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) tools allow organizations to extract data from multiple sources, transform the data into a usable state, and load that data into a data warehouse or data lake. From there, the data can be used for all sorts of business purposes, like data analytics, data visualization or machine learning.