This control plane turns raw BigQuery usage exports into one FinOps surface: bytes-scanned spikes, slot pressure, partition misses, reservation drift, attribution gaps, telemetry issues, and the remediation packets needed before forecast, chargeback, or optimization windows slip.
| Lane | Owner | Focus | Status | Findings | Next action |
|---|---|---|---|---|---|
| Scan efficiency lane High-value workloads are scanning more data than the budget envelope expects. | Analytics Engineering | Bytes scanned, partition discipline, and wide-read regression control | red | 2 | Restore partition filters and tune the hotspot queries before the next executive refresh cycle. |
| Slot governance lane Reservation contention and underuse are both weakening slot efficiency. | Data Platform | Reservation pressure, queue health, and right-sizing posture | red | 3 | Rebalance reservations and reduce queue pressure on the busiest analytics paths. |
| Attribution hygiene lane Unlabeled query-cost paths are reducing showback trust. | FinOps Operations | Labels, chargeback trust, and finance-facing visibility | yellow | 1 | Backfill labels and enforce owner tagging on scheduled query workflows. |
| Telemetry freshness lane Telemetry and export freshness need cleanup before query-cost posture can be called healthy. | Data Platform | Billing exports, usage extracts, and optimization evidence freshness | yellow | 6 | Restore export freshness and validate downstream cost-governance feeds. |