ETL—meaning extract, transform, load—is a data integration process that combines, cleans and organizes data from multiple sources into a single, consistent data set for storage in a data warehouse, data lake or other target system. ETL data pipelines provide the foundation for data analytics and machine learning workstreams.

ETL, which stands for “extract, transform, load,” are the three processes that move data from various sources to a unified repository—typically a data warehouse. It enables data analysis to provide actionable business information, effectively preparing data for analysis and business intelligence processes.