Paperback. 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 audienceOrganizations of any size, from single cloud (e.g., Azure) to multi-cloudFinOps owners and cloud cost managersData engineers and BI/Power BI developersCloud architects as well as engineering and platform teamsFinance/controlling and management teams that want to steer costs transparently and prepare decisions on a solid basisContents include: Data engineering as the foundation for FinOpsHarmonizing cost data with FOCUSSingle- and multi-cloud scenariosAI cost models: tokens, GPUs, workflows, and KPIsSemantic models, metrics, and reporting with Power BIData quality, allocation, and accountability (governance)Forecasting, budgets, and early warning systemsCloud cost management in 90 days46 KPI fact sheets as a downloadFor everyone who wants to not only display cloud and AI costs, but truly manage them, from a data engineering, FinOps, and Power BI perspective. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Bibliographic Details

Title: Cloud and AI Cost Management with Power BI (Paperback)
Publisher: Independently Published
Publication Date: 2026
Language: English
ISBN 13: 9798257388354
Binding: Paperback
Condition: new

About this title

Synopsis

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.

"About this title" may belong to another edition of this title.

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