ELT vs ETL: Why not both?

The discussion of data ingestion practices, particularly ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform), highlights the distinct sequences and benefits of each method, with ETL being advantageous for on-premise solutions needing transformed data before storage and ELT excelling in cloud-based applications where raw data can be stored and transformed later. ETL, originating in the 1970s, is beneficial for regulatory compliance and consistent workflows but faces challenges with big data and diverse sources, while ELT, emerging with advancements in storage and cloud technology, offers flexibility and efficiency but risks data exposure and compliance issues. Kestra, a data orchestration tool, facilitates a hybrid approach by managing both ETL and ELT processes within a single solution, allowing for complex workflows and seamless integration with various data systems, thus offering organizations the ability to harness the strengths of both methods without the limitations of choosing one over the other.