Which AWS service helps organizations manage and analyze large datasets for machine learning?

AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easier to prepare data for analytics and machine learning. It automates much of the heavy lifting involved in data preparation, such as data discovery, cleaning, and transformation. This capability is crucial for organizations that need to manage and analyze large datasets, as it seamlessly integrates with other AWS services and allows for flexible data handling.

By providing a serverless environment, AWS Glue enables organizations to scale their operations efficiently without the need to manage infrastructure, optimizing the data preparation process. Moreover, it facilitates the creation of data catalogs, which improve data accessibility and usability for machine learning applications, ensuring that data scientists and analysts have the necessary resources at their disposal to build models based on high-quality data.

The other options serve different purposes; for example, AWS Lambda is a compute service that runs code in response to events and does not specialize in data management or analytics. AWS S3 is primarily a storage service, providing a scalable solution for storing large datasets but doesn't offer specific management or analysis capabilities. AWS Athena is an interactive query service that allows users to analyze data directly in S3 using SQL but does not handle ETL processes or data preparation as comprehensively as AWS Glue