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.
Which solution meets these requirements?

A. Unload the call center data from Amazon Redshift to Amazon S3 using an AWS Lambda function. Perform the join with AWS Glue ETL scripts.

B. Export the call center data from Amazon Redshift using a Python shell in AWS Glue. Perform the join with AWS Glue ETL scripts.

C. Create an external table using Amazon Redshift Spectrum for the call center data and perform the join with Amazon Redshift.

D. Export the call center data from Amazon Redshift to Amazon EMR using Apache Sqoop. Perform the join with Apache Hive.








 

Suggested Answer: C

Community Answer: C




This question is in DAS-C01 AWS Certified Data Analytics – Specialty Exam
For getting AWS Certified Data Analytics – Specialty Certificate



Disclaimers:
The website is not related to, affiliated with, endorsed or authorized by Amazon.
Trademarks, certification & product names are used for reference only and belong to Amazon.
The website does not contain actual questions and answers from Amazon's Certification Exam.