In large-scale ETL processes, why might an organization choose to implement incremental (or delta) loads instead of full loads?
- Full loads are faster and more efficient
- Full loads guarantee data accuracy
- Incremental loads are more straightforward to implement
- Incremental loads reduce data transfer and processing time
In large-scale ETL (Extract, Transform, Load) processes, organizations often choose incremental (or delta) loads over full loads to reduce data transfer and processing time. Incremental loads only transfer and process data that has changed since the last load, making them more efficient for managing large datasets and improving performance.
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