ELT stands for Extract, Load, and Transform, which represents a modern approach to data processing in data engineering and analytics. In this methodology, data is first extracted from various source systems, such as databases or APIs, and then loaded into a data warehouse or data lake. Once the data is in the destination system, transformations are performed according to the analysis needs.
This contrasts with the traditional ETL (Extract, Transform, Load) process, where data is transformed before it is loaded into the destination. The ELT approach is particularly effective when dealing with large volumes of data and complex data transformations, as it leverages the computing power of the data warehouse to perform transformations after the loading process. This method can lead to more flexible data usage, as raw data is readily available for various analyses.
Other options presented do not accurately reflect the commonly accepted definitions in data processing, with terms like "Launch," "Transfer," "List," and "Test" not aligning with the standard understanding of data handling methodologies.