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An airline has been collecting metrics on flight activities for analytics. A recently completed proof of concept
demonstrates how the company provides insights to data analysts to improve on-time departures. The proof of concept
used objects in Amazon S3, which contained the metrics in .csv format, and used Amazon Athena for querying the data.
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An airline has .csv-formatted data stored in Amazon S3 with an AWS Glue Data Catalog. Data analysts want to join this
data with call center data stored in Amazon Redshift as part of a dally batch process. The Amazon Redshift cluster is
already under a heavy load. The solution must be managed, serverless, well-functioning, and minimize the load on the
existing Amazon Redshift cluster. The solution should also require minimal effort and development activity.