In ETL (extract, transform, load), data is transformed in an intermediate engine before it is loaded into the destination. In ELT (extract, load, transform), it is loaded raw first and transformed in the destination by using its compute.
In DP-900: copying raw data into a lakehouse and transforming it later with Spark notebooks is ELT. Pipelines are orchestrated with Azure Data Factory or Data Factory in Microsoft Fabric.
ETL vs. ELT is a concept that can show up on the exam. Check the full guide to see it in context.