The correct option is Mask sensitive fields by replacing them with realistic non-sensitive values to keep datasets usable for testing.

Mask sensitive fields by replacing them with realistic non-sensitive values to keep datasets usable for testing is the primary purpose because it removes or alters personally identifying values while preserving format and realism so developers and testers can run scenarios without exposing customer identifiers. Masking preserves data formats and referential integrity so tests remain meaningful while sensitive values are replaced with plausible non sensitive ones.

Compress datasets to lower storage requirements is wrong because compression only reduces storage size and does not hide or replace sensitive values so it does not protect customer identifiers for testing.

Google Cloud Data Loss Prevention is wrong because that is a Google Cloud product rather than an Azure feature and the question is about masking in an Azure data platform. It is also a different tool even though it can classify and transform data in Google Cloud.

Encrypt data at rest and in transit for stronger protection is wrong because encryption protects confidentiality while data is stored or moving and it does not produce realistic, non sensitive test values. Encrypted data is not directly usable for normal testing without decryption which defeats the purpose of creating safe test datasets.

Full AWS Practitioner Certification Question