An ETL process is optimized for small datasets but struggles with larger datasets. What adjustments can be made to optimize it for handling large data volumes?

  • Implementing row-by-row processing
  • Increasing the frequency of data loads
  • Removing data validation steps
  • Using bulk loading techniques
To optimize an ETL process for handling large data volumes, using bulk loading techniques is crucial. Bulk loading minimizes the overhead associated with processing individual records and allows for faster data transfer and loading, improving overall performance.
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