KB: Data ELT vs ETL
ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are both data integration processes used for data management, typically within data warehouses, but they differ in the order of steps and their specific use cases. ETL (Extract, Transform, Load) Order : Data is first extracted from source systems, then transformed (cleaned, formatted, aggregated, etc.), and finally loaded into the target data warehouse or data store. Transformation Location : Data is transformed in a staging area or in an ETL tool before it reaches the target. Use Case : Traditional data warehouses, where transformations are needed to standardize data before storage. Often suitable for environments with limited storage or compute power. Pros : Ensures data is clean and structured upon arrival in the target system. Good for legacy systems where transformations need to happen outside the data warehouse. Cons : Can be time-consuming and resource-intensive, especially for large datasets. Transformation...