BigQuery tables contain PII accessible only to compliance; other data must be available to data scientists. Minimize cost and speed of granting access. What is the best approach?

The correct approach involves creating a separate dataset for data scientists and populating it with views that exclude PII. This method allows for fine-grained access control: the data science team gets project-level IAM roles, and dataset-level access is granted to their specific dataset. Critically, authorizing the views to access the source dataset (instead of granting direct access to the data scientists) ensures that PII remains protected while still allowing data scientists to query the non-sensitive data. This minimizes cost and speeds up access granting because only views, not copies of data, are created, and access is managed at the dataset and view level. Materialized views (options 2 and 4) would incur additional storage and refresh costs, which goes against the requirement to minimize cost. Creating views directly from the source dataset without a dedicated dataset for data scientists (option 1) would make access management more complex and less secure for the PII.