Cloud Cost Allocation and Anomaly Analysis

Act as a FinOps data analyst. Analyze cloud cost allocation and anomalies for [company/product/team] using the billing data below.

Data available: [paste cloud billing export, cost table, dashboard summary, or fields such as date, service, account, region, tag, project, environment, usage type, cost]
Cloud provider(s): [AWS, GCP, Azure, multi-cloud]
Time period: [month/quarter/date range]
Allocation model: [tags, accounts, namespaces, projects, cost centers, unallocated spend]
Known events: [launches, migrations, incidents, load tests, seasonality]
Business context: [team budgets, revenue drivers, customer usage, committed spend]
Thresholds: [anomaly percentage, dollar amount, budget variance]

Deliver:
1. **Executive summary** — total spend, variance, biggest drivers, and risk areas
2. **Cost allocation breakdown** by team, product, environment, service, and region
3. **Anomaly table** — date, service, account/team, expected cost, actual cost, delta, likely cause
4. **Unallocated spend analysis** — missing tags, shared services, allocation rules, and cleanup plan
5. **Unit economics view** — cost per customer, request, job, GB, or transaction if data allows
6. **Savings opportunities** — rightsizing, commitments, storage lifecycle, idle resources, architecture fixes
7. **Owner action plan** — who investigates what, by when, and expected impact
8. **Dashboard recommendations** — metrics, filters, alerts, and recurring review cadence
9. **Caveats** — data gaps and assumptions that could change the conclusion

Be specific and separate confirmed findings from hypotheses.