BigQuery

GCP Testing

BigQuery Data Pipeline Validation: Testing SQL Transforms, Data Quality, and Pipeline Correctness

BigQuery data pipelines have a testing problem. The transformations run in SQL, the data volumes are large, and a broken pipeline often produces plausible-looking results that fail to reveal themselves as wrong until someone checks a business metric two weeks later. This guide covers practical validation strategies for BigQuery

Testing

Testing BigQuery Queries and Data Pipelines with bq-test-kit and dbt

BigQuery pipelines are notoriously hard to test because every query costs money and requires live infrastructure. This guide covers three layers of testing: bq-test-kit for Python unit tests against a local emulator, dbt's built-in test framework for data quality assertions, and direct SQL testing patterns