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A data analyst is designing a solution to interactively query datasets with SQL using a JDBC connection. Users will join data stored in Amazon S3 in Apache ORC format with data stored in Amazon OpenSearch Service (Amazon Elasticsearch Service) and Amazon Aurora MySQL.
Which solution will provide the MOST up-to-date results?

A. Use AWS Glue jobs to ETL data from Amazon ES and Aurora MySQL to Amazon S3. Query the data with Amazon Athena.

B. Use Amazon DMS to stream data from Amazon ES and Aurora MySQL to Amazon Redshift. Query the data with Amazon Redshift.

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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.

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