Certified Data Analyst AssociateDemo

By Databricks · Question Mode

QuestionQ40

Securing Data

A data analyst is assembling a dataset containing customer details, including email addresses and birthdates. Multiple teams will use this dataset to generate reports, but certain teams must not be permitted to access sensitive data. The analyst must ensure that the data is stored securely and that personally identifiable information (PII) is safeguarded in accordance with organizational standards and Databricks best practices.

Which action should the analyst take to protect the PII data while enabling safe reporting access for other teams?

  • A Grant SELECT privileges to all report writers for the required subset of data from the base table.
  • B Use Dynamic Views with IS_MEMBER() functions to restrict PII columns based on user roles.
  • C Store the PII data in a shared CSV file on DBFS and apply access control at the folder level.
  • D Mask PII data by obfuscating it in the source table before conducting analysis.
Explanation

Dynamic views can provide fine-grained, role-aware column-level security and data masking for reporting users. A view can use a group-membership function to return PII only to authorized roles and redact or exclude it for other teams, while the underlying table remains inaccessible to those users. Databricks recommends using is_account_group_member() for Unity Catalog account-level groups; is_member() evaluates workspace-level membership and is retained for compatible use cases.

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