Question:
A company is running an application in the AWS Cloud. The application collects and stores a large amount of unstructured data in an Amazon S3 bucket. The S3 bucket contains several terabytes of data and uses the S3 Standard storage class. The data increases in size by several gigabytes every day. The company needs to query and analyze the data. The company does not access data that is more than 1 year old. However, the company must retain all the data indefinitely for compliance reasons. Which solution will meet these requirements MOST cost-effectively? A. Use S3 Select to query the data. Create an S3 Lifecycle policy to transition data that is more than 1 year old to S3 Glacier Deep Archive. B. Use Amazon Redshift Spectrum to query the data. Create an S3 Lifecycle policy to transition data that is more than 1 year old 10 S3 Glacier Deep Archive. C. Use an AWS Glue Data Catalog and Amazon Athena to query the data. Create an S3 Lifecycle policy to transition data that is more than 1 year old to S3 Glacier Deep Archive. D. Use Amazon Redshift Spectrum to query the data. Create an S3 Lifecycle policy to transition data that is more than 1 year old to S3 Intelligent-Tiering.
Author: Jorge SoroceAnswer:
Use an AWS Glue Data Catalog and Amazon Athena to query the data. Create an S3 Lifecycle policy to transition data that is more than 1 year old to S3 Glacier Deep Archive.
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