As data + AI adoption grows, Databricks consumption expands across data engineering, analytics, business intelligence, machine learning, generative AI, and shared platform services. While detailed usage and cost signals provide visibility, enterprises can still struggle to connect consumption with business context, funded priorities, and accountable owners. This gap can complicate financial control, budgeting, forecasting, and investment decisions.

Move from cost visibility to in-period accountability

Zensar FinSights is an accountability and decision-support solution for Databricks that transforms consumption data into governed financial context and actionable decisions. Built on a FOCUS-based cost and usage foundation, FinSights helps organizations identify material variances, understand what changed, establish ownership, and link consumption to funded business priorities. Still, there's time to act.

See, explain, and act on consumption

FinSights brings finance, engineering, platform teams, and business owners onto a shared operating model. Executive KPI views, service and SKU-level analysis, anomaly detection, workload investigation, and ownership mapping help teams move from identifying consumption to deciding whether to fund, tune, pause, retire, or scale it. This reduces dependence on manual reconciliation and supports a more consistent decision-making cadence.

Scale data + AI with greater financial confidence

By connecting Databricks consumption with governed evidence, ownership, and funded priorities, FinSights helps enterprises strengthen financial discipline, improve consumption attribution, reduce reconciliation effort, and build greater confidence in continued data + AI investment. Zensar operationalizes this model around each organization's taxonomy, responsibilities, and priorities, creating a practical path from platform visibility to accountable consumption.