← Data Engineering & ETL learning pathData Engineering & ETL · Module 3 of 10
Transformations
Clean, join and reshape data into useful models.
📖 Key ideas
- Cleaning: types, nulls, duplicates, standard formats.
- Joining sources: customers + orders.
- Aggregating: daily sales per store.
- Business logic: revenue, margins, segments.
- Tools: SQL, dbt, Spark, pandas.
💡 Real-life example: Transformation is turning raw vegetables into a cooked meal ready to serve.
dbtSQL-based transformation tool
DeduplicationRemoving duplicate records
Business logicRules defining metrics
Staging modelLightly cleaned source data