Exam Professional Data Engineer topic 1 question 217 discussion

Option B & E

B& E https://cloud.google.com/bigquery/docs/column-level-security-intro

the correct options are: A. Create two separate authorized datasets; one for the data analytics team and another for the consumer support team. C. Replace the authorized dataset with an authorized view. Use row-level security and apply filter_expression to limit data access.

B & E B - It will ensure they don't have access to secure columns E- It will allow to enforce column level security Ref - https://cloud.google.com/bigquery/docs/column-level-security-intro

Option B& E to me

A & B The current setup is not effective because the data analytics team still has access to the sensitive columns despite using an authorized dataset and policy tags. This indicates that the policy tags are not being enforced properly, and the data analytics team members are able to view the tags and gain access to the sensitive data. Separating the data into two distinct authorized datasets is a better approach because it isolates the sensitive data from the non-sensitive data. This prevents the data analytics team from accessing the sensitive columns directly, even if they have access to the authorized dataset for general customer data. Additionally, revoking the Data Catalog Fine-Grained Reader role from the data analytics team members ensures that they cannot view or modify the policy tags. This limits their ability to bypass the access control imposed by the authorized dataset and policy tags.

And the second answer? One is option B and the other is option D maybe?

- The Data Catalog Fine-Grained Reader role allows users to read metadata that is restricted by policy tags. - If members of the data analytics team have this role, they might bypass the restrictions set by policy tags. - Ensuring they do not have this role will help enforce the restrictions intended by the policy tags.

Prevents data analytics team members from viewing sensitive data, even if it's tagged. Restricts access to policy tags themselves, ensuring confidentiality of sensitive information.