MLOps & Infrastructure · intermediate · concept 137 of 176

⚙️Data Pipelines & ETL

Automated workflows for collecting, cleaning, transforming, and loading data for ML. The unsexy but critical infrastructure that makes everything else possible. At big-data scale the same jobs run on engines like Spark over data lakes, while SQL over relational databases remains where most structured training data actually lives.