Data cloud platforms can be hard to manage with FinOps because the spend model is complex. Spend can change quickly with elastic workloads, shared resources blur ownership, and standard reporting often does not fully connect billing data and platform telemetry to enable total cost understanding, clean attribution to teams, and clear workload efficiency signals. The result is that teams can see spend, but cannot quickly tell what is driving it, whether it is efficient, or what to fix.
In this session, I will share how we developed FinOps insights that delivered a total cost of ownership view of our data cloud spend, making it understandable, attributable, and actionable. We created a consistent cost and usage foundation by combining cloud billing data with platform telemetry, then delivered a set of practitioner-friendly tools and insights that make spend transparent and actionable. Teams can quickly drill from executive-level rollups down to the workloads and resources driving cost, and engineers can use efficiency insights and guided optimization playbooks to tune workloads, right size configurations, and measure impact. We operationalized these insights through best-practice guidance and a lightweight operating model that was gamified to scale adoption across the organization.