Data cloud FinOps gets hard fast. Spend changes quickly with elastic workloads, shared resources blur ownership, and standard cloud reports rarely explain which teams, workloads, or behaviors are driving the bill. At 84.51°, we found that high-level reporting was not enough. To scale FinOps, we had to empower the people creating the spend with insights they could actually use.
In this session, I’ll share how we built a personalized FinOps approach for data cloud platforms by combining billing data, workload telemetry, and business context into a shared reporting layer. Rather than building separate reports for every persona, we created common reports and insights that leaders, product teams, engineers, and FinOps practitioners could filter, drill into, and use at the level of detail their decisions required. I’ll cover how we established business ownership, built a trusted data foundation and TCO model, surfaced optimization opportunities across compute, workloads, and storage, and operationalized the work through lightweight cadence, training, and gamified recognition. The result was a scalable model that enabled teams to own and optimize their spend, driving millions in savings.
