If you need to enable selective column visibility in BigQuery based on user roles, which approach should you use?

The correct approach to enable selective column visibility in BigQuery based on user roles is to use policy tags. Policy tags in BigQuery allow you to define and manage column-level access controls. By assigning policy tags to specific columns in a table, you can restrict visibility based on the roles assigned to users.

For instance, if certain users should not have access to sensitive information contained in specific columns, you can use policy tags to ensure that only specific user roles can see those columns. This feature is particularly useful in environments that require compliance with data privacy regulations or internal data governance policies, as it provides a granular mechanism for controlling access.

Creating a new dataset or a new table with the column's data could be considered workarounds to manage access control, but they do not offer the same flexibility and maintainability as policy tags. Moreover, these approaches can lead to data duplication and increased management overhead. Utilizing IAM permissions could control access at a higher level, such as to entire datasets or tables, but it does not provide the detailed granularity needed for specific column visibility based on user roles. Therefore, policy tags are the most effective and suitable approach for this requirement.