You oversee a BigQuery data pipeline for your analytics platform, with daily data loads and transformations via an ETL pipeline. This pipeline undergoes frequent updates, potentially introducing errors that might go unnoticed for up to two weeks. Your goal is to ensure error recovery capability while optimizing backup storage costs. What strategy should you adopt?