:57Evolving development roles
3. 6:32Notebook interface overview
4. 13:42Apache spark explained
5. 19:02Data frames and libraries
6. 21:54Python and pandas hands-on
7. 29:49PySpark and distributed data
8. 34:26Data wrangler and profiling
9. 38:52Co-pilot assistance
10. 42:12Semantic link deep dive
11. 47:31Conclusion and Q&A

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