Applying Data Security Mechanisms. DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 5)

Questions 21–23

1. 21application · medium

   A healthcare company stores patient records in a Delta table. Only users in the 'clinicians' group should see rows for patients in their own department. A data analyst in the 'research' group must see all rows but with the patient's name masked. Which combination of features should be applied?

   • ACreate a column mask on the department column for the 'clinicians' group and a row filter on the name column for the 'research' group.
   • BCreate a view that filters rows for 'clinicians' and masks names for 'research', then grant access to the view.
   • CCreate a row filter on department for the 'clinicians' group and a column mask on the name column for the 'research' group.
   • DCreate a single row filter that hides the name column for the 'research' group and restricts rows for the 'clinicians' group.
   Reveal Solution Discussion Select an answer first
2. 22application · medium

   An organization's security policy requires that only members of the 'finance' group can access the 'budget' folder, while all other employees must have no access. The folder currently inherits permissions from the parent folder that grants 'Can View' to all workspace users. What should the data engineer do?

   • ACreate a new group for non-finance users and deny them access to the 'budget' folder.
   • BMove the 'budget' folder to a new location and grant 'Can View' to the 'finance' group.
   • CGrant 'Can Manage' to the 'finance' group on the 'budget' folder and remove the parent folder's permission from all users.
   • DChange the 'budget' folder's permissions to grant 'Can Edit' to the 'finance' group and remove the inherited 'Can View' for all users.
   Reveal Solution Discussion Select an answer first
3. 23application · medium

   A marketing analytics team needs a dataset for campaign analysis that does not include any personally identifiable information (PII). The team requires age ranges (e.g., 20-29) instead of exact ages and does not need to re-identify individuals. Which anonymization approach should the data engineer apply?

   • AHash the names and email addresses and keep exact ages.
   • BRemove the age column entirely and keep names and email addresses.
   • CReplace exact ages with age ranges and remove names and email addresses from the dataset.
   • DTokenize the names and email addresses and keep exact ages.
   Reveal Solution Discussion Select an answer first