You see the same symptoms in every team: dashboards that silently drift, analysts manually verifying numbers every morning, a spike in "the dashboard is wrong" tickets after a deploy, and an on-call rota that burns out faster than features ship. Detecting those problems before BI refreshes — and having a tested path to fix them — is what separates a reliable analytics org from one that succumbs to firefighting. Contents Essential Post-deploy Checks Every Team Should Run How to Implement Automated DQ Tests with dbt and SQL Designing Alerting, SLAs, and Automated Remediation Playbooks That Work Tooling and Integrations: Great Expectations, Data Observability Platforms, and Integrations Operational Metrics to Measure Impact and Prove ROI Practical Implementation Checklist Essential Post-deploy Checks Every Team Should Run When a deploy finishes, treat the production data surface like a canary.…