What is the function of ETL in data processing?

The function of ETL in data processing is primarily to extract, transform, and load data from multiple sources. This process is crucial for moving data between systems and ensuring it is in a usable format for analysis or reporting.

During the extraction phase, ETL gathers data from various sources, which may include databases, cloud storage, files, or external APIs. The transformation phase involves cleansing and converting this data into a format that is appropriate for analysis; this can include operations like filtering, aggregating, or changing data types. Finally, during the loading phase, the processed data is loaded into a target system, such as a data warehouse or a database, where it can be accessed for querying or further analysis.

This comprehensive approach is vital for organizations that rely on multiple data sources to generate insights and make data-driven decisions. Each of the other choices does not encapsulate the complete process or focus solely on the diverse functionalities that the ETL process serves.