Which tool serves as a visual data preparation solution that helps clean and normalize data for analytics and machine learning?

AWS Glue DataBrew is designed specifically to assist data analysts and data scientists in the process of data preparation by providing a visual interface. This tool allows users to perform data cleaning, normalization, and transformation tasks without needing to write code. DataBrew offers over 250 built-in transformations, making it easier to prepare data for analytics and machine learning applications.

The ability to visualize data and apply transformations through simple clicks and drag-and-drop functionality enables users to understand their data better and optimize it for modeling. This is particularly valuable in the context of machine learning, where clean and well-structured data is crucial for building effective models.

Other tools in the options provided have different primary functions. Amazon SageMaker focuses on building, training, and deploying machine learning models, while Amazon Redshift is a data warehouse service designed for analytics and data storage, and Amazon Athena is primarily an interactive query service for analyzing data in Amazon S3 using SQL. These tools do not offer the specific visual data preparation capabilities that AWS Glue DataBrew provides.