This infographic explains why ELT is better suited than ETL for modern data integration. In ETL, transformations happen before loading, so when source schemas or business requirements change, pipelines often break and must be rewritten, consuming engineering hours. In ELT, data is extracted and loaded first, with transformations handled in the destination, allowing pipelines to keep running even if transformations fail. Analysts can then adjust SQL in the warehouse to meet new requirements. By decoupling loading from transformation, ELT provides flexibility, reduces rework, and empowers faster, more reliable insights.

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