FinOps program for analytics spend

Cost visibility and engineering habits across warehouses and BI tools — without blocking clinical and operations analytics.

Spend was visible only after invoices — and every team had a favorite oversized warehouse. We introduced tagging, showback, and engineering rituals so new workloads were sized before they landed on the bill.

How we approached it

Allocation & showback

Department and workload dimensions everyone agrees on; dashboards finance and engineering both trust.

Optimization sprints

Query and table tuning, tiering, and scheduling changes with measured savings per wave.

Guardrails

Budget alerts and policy hooks in the platform so surprises surface in Slack before finance does.

What we delivered

Showback by department and workload tagging
Query and warehouse optimization sprints
Budget alerts and guardrails in the platform
Playbooks engineers use before opening new capacity

Outcomes

Predictable monthly analytics spend with fewer fire drills
Clinical and ops teams unblocked with clear capacity rules
Engineering playbooks reused when onboarding new use cases

Representative stack

SnowflakedbtCloudWatchOpenMetadataSlack