Data Extraction and ETL Salary and Insights for 2025

What is ETL?

Extract, transform, load (ETL) is a tried-and-tested data integration process for collecting data from different source systems, cleaning and processing it, and loading it into a data warehouse or data lake (or other downstream ‘target’ data store). By the mid-1970s, as these databases gained popularity, the term ETL was used to define a process to extract, transform and load data for computation and analysis in order to become the primary way to prepare data for data warehouse projects.

ETL supports the primary workstreams in data analytics and machine learning through a series of business rules, which prep the data into a form that fits the specific need, whether it’s a monthly reporting requirement or more advanced analytics that can help optimise back-end processes or end-user experiences.

An organisation frequently uses ETL to:

• Extract data from legacy systems Cleanse the data to improve data quality and establish consistency
• Load data into a target database