data-engineer-pro video for scenario: You are using BigQuery as your centralized analytics platform. New data is loaded daily, and an ETL pipeline processes the
Scenario: You are using BigQuery as your centralized analytics platform. New data is loaded daily, and an ETL pipeline processes the original data and prepares it for final use. This ETL pipeline is modified regularly and may cause errors, which are sometimes detected only after two weeks. You need a method to recover from these errors while optimizing backup storage costs. Question: How should you organize your data in BigQuery and store your backups?