A company has a data lake on AWS. The data lake ingests sources of data from business units. The company uses Amazon Athena for queries. The storage layer is Amazon S3 with an AWS Glue Data Catalog as a metadata repository.
The company wants to make the data available to data scientists and business analysts. However, the company first needs to manage fine-grained, column-level data access for Athena based on the user roles and responsibilities.
Which solution will meet these requirements?
To manage fine-grained, column-level data access for Amazon Athena based on user roles and responsibilities, setting up AWS Lake Formation is the appropriate solution. Lake Formation allows you to define security policy-based rules that include granular permissions at the column level. This permits better control and secure access management tailored to specific user roles and responsibilities within the organization.
Lake Formation supports fine-grained access control, including column-level permissions.
Correct Solution: A. Set up AWS Lake Formation. Define security policy-based rules for the users and applications by IAM role in Lake Formation. Explanation: AWS Lake Formation: This service simplifies and automates the process of securing and managing data lakes. It allows you to define fine-grained access control policies at the database, table, and column levels. Security Policy-Based Rules: Lake Formation allows you to create policies that specify which users or roles have access to specific data, including column-level access controls. This makes it easier to manage access based on roles and responsibilities.
A - Lake formation