What is a common use case for AWS Athena?

AWS Athena is a serverless interactive query service that allows users to analyze large datasets stored in Amazon S3 using standard SQL. This capability makes it particularly valuable for cases where there is a need to analyze data without having to set up and manage any underlying infrastructure. Since Athena supports querying data in various formats such as CSV, JSON, ORC, and Parquet, it is highly versatile for data analysis tasks.

When dealing with large datasets, such as logs or large tables, users can leverage Athena to quickly run SQL queries, gaining insights without the need for complex data processing pipelines or extensive ETL processes. This efficiency and simplicity suit a variety of analytics solutions, making Athena a preferred choice for data analysis directly from S3.

Other options, while they represent valid use cases for different AWS services, do not align with the primary function of Athena. For example, analyzing real-time streaming data typically falls under the capabilities of AWS services like Kinesis. Running machine learning models is generally handled by services like Amazon SageMaker, and deploying and managing server infrastructures relates more to services like Amazon EC2 or AWS Elastic Beanstalk. Thus, the essence of Athena is encapsulated in its ability to query large datasets in a straightforward manner using SQL.