Option B is the best answer because separate regional Aurora PostgreSQL clusters keep raw customer PII in the Region where the data is collected, while AWS Glue DataBrew can transform, mask, or redact PII before datasets are used for cross-Region analytics. AWS documentation states that DataBrew can identify and mask PII using techniques such as substitution and shuffling, and AWS Glue sensitive-data transforms can detect, mask, or remove PII entities. Amazon Redshift Serverless then provides a managed analytics layer without requiring the company to operate data warehouse infrastructure. Option D is incorrect because Amazon Macie discovers and helps secure sensitive data in S3; it does not anonymize the data. Option C relies on custom Lambda anonymization and an awkward cross-Region QuickSight database access pattern.