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Answer: AWS Glue ETL job to convert CSV to Redshift-compatible format.
The correct answer is A. Using AWS Glue to create a scheduled ETL job allows for the automated transformation of CSV files into a format compatible with Amazon Redshift, thus enabling the COTS application to process the data. This solution requires the least operational overhead because AWS Glue is a fully managed service that simplifies the process of extracting, transforming, and loading data. It eliminates the need for managing servers or complex coding, unlike the other options provided.
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A company's legacy application generates CSV-formatted data stored in Amazon S3. The new COTS application requires data in formats compatible with Amazon Redshift or Amazon S3, but it does not support CSV. The legacy application cannot be altered to change its output format. What is the least operationally intensive solution to enable the COTS application to utilize the legacy data?
A
AWS Glue ETL job to convert CSV to Redshift-compatible format.
B
Python script on EC2 converting CSV to SQL, scheduled via cron, with outputs to S3.
C
AWS Lambda with DynamoDB, triggered by S3 events, for CSV to DynamoDB ETL.
D
Amazon EventBridge to run EMR clusters weekly, processing CSV to Redshift.