👨‍💻 Week 5: How dlt Works — Behind the Scenes This week we step back from coding and learn the theory of dlt. Every pipeline you run goes through 3 simple phases: ✅ Extract – pull raw data from your source ✅ Normalize – detect schema & flatten nested data ✅ Load – migrate it into your destination (DuckDB, BigQuery, etc.) ✨ Why it matters: Understanding these phases explains how dlt handles schema changes, incremental loads, and migrations — so you can focus on what data you need, not the plumbing. 📦 Repo – Week 5: [https://github.com/1997mahadi/Data-Engineering-with-dlt/tree/main/week-05_how-dlt-works] LinkedIn:https://www.linkedin.com/posts/mahadi-nagassou-850a87254_dataengineering-python-dlt-activity-7369681709837049861-hRP2?utm_medium=ios_app&rcm=ACoAAD7Os_wBFAAF1g7fKTnQFhj7G6uWNYukvWw&utm_source=social_share_send&utm_campaign=copy_link