DP-700 Question #62: Real Exam Question with Answer & Explanation

Question

Your organization wants to classify data based on its sensitivity and regulatory requirements. Which of the following methods would be most appropriate for implementing data classification within Microsoft Fabric ?

Options

• AUse Azure Information Protection (AIP) labels to classify data at the file or folder level.
• BCreate custom tags in Azure Data Factory to label data based on its sensitivity.
• CConfigure row-level security (RLS) to restrict data visibility based on sensitivity levels.
• DImplement data masking to obfuscate sensitive data.

Explanation

To implement data classification based on sensitivity and regulatory requirements in Microsoft Fabric, using Azure Information Protection (AIP) labels is the most appropriate method.

Common mistakes.

• B. Custom tags in Azure Data Factory are primarily for organizing and filtering pipelines or datasets within Data Factory itself, not for enterprise-wide data sensitivity classification or regulatory compliance.
• C. Row-level security (RLS) restricts who can see which rows of data based on permissions, which is an access control mechanism, not a method for classifying the inherent sensitivity of the data itself.
• D. Data masking is a technique to obfuscate or hide sensitive data from unauthorized users, serving as a data protection measure, but it is not a method for classifying the data's sensitivity or regulatory requirements.

Concept tested. Data classification and Microsoft Purview

Reference. https://learn.microsoft.com/en-us/fabric/data-governance/microsoft-purview-information-protection-overview

No community discussion yet for this question.