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Answer: Create user roles based on job functions and assign dataset access to these roles, rather than individuals.
Creating user roles based on job functions and assigning dataset access to these roles (Option C) is the most suitable and efficient approach for implementing a least privilege access model in a data lake environment with varying levels of sensitivity. This approach allows for granular control over dataset access based on job responsibilities and ensures that users have the necessary access to perform their tasks without granting unnecessary permissions. It also simplifies access management by assigning permissions to roles rather than individual users, making it easier to maintain and update access controls as needed. Other options, such as using a blanket policy (Option A) or an allowlist (Option B), may not provide the same level of flexibility and efficiency. Assigning all users to a default role with no access (Option D) may be too restrictive and time-consuming to manage effectively.
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In a data lake environment with datasets of varying sensitivity levels, what is the most effective way to implement a least privilege access model?
A
Use a blanket policy that restricts access to sensitive datasets, with an ad-hoc process for granting exceptions.
B
Implement an allowlist for sensitive datasets, requiring explicit approval for access.
C
Create user roles based on job functions and assign dataset access to these roles, rather than individuals.
D
Assign all users to a default role with no access, granting specific dataset permissions on a case-by-case basis.
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