A company has 100 GB of CSV log files in S3. SQL developers need to query the data, create graphs for visualization, and automatically store metadata from the CSVs with minimal effort. Which combination of steps (choose three) meets these needs with the least work?

This solution leverages serverless services for minimal operational overhead. Amazon Athena allows SQL developers to directly query the CSV files in S3 without needing to load them into a database, making it ideal for ad-hoc queries on existing S3 data. The AWS Glue Data Catalog automatically discovers and stores metadata (schema, data types) for the CSV files, making them queryable by Athena and other services, fulfilling the "automatically store metadata" requirement with minimal effort. Amazon QuickSight can then connect to Athena to visualize the queried data, creating graphs for visualization. Incorrect options: AWS X-Ray is for tracing requests, not for data filtering and visualization. Amazon Redshift is a data warehouse requiring data loading and management, which is more work than querying directly from S3 with Athena. Amazon DynamoDB is a NoSQL database, not designed for storing metadata for S3 CSV files in this context; AWS Glue Data Catalog is the purpose-built solution.