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DEA-C01 · Question #13

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3. Which solution will meet

The correct answer is C. Use Amazon Athena Federated Query to join the data from all data sources.. You can query these sources by using Federated Queries, which is a native feature of Athena. The other options may increase costs and operational overhead, as they use more than one service to achieve the same result. https://docs.aws.amazon.com/athena/latest/ug/connectors-availa

Data Ingestion and Transformation

Question

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3. Which solution will meet this requirement MOST cost-effectively?

Options

  • AUse an Amazon EMR provisioned cluster to read from all sources. Use Apache Spark to join the
  • BCopy the data from DynamoDB, Amazon RDS, and Amazon Redshift into Amazon S3. Run
  • CUse Amazon Athena Federated Query to join the data from all data sources.
  • DUse Redshift Spectrum to query data from DynamoDB, Amazon RDS, and Amazon S3 directly

How the community answered

(16 responses)
  • A
    13% (2)
  • C
    81% (13)
  • D
    6% (1)

Explanation

You can query these sources by using Federated Queries, which is a native feature of Athena. The other options may increase costs and operational overhead, as they use more than one service to achieve the same result. https://docs.aws.amazon.com/athena/latest/ug/connectors-available.html

Topics

#Athena Federated Query#Cross-source data joining#Cost optimization#Ad-hoc data analysis

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