ETLT (extract-transform-load-transform) combines ETL and ELT: it performs simple transformations before loading data, then applies complex business transformations after loading, where Snowflake compute resources can process them. section 11.3
A typical ETLT flow separates responsibilities across pipeline stages:
- Extract data from operational databases or files. section 11.0
- Apply simple transformations before loading the data. section 11.3
- Load the prepared data into Snowflake. section 11.3
- Perform complex business transformations inside Snowflake using its compute resources. section 11.3
Organize intermediate outputs into layers such as extraction, staging, data warehouse, and presentation. These layers are optional, but separating flows by layer helps keep pipeline dependencies orderly; outputs may be tables, materialized views, dynamic tables, or views. section 11.3
