A data analyst at a healthcare organization is preparing a dataset for a university research study on patient outcomes. The dataset contains sensitive Personal Health Information (PHI). To comply with privacy regulations and protect patient identities, while still providing valuable data for statistical analysis, which of the following data protection practices is the MOST appropriate to apply before sharing the dataset?
The correct answer is Anonymization. Anonymization is the process of removing or modifying personally identifiable information (PII) and personal health information (PHI) to ensure that the individuals who are the subjects of the data cannot be identified. This technique is essential when sharing sensitive data for external research or statistical analysis, as it protects privacy while maintaining the analytical value of the data.
Data masking is a plausible but less appropriate choice. Masking typically replaces sensitive data with realistic but fabricated data and is most often used for internal purposes like software testing or training where the data format must be preserved. While it is a form of data obfuscation, anonymization is the more precise term for the goal of making re-identification impossible for research purposes.
Encryption at rest protects data that is stored on a disk or in a database by making it unreadable without a decryption key. It does not protect the data once it has been decrypted and shared with the third-party researchers.
Role-based access control (RBAC) is a method for managing who can access data within a system based on their job function. It controls access permissions but does not alter the data itself to make it safe for sharing with an external entity.
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CompTIA Data+ DA0-002 (V2)
Data Governance
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