What does ELT stand for?

ELT stands for Extract, Load, and Transform. This term is commonly used in data processing and data integration workflows. In the ELT process, data is first extracted from various sources, whether it be databases, files, or application interfaces. After extraction, the data is loaded into a data warehouse or data lake before any transformation or processing occurs.

This approach differs from the traditional ETL (Extract, Transform, Load) process, where data is transformed before being loaded into the target storage system. One of the key advantages of ELT is that it leverages the power of the target system, often allowing for faster processing and enabling more complex queries on the raw data after it has been loaded.

The other options do not represent the correct sequence or components involved in the ELT process. For instance, "Extract, list, and transform" introduces "list," which is not a relevant operation in this context. "Extract, load, and test" inaccurately includes testing as a primary step. "Engage, load, and transform" does not relate to standard data engineering terminology. Therefore, knowing that ELT specifically emphasizes extracting data, loading it into a storage solution, and then transforming it allows for better understanding of modern data processing strategies