A company has both structured and unstructured data in S3 and needs to run SQL queries over it. Which solution requires the least amount of work to enable SQL querying?

The correct answer is to use AWS Glue to create a data catalog for the S3 data and query it directly with Amazon Athena. This is the most efficient solution because Athena allows direct SQL querying of data in S3 without needing to move or transform the data beforehand. AWS Glue automatically crawls the S3 data, infers schemas, and populates the Data Catalog, making the data queryable by Athena. Incorrect options: Using AWS Data Pipeline to transform and load data into Amazon RDS requires significant ETL work and data movement, which is not the "least amount of work." Using AWS Batch for ETL and Amazon Aurora also involves substantial ETL and managing a relational database, adding complexity. Using AWS Lambda for transformation and Amazon Kinesis Data Analytics for queries is designed for streaming data and would be overly complex and unnecessary for static data in S3.