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Answer: Set a row-level filter to prevent user access to a row where the country is Canada.
Option A is CORRECT because setting a row-level filter in AWS Lake Formation allows the company to restrict access to specific rows in a table based on conditions, such as preventing access to rows where the country is "Canada." Row-level filtering ensures that users can only see data that meets the specified conditions, effectively excluding the rows related to Canadian customers. This approach meets the requirement with the least operational effort, as AWS Lake Formation natively supports row-level security policies for fine-grained access control.
Author: Ritesh Yadav
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Question 21/58
A company stores customer data tables that include customer addresses in an AWS Lake Formation data lake. To comply with new regulations, the company must ensure that users cannot access data for customers who are in Canada.
The company needs a solution that will prevent user access to rows for customers who are in Canada.
Which solution will meet this requirement with the LEAST operational effort?
A
Set a row-level filter to prevent user access to a row where the country is Canada.
B
Create an IAM role that restricts user access to an address where the country is Canada.
C
Set a column-level filter to prevent user access to a row where the country is Canada.
D
Apply a tag to all rows where Canada is the country. Prevent user access where the tag is equal to "Canada".
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