A data engineer is loading third-party customer data into Amazon Redshift. One source field contains JSON-formatted values. To load the JSON into the data warehouse with the least effort, what should the engineer do?

The SUPER data type in Amazon Redshift is designed to store semi-structured data, including JSON, directly within a table. This allows for direct ingestion of JSON-formatted values with minimal transformation effort, as Redshift can query and process this data natively using PartiQL. Using AWS Glue to flatten the JSON data would involve creating and running an ETL job, which is more effort than directly loading into a SUPER column. Storing the JSON in Amazon S3 and querying with Athena is a valid approach for semi-structured data but doesn't load it into Redshift, which is the stated goal. Using an AWS Lambda function to flatten the JSON and store it in S3 also introduces additional development and operational overhead, again not directly loading into Redshift.