Fix GCP BigQuery Column Level Errors

When working with GCP BigQuery, you may encounter a configuration error that prevents your data pipeline or messaging system from working. This guide explains the most common mistake with column level and shows the exact fix.

A Common Mistake

Granting access to a table without using column-level security, exposing sensitive columns (PII, financial data) to unauthorized users.

The incorrect command:

# User can query all columns
SELECT name, email, ssn, salary FROM employees

Error output:

User sees all columns including sensitive PII:
name, email, ssn, salary
SSN and salary data should be restricted. Without column-level security, the user has access to all columns if they have table read permission.

The Correct Approach

The right way to configure column level in GCP BigQuery:

CREATE OR REPLACE VIEW my_project:my_dataset.employees_safe AS
SELECT name, email, department_id, role_id
FROM my_project:my_dataset.employees
# Omit ssn and salary columns
# Grant access to the view, not the underlying table

Successful result:

Authorized view created.
GRANT `roles/bigquery.dataViewer` ON my_project:my_dataset.employees_safe TO user:analyst@example.com
User can query the view:
SELECT * FROM employees_safe
Returns only non-sensitive columns. ssn and salary are excluded.

How to Prevent This

Use authorized views or column-level security (Policy Tags) to restrict column access. Column-level security uses taxonomy policy tags to classify data (e.g., 'PII', 'SSN', 'Sensitive'). Users without the required role see NULL for tagged columns. Policy tags can also enforce masking rules.

FAQ

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