Typically, ELT takes place during business hours when traffic on the source systems and the data warehouse is at its peak and consumers are waiting to use the data for analysis or otherwise. In this step, the transformed data is moved from the staging area into a data storage area, such as a data warehouse or data lake.įor most organizations, the data loading process is automated, well-defined, continuous and batch-driven.
That said, it is more typically used with unstructured data. The data set can consist of many data types and come from virtually any structured or unstructured source, including but not limited to:
Extractĭuring data extraction, data is copied or exported from source locations to a staging area. How ELT worksĮLT consists of three primary stages Extract, Load, and Transform. While similar to ETL, ELT is a fundamentally different approach to data pre-processing which has only more recently gained adoption with the transition to cloud environments. This process moves raw data from a source system to a destination resource, such as a data warehouse. What is ELT?ĮLT, which stands for “Extract, Load, Transform,” is another type of data integration process, similar to its counterpart ETL, “Extract, Transform, Load”. ELT is a process that extracts, loads, and transforms data from multiple sources to a data warehouse or other unified data repository.
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