ETL is a process that extracts the data from different source systems, then transforms the data (like applying calculations, concatenations, etc.) and finally loads the data into the Data Warehouse system. Full form of ETL is Extract, Transform and Load.

ETL stands for Extract, Transform, Load. It is a process used in data integration to extract data from various sources, transform it into a consistent format, and load it into a target database or data warehouse. The goal of ETL is to ensure that data from different sources can be combined and analyzed effectively.

The abbreviation ETL stands for Extract, Transform, and Load, addressing the three phases of data handling. In the extraction stage, data is accumulated from different sources like data sets, records, and APIs. Then, in the transformation stage, the data goes through cleaning, standardization, and aggregation to guarantee consistency and accuracy.

ETL is a series of steps that enable organizations to collect data from various sources, transform it into a consistent format, and load it into a destination system, typically a data warehouse or a database, where it can be analyzed and used for business intelligence, reporting, and decision-making purposes.