Topic 1 Question 609
A company is building a data analysis platform on AWS by using AWS Lake Formation. The platform will ingest data from different sources such as Amazon S3 and Amazon RDS. The company needs a secure solution to prevent access to portions of the data that contain sensitive information.
Which solution will meet these requirements with the LEAST operational overhead?
Create an IAM role that includes permissions to access Lake Formation tables.
Create data filters to implement row-level security and cell-level security.
Create an AWS Lambda function that removes sensitive information before Lake Formation ingests the data.
Create an AWS Lambda function that periodically queries and removes sensitive information from Lake Formation tables.
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- 正解だと思う選択肢: B
The key reasons are:
Lake Formation data filters allow restricting access to rows or cells in data tables based on conditions. This allows preventing access to sensitive data. Data filters are implemented within Lake Formation and do not require additional coding or Lambda functions. Lambda functions to pre-process data or purge tables would require ongoing development and maintenance. IAM roles only provide user-level permissions, not row or cell level security. Data filters give granular access control over Lake Formation data with minimal configuration, avoiding complex custom code.
👍 7Guru4Cloud2023/09/23 - 正解だと思う選択肢: B
The best solution to meet the requirements with the least operational overhead is to create data filters to implement row-level security and cell-level security.
Data filters are a feature of Lake Formation that allow you to restrict access to data based on row and column values. This can be used to implement row-level security and cell-level security.
To implement row-level security, you would create a data filter that only allows users to access rows where the values in certain columns meet certain criteria. For example, you could create a data filter that only allows users to access rows where the value in the customer_id column matches the user's own customer ID.
👍 2nnecode2023/09/22 - 正解だと思う選択肢: B👍 2potomac2023/11/06
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