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Answer: Optimize the ETL scripts by using more efficient data transformations and parallel processing techniques, then monitor the performance using Amazon CloudWatch.
Optimizing the ETL scripts by using more efficient data transformations and parallel processing techniques can significantly improve the performance of the data pipeline. Monitoring the performance using Amazon CloudWatch allows for real-time adjustments and ensures that any improvements are sustained.
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You are tasked with maintaining a data pipeline that processes large volumes of financial data. The pipeline uses AWS Glue for ETL jobs and Amazon S3 for data storage. Recently, the performance of the pipeline has degraded, leading to delays in data processing. What steps would you take to diagnose and improve the performance of this pipeline?
A
Increase the number of nodes in the AWS Glue job and monitor the Amazon CloudWatch metrics for any improvements.
B
Reduce the frequency of the ETL jobs and use Amazon Macie to scan for sensitive data to optimize data handling.
C
Implement AWS CloudTrail to log all API calls and analyze the logs to identify bottlenecks.
D
Optimize the ETL scripts by using more efficient data transformations and parallel processing techniques, then monitor the performance using Amazon CloudWatch.
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