The correct answer is D because data anonymization best mitigates privacy risk while still enabling testing.
It allows the organization to use realistic data sets for development or testing purposes without exposing identifiable personal information. This supports business needs while reducing the chance of privacy violations.
The other options are less effective for this specific purpose:
* A. Data classification helps determine protection requirements, but it does not by itself make the data safe for testing.
* B. Data sanitization can remove sensitive data, but anonymization is the more direct privacy- preserving method for retaining usable test data.
* C. Data encryption protects data from unauthorized access, but the data remains personal information once decrypted for testing.
Exact Extracts supporting the answer:
* "A privacy impact assessment can help enterprises weigh the benefits of their data processing activities against risk to determine the appropriate response."
* "The MAIN benefit of information classification is that it helps select security measures proportional to risk."
* "To determine the level of protection required for securing personally identifiable information a risk practitioner should PRIMARILY consider the sensitivity property of the information."
* "The MOST important principle of data protection that a risk practitioner should advocate for is that data should be accurate." These extracts support that personal information should be processed in a way that reduces privacy risk while preserving appropriate business use. For testing, data anonymization is the best answer.