How to Enforce GDPR Compliance in BigQuery

How do I make my BigQuery data GDPR compliant?

GDPR compliance in BigQuery means configuring storage, processing, and access controls so personal data is collected, stored, queried, and deleted in line with EU regulations.

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Description

Example H2

Example H3

What steps achieve GDPR compliance in BigQuery quickly?

Create datasets in EU regions, use customer-managed encryption keys (CMEK), restrict query access with IAM roles, and automate data deletion with partition expiration.

How to store EU data only in EU regions?

Create datasets with the LOCATION=EU clause. BigQuery guarantees data residency inside EU data centers.

How to prevent unauthorised reads of personal data?

Grant the bigquery.dataViewer role only to users who need it. Combine with Column-Level Security and dynamic data masking.

How does Column-Level Security work?

Attach CREATE POLICY rules to sensitive columns such as email in the Customers table. Only authorised groups will see the raw value.

Why use dynamic data masking?

Masking lets analysts query but never see full personal data. GDPR allows pseudonymisation as a safeguard.

How to automate the right to be forgotten?

Partition tables by created_at and set partition_expiration_days. Combine with scheduled DELETE statements for exact requests.

How to audit who accessed personal data?

Enable Cloud Audit Logs for BigQuery. Logs show every query, the user, the job ID, and affected tables—critical for GDPR accountability.

Best practices for ongoing compliance?

Run scheduled queries that look for unencrypted or non-EU datasets, set alerting on IAM policy changes, and document data-flow diagrams.

Why How to Enforce GDPR Compliance in BigQuery is important

How to Enforce GDPR Compliance in BigQuery Example Usage


-- GDPR "right to erasure" example
DECLARE v_customer_id INT64 DEFAULT 42;

DELETE FROM `ecommerce_eu.OrderItems`
WHERE order_id IN (
  SELECT id FROM `ecommerce_eu.Orders` WHERE customer_id = v_customer_id
);

DELETE FROM `ecommerce_eu.Orders` WHERE customer_id = v_customer_id;
DELETE FROM `ecommerce_eu.Customers` WHERE id = v_customer_id;

How to Enforce GDPR Compliance in BigQuery Syntax


-- 1. Create EU-only dataset
CREATE SCHEMA `ecommerce_eu`
OPTIONS(location="EU", default_table_expiration_days=365);

-- 2. Mask email column for most users
CREATE POLICY mask_email
  ON `ecommerce_eu.Customers`
  COLUMN email
  USING (NOT (EXISTS (SELECT 1 FROM BIGQUERY_SESSION_GROUPS() g WHERE g.group_name = "gdpr_privileged")))
  WITH REPLACEMENT AS "***MASKED***";

-- 3. Partition Orders table and auto-expire after 730 days
CREATE TABLE `ecommerce_eu.Orders` (
  id INT64,
  customer_id INT64,
  order_date DATE,
  total_amount NUMERIC
)
PARTITION BY DATE(order_date)
OPTIONS(partition_expiration_days=730);

-- 4. Delete a specific customer on request
delete_customer_id = 42;
DELETE FROM `ecommerce_eu.Customers`
WHERE id = delete_customer_id;

Common Mistakes

Storing EU customer data in the US multi-region dataset. Always specify LOCATION=EU when creating schemas or tables.
Deleting only from core tables while leaving personal data in nested logs or derived tables. Use dependency tracking and scheduled erasure jobs.