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Answer: Deploy Azure Purview to automatically discover, classify, and label sensitive data across the lakehouse and semantic models, and use these labels to enforce access controls and compliance policies dynamically.
Option D is the correct answer because Azure Purview provides a unified data governance solution that automates the discovery, classification, and labeling of sensitive data across both lakehouses and semantic models. It also enables dynamic enforcement of access controls and compliance policies based on sensitivity labels, which is essential for meeting regulatory requirements and scaling with the organization's data growth. Option A is incorrect due to its manual approach, which is not scalable and increases operational overhead. Option B is incorrect because Azure Policy does not provide the capability to discover and classify sensitive data automatically. Option C is incorrect as it only addresses data within the lakehouse and lacks integration with semantic models for a comprehensive governance strategy.
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As a Microsoft Fabric Analytics Engineer Associate DP-600, you are responsible for implementing a comprehensive data governance strategy that includes sensitivity labeling for semantic models and lakehouses within your organization. The organization operates in a highly regulated industry, requiring strict compliance with data protection standards. You need to ensure that sensitive data is accurately classified, labeled, and protected across all data assets. Additionally, the solution must scale to accommodate the organization's growing data volume and complexity, while minimizing operational overhead. Which of the following approaches BEST meets these requirements? (Choose one option)
A
Create and manually apply custom sensitivity labels using Azure Information Protection (AIP) to each data source, table, and column in the semantic model and lakehouse, ensuring each label is configured with the appropriate protection settings.
B
Define a set of data classification and labeling policies using Azure Policy, and assign these policies at the subscription level to automatically enforce compliance across all Azure resources, including semantic models and lakehouses.
C
Utilize Azure SQL Information Protection to automatically classify and label sensitive data within the lakehouse, and apply dynamic data masking rules based on the sensitivity labels to restrict data access.
D
Deploy Azure Purview to automatically discover, classify, and label sensitive data across the lakehouse and semantic models, and use these labels to enforce access controls and compliance policies dynamically.