Cloud and AI costs are dynamic, distributed, and often difficult to allocate today, both in
single-cloud environments and in
multi-cloud environments.
This book turns
Power BI into an end-to-end management platform and outlines a practical path for building transparent, comparable, and operationally controllable cost management from the
data foundation through
KPIs,
reporting, and
steady-state operations, from a
data engineering and
FinOps perspective.
FOCUS provides the open standard as a shared language for cost and usage data. It standardizes billing and export data from different cloud providers and thereby enables consistent analyses, comparisons, and KPIs across cloud boundaries.
AI costs are equally central. AI workloads create new cost patterns with
tokens,
GPU time, and multi-step
workflows. Even small changes to a prompt, model version, or agent logic can shift cost profiles quickly. The book explains how token, GPU, and workflow data can be transformed into a controllable model, including practical KPIs such as
cost per request,
cost per feature, and
version economics.
Special feature: The book consistently brings
FinOps,
FOCUS, and
Power BI together and extends this foundation with a complete
AI cost model.
Highlight: A structured
90-day program that describes adoption step-by-step in three phases: establishing transparency, building accountability, and embedding cost governance into steady-state operations.
Download: Also included are a
central KPI overview and
downloadable working materials with
46 KPI fact sheets (definition, data requirements, calculation, interpretation).
Target audience- Organizations of any size, from single cloud (e.g., Azure) to multi-cloud
- FinOps owners and cloud cost managers
- Data engineers and BI/Power BI developers
- Cloud architects as well as engineering and platform teams
- Finance/controlling and management teams that want to steer costs transparently and prepare decisions on a solid basis
Contents include:- Data engineering as the foundation for FinOps
- Harmonizing cost data with FOCUS
- Single- and multi-cloud scenarios
- AI cost models: tokens, GPUs, workflows, and KPIs
- Semantic models, metrics, and reporting with Power BI
- Data quality, allocation, and accountability (governance)
- Forecasting, budgets, and early warning systems
- Cloud cost management in 90 days
- 46 KPI fact sheets as a download
For everyone who wants to not only display
cloud and AI costs, but truly
manage them, from a
data engineering,
FinOps, and
Power BI perspective.
