A company uses Microsoft Purview Information Protection to classify and protect sensitive data. They want to automatically apply a sensitivity label to documents containing credit card numbers. Which should you configure?
Configuring an auto-labeling policy with a sensitive information type for credit card numbers is the most effective and accurate method for automatic protection. This approach leverages Microsoft Purview's built-in capabilities to scan content for specific patterns, keywords, and checksums associated with credit card numbers, then automatically applies the appropriate sensitivity label and its associated protection actions (e.g., encryption, access restrictions) without any user intervention.
Why this answer
Microsoft Purview auto-labeling policies can automatically apply sensitivity labels to documents and emails that contain specific sensitive information types, such as credit card numbers. This enables automated classification and protection without requiring user intervention, directly meeting the requirement to automatically apply a label based on the presence of credit card data.
Exam trap
The trap here is confusing trainable classifiers with sensitive info types, leading candidates to choose Option B because they think 'trainable' implies automatic detection, but trainable classifiers are for broader content categories, not specific regex-based patterns like credit card numbers.
How to eliminate wrong answers
Option A is wrong because manual labeling requires users to apply labels themselves, which does not meet the requirement for automatic application. Option B is wrong because trainable classifiers are used to identify content based on patterns or context (e.g., contracts or resumes), not for detecting specific sensitive info types like credit card numbers; that is the role of sensitive info types. Option D is wrong because the data classification activity explorer is a monitoring and auditing tool that shows what labels and classifications have been applied, not a mechanism to automatically apply labels.