Fantastic Data and Where to Find It

on YouTube ↗34m

" summary

Overview of data roles, technologies and practical patterns used at Clarity.AI, with concrete code examples from the past two years. Presents sustainable, production-ready Python data engineering using Pandas, Dask and Airflow to build scalable automated ETL pipelines.

AI-written summary · about

" chapters (11)

1. 0:00Welcome
2. 2:29Data roles
3. 7:51Key data technologies
4. 9:14ETL practical example
5. 12:05Refactoring messy code
6. 15:43ETL testing importance
7. 17:07Property-based testing
8. 18:32Data validation in processes
9. 20:59Notebooks and auto-validation
10. 23:28ETL orchestrators
11. 27:01Final conclusions

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