AWS Certified Data Engineer - Associate DEA-C01Demo

By Amazon · Question Mode

QuestionQ261

Data Ingestion and Transformation

A company must load customer data received from a third party into an Amazon Redshift data warehouse. The company keeps order data and product data in that same warehouse. It wants to use the combined dataset to identify potential new customers.

A data engineer observes that one field in the source data contains values in JSON format.

How should the data engineer load the JSON data into the data warehouse with the LEAST effort?

  • A Use the SUPER data type to store the data in the Amazon Redshift table.
  • B Use AWS Glue to flatten the JSON data and ingest it into the Amazon Redshift table.
  • C Use Amazon S3 to store the JSON data. Use Amazon Athena to query the data.
  • D Use an AWS Lambda function to flatten the JSON data. Store the data in Amazon S3.
Explanation

Amazon Redshift’s SUPER data type natively stores semi-structured JSON and supports loading JSON into SUPER columns. This avoids the extra transformation and operational work required to flatten the JSON with AWS Glue or Lambda, while keeping the data in the Redshift warehouse for combined analysis.

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