Extract, Transform, Load (ETL) refers to a process in database usage and especially in data warehousing that performs data extraction, data transformation and data loading.
ETL In computing, Extract, Transform, Load (ETL) refers to a process in database usage and especially in data warehousing that performs:
- Data extraction – extracts data from homogeneous or heterogeneous data sources
- Data transformation – transforms the data for storing it in the proper format or structure for the purposes of querying and analysis
- Data loading – loads it into the final target (database, more specifically, operational data store, data mart, or data warehouse)
Since the data extraction takes time, it is common to execute the three phases in parallel. While the data is being extracted, another transformation process executes. It processes the already received data and prepares it for loading. As soon as there is some data ready to be loaded into the target, the data loading kicks off without waiting for the completion of the previous phases.
ETL systems commonly integrate data from multiple applications (systems), typically developed and supported by different vendors or hosted on separate computer hardware. The disparate systems containing the original data are frequently managed and operated by different employees. For example, a cost accounting system may combine data from payroll, sales, and purchasing.