Scenario: During ETL testing, you notice that the loading phase is taking longer than expected, impacting the data refresh schedule. What strategies can you employ to optimize the ETL process and improve loading speed?
- Data partitioning
- Incremental loading
- Indexing
- Parallel processing
Implementing data partitioning involves dividing large datasets into smaller, manageable partitions based on specific criteria (e.g., date ranges, geographical regions). By distributing data across multiple partitions, you can parallelize the loading process and improve loading speed. Additionally, data partitioning facilitates easier data maintenance and enhances query performance. This strategy helps optimize the ETL process by reducing the load on individual components and improving overall system efficiency, thereby addressing the issue of prolonged loading phases.
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