This document discusses ETL patterns in the cloud using Azure Data Factory. It covers topics like ETL vs ELT, scaling ETL in the cloud, handling flexible schemas, and using ADF for orchestration. Key points include staging data in low-cost storage before processing, using ADF's integration runtime to process data both on-premises and in the cloud, and building resilient data flows that can handle schema drift.