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You are designing a data pipeline for a retail company that needs to analyze sales data. The pipeline must extract data from Amazon S3, transform it using AWS Glue, and load it into Amazon Redshift. How would you configure this pipeline to handle large volumes of data and ensure efficient processing?
A
Use Amazon S3 event notifications to trigger AWS Glue jobs directly for data transformation and loading into Redshift.
B
Set up a cron job on an EC2 instance to periodically check S3 for new files and then trigger Glue jobs.
C
Manually run AWS Glue jobs to extract data from S3, transform it, and then load it into Redshift.
D
Use Amazon SQS to queue S3 events and have Glue jobs poll the queue for processing.