ELT is a data processing approach where data is first extracted from various sources and loaded into a data repository or data lake. Unlike ETL (Extract, Transform, Load), where transformation occurs before loading, ELT involves transforming the data after it has been loaded into the destination system. This method leverages the processing power of modern data warehouses and data lakes to perform transformations more efficiently at scale. ELT is particularly useful for handling large volumes of data and complex transformations, as it allows for flexible, on-demand processing and reduces the need for pre-transformation. It is commonly used in modern data architectures to streamline data integration and analytics workflows.