DoubleCloud recently published a blog on ETL vs ELT, or Extract, Transform Load vs Extract, Load, Transform. The article introduces a new hybrid process called EtLT (Extract, transform, Load, Transform). While ETL is more resource-intensive and requires moving and transforming data before loading into a target system, ELT is considered more performant and scalable as it leverages the power of modern data stack to perform transformations close to the data. However, EtLT combines the best of both worlds by offering fast analytics while ensuring data quality for sensitive information in compliance with regulations. The process involves extracting raw data from various sources, performing a 'lite' transformation stage to remove or encrypt sensitive data, loading the prepared data into a Data Warehouse, and finally transforming and integrating all data sources within the warehouse. EtLT is most useful when an organization needs sub-second analytics with security concerns about the data requiring preload transformations.