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What is ELT? 

ELT stands for Extract, Load, and Transform of data. ELT is a process whereby a system first extracts data from various sources and then loaded as-is into a data warehouse. Finally, the data is transformed directly in the data warehouse (normally using SQL) into a standardized format suitable for analysis/ML. Compared to the traditional ETL process, where data is transformed in an external engine, like Spark, before it is loaded into the warehouse, in ELT, the data is transformed in-place using SQL in the data warehouse.

Where is ELT important in ML systems?

ELT is often found in feature pipelines that extract data from existing data stores, load it into a data warehouse or feature store, and then transform the raw data into features in the data warehouse or feature store.

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