ETL (extract, transform, load) transforms the data at the staging area and redact sensitive data before loading it into the target device. Transformations have a higher latency, which can be reduced with streaming ETL. The ETL pipeline can optimize uptime and can be used to manage edge cases. On the other hand, ELT (extract, load, transform) loads the raw data directly into the target device, where the transformation takes place. In this pipeline, the latency is reduced in cases where there are little or no transformations. Edge case solutions that are generic will result in downtime or increased latency in ELT.