ETL stands for extract, transform, and load and is a traditionally accepted way for organizations to combine data from multiple systems into a single database, data store, data warehouse, or data lake. ETL can be used to store legacy data, or—as is more typical today—aggregate data to analyze and drive business decisions.

Extract, transform, and load (ETL) is the process data-driven organizations use to gather data from multiple sources and then bring it together to support discovery, reporting, analysis, and decision-making.