Data Platform Control Plane

Quality gates + GCP-native reliability

Two separate controls: Great Expectations validates data contracts before release; Cloud Scheduler and Cloud Monitoring verify the live BigQuery platform after deployment.

48/48GE expectations passed
55,500Source rows contract-tested
50,000Warehouse facts verified live
6-hourGCP reliability schedule
✓ Quality gate passed — release allowed

Great Expectations: release-boundary contracts

GE runs automatically in CI before release: once over the full source delivery, then again over the AI-facing enrichment. Domain-specific PII, identity, and lineage checks run as a separate custom checkpoint.

Contract groupCoverageObserved result
source_release_contract55,500 rows · 27 expectations27/27 passed
enriched_ai_contract497 rows · 21 expectations21/21 passed
exception visibility108 negative billing values observedWithin explicit 0.5% tolerance
release behaviorCritical contract failureBlocks publish
✓ Reconciliation passed — no silent row loss

Source-to-warehouse reconciliation

The grain chain accounts for every source row and verifies that entity resolution and the warehouse patient dimension agree.

55,500 raw5,500 exact duplicates removed50,000 encounters40,235 canonical patients
✓ Live GCP probe — final verification true

Platform reliability: detect, retry, verify, escalate

A GCP-native probe runs every six hours against the live BigQuery warehouse. Each execution writes a verified receipt to healthcare_analytics.pipeline_run_history; HTTP failures trigger bounded Scheduler retries and a Cloud Monitoring alert policy.

Reliability controlNative GCP mechanismLatest proof
DetectCloud Run probe → BigQuery50,000 fact rows queryable
RetryCloud Scheduler exponential backoffEnabled
VerifyBigQuery run receiptfinal_verification=true
EscalateCloud Monitoring alert policyEnabled on HTTP 5xx