A company runs proprietary ETL and aggregation logic, stores results in Amazon Redshift, and sells the resulting data to customers. Previously the company exported files from Redshift and sent them to customers via FTP. The company will use AWS Data Exchange to distribute the data and must verify customer identities before sharing. Customers also need access to the most recent published data. Which solution meets these needs with the LEAST operational overhead?

The correct answer leverages AWS Data Exchange's native integration with Amazon Redshift datashares. This approach allows the company to directly share live Redshift data with customers, ensuring they always have access to the most recent published data. Enabling subscription verification directly within Data Exchange meets the identity verification requirement. This solution has the least operational overhead because it avoids manual data exports or managing separate API infrastructure. Using AWS Data Exchange for APIs would introduce the overhead of building and maintaining an API Gateway and its integration with Redshift. Periodically exporting data to S3 would not provide access to the most recent published data instantly and adds operational overhead for managing exports. Publishing as an Open Data offering doesn't align with the requirement for subscription verification and controlled access.