A data engineer must create an enterprise data catalog covering S3 buckets and RDS databases, and the catalog must include storage format metadata. Which solution requires the least effort?

The correct answer is to use an AWS Glue crawler with classifiers because this approach automates the discovery of both schema and data format, requiring the least manual effort. AWS Glue crawlers can connect to various data stores, including S3 and RDS, and automatically infer schemas and data formats (like CSV, JSON, Parquet) using built-in or custom classifiers. This information is then stored in the AWS Glue Data Catalog. The other options are less efficient: Manually inspecting data and adding format metadata is time-consuming and prone to error, especially for large datasets. Amazon Macie is primarily for data security and discovery of sensitive data, not for comprehensive data cataloging of storage formats. While it can identify data types, it's not its core purpose to build a complete enterprise data catalog with format metadata for all data. Writing custom scripts is a high-effort solution, requiring significant development and maintenance, which goes against the "least effort" requirement.