Restricting User Access in Azure Synapse Analytics Dedicated SQL Pool
Question
You work in Azure Synapse Analytics dedicated SQL pool that has a table titled Pilots.
Now you want to restrict the user access in such a way that users in ‘IndianAnalyst' role can see only the pilots from India.Which of the following would you add to the solution?
Answers
Explanations
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A. B. C. D. E.Correct Answer: D
Row-level security is applicable on databases to allow fine-grained access to the rows in a database table for restricted control upon who could access which type of data.
Option A is incorrect.
Table partitions are generally used to group similar data.
Option B is incorrect.
Encryption is used for security purposes.
Option C is incorrect.
Column level security is used to restrict data access at the column level.
In the given scenario, we need to restrict access at the row level.
Option D is correct.
In this scenario, we need to restrict access on a row basis, i.e only for the pilots from India, there Row-level security is the right solution.
Option E is incorrect.
Sensitive data exposure can be limited by masking it to unauthorized users using SQL Database dynamic data masking.
References:
To know more about Row-level security, please visit the below-given links:
The correct answer to the question is D. Row-level security.
Row-level security is a feature in Azure Synapse Analytics dedicated SQL pool that allows users to restrict access to specific rows in a table based on predefined criteria. With row-level security, you can define security predicates that restrict access to certain rows based on user roles, user-defined functions, or context variables.
In this scenario, the requirement is to restrict access to the Pilots table in such a way that only users in the ‘IndianAnalyst' role can see the pilots from India. This can be achieved by using row-level security. You can define a security predicate that restricts access to rows where the ‘Country' column is not equal to ‘India'. This security predicate can be associated with the ‘IndianAnalyst' role, which would restrict access to only those rows that meet the security predicate criteria.
Table partitions are used to improve query performance by dividing a large table into smaller, more manageable partitions. Encryption is used to secure data by converting it into a form that can only be read by authorized users. Column-level security is used to restrict access to specific columns in a table based on user roles or permissions. Data masking is used to conceal sensitive data by replacing it with dummy data or masking characters.
Therefore, in this scenario, the appropriate security measure to restrict user access is row-level security.
