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Answer: Mapping Azure AD groups to Databricks groups and assigning minimal necessary permissions at the workspace level
Mapping Azure AD groups to Databricks groups and assigning minimal necessary permissions at the workspace level is the most effective method to ensure the principle of least privilege is applied effectively for data access in Databricks with Azure AD integration. This approach allows for centralized management of access control by leveraging Azure AD groups, simplifying the process of assigning and revoking permissions based on user roles or responsibilities. It ensures users only have access to the data and resources necessary for their job functions, reducing the risk of unauthorized access and data breaches. Additionally, this method supports scalability and ease of auditing access control settings.
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How can the principle of least privilege be effectively applied for data access when integrating Azure AD with Azure Databricks?
A
Automatically provisioning users in Databricks with the same role-based access controls defined in Azure AD
B
Implementing a custom Azure Function to dynamically adjust Databricks permissions based on real-time Azure AD group membership changes
C
Mapping Azure AD groups to Databricks groups and assigning minimal necessary permissions at the workspace level
D
Using Azure AD Conditional Access policies to limit Databricks access based on user role and location