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Answer: Use the SUPER data type to store the data in the Amazon Redshift table.
Amazon Redshift natively supports the `SUPER` data type, which is specifically designed to store and query semi-structured data formats such as JSON. By loading the JSON data directly into a `SUPER` column, the data engineer avoids the operational overhead of parsing and flattening the data beforehand using AWS Glue or AWS Lambda, making it the solution with the least effort.
Author: Ritesh Yadav
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A company needs to load customer data that comes from a third party into an Amazon Redshift data warehouse. The company stores order data and product data in the same data warehouse. The company wants to use the combined dataset to identify potential new customers. A data engineer notices that one of the fields in the source data includes values that are 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.
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