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Common Operating Model Terms (Fabric Context)

Understanding the terminology around operating models is key to planning for Microsoft Fabric adoption. This article clarifies foundational terms that shape how an organization aligns business strategy, customer experience, and technical operations in the cloud era.

Terms​

Business Model​

A business model defines what value a company provides and why it exists. This includes vision, mission, and financial goals. A strong model includes measurable goals or KPIs to track progress. In the context of Microsoft Fabric, it sets the direction for data-driven value delivery, such as insights, automation, and customer-facing analytics.

Customer Experience​

The why of any business strategy is grounded in customer experience (CX). Whether customers interact through digital channels (dashboards, reports, embedded analytics) or internal users consume insights for better service delivery, Fabric becomes a critical element in shaping and improving CX through data products and real-time information delivery.

Digital Transformation​

Digital transformation represents the organization's evolution to support digitized business processes and experiences. In Microsoft Fabric, this means replacing traditional BI silos and legacy ETL systems with a unified Software-as-a-Service (SaaS) data platform that accelerates reporting, data sharing, and decision-making.

Operating Model​

If the business model defines the what and why, the operating model defines the how and who. It's how teams collaborate, how decisions are made, and how technologies and governance operate to support strategic objectives. In Fabric, this includes data governance, DataOps, DevOps, workspace provisioning, ownership of Fabric artifacts, and usage oversight through roles and capacity assignments. For more, see Understanding your Fabric Operating Model.

Cloud Adoption​

Cloud adoption is the process of activating the operating model with scalable, cloud-native technologies like Microsoft Fabric. It includes migration, modernization, and innovation activities that align with business goals. For Fabric, adoption may involve consolidating analytics infrastructure, implementing data mesh principles, and shifting to real-time data experiences—all as part of the broader transformation journey.

Capabilities​

Capabilities describe what an organization must be able to do to operate successfully. In the context of Microsoft Fabric, this includes the ability to create, manage, and consume data products; govern data responsibly; and enable real-time decision-making. Examples include DataOps automation, decentralized publishing of insights, or cross-domain data discoverability.

Functions & Responsibilities​

Functions define what operational responsibilities exist and how they are distributed. Responsibilities should be clearly assigned to roles such as Data Product Owner, Fabric Platform Owner, Data Steward, or Compliance Officer. Establishing these clearly avoids friction and ensures accountability in Fabric-based operating models.

Processes​

Processes are standardized, repeatable workflows. In a Fabric context, this includes processes such as workspace provisioning, data product lifecycle management, CI/CD deployment of pipelines and notebooks, incident and access management, and quality checks. Clear processes enable scalable, governed operations.

RACI / Accountability Structure​

RACI (Responsible, Accountable, Consulted, Informed) structures help clarify who does what. A clear RACI is crucial in decentralized environments like Data Mesh to manage responsibilities across teams and domains, especially when Fabric artifacts span organizational boundaries.

Operating Model Archetypes​

Common archetypes such as Centralized, Decentralized, Federated, and Mesh describe how responsibilities and operations are structured. In Fabric, a federated model with central governance and domain autonomy is most common, particularly when data mesh principles are applied.

Performance & Cost Transparency​

Cost and usage accountability are vital in a shared SaaS model like Fabric. Teams need visibility into how capacities are used. Tools like the Fabric Performance Report (via Admin Portal) help monitor usage by workspace, user, and artifact type.

Governance & Compliance​

These define the policies, controls, and rules that ensure secure and compliant operations. In Fabric, this includes policies on sharing, retention, sensitivity labels, and workspace naming. Central enforcement is often combined with local responsibilities.

Technology & Platform Stack​

The operating model must describe the technical scope. In Fabric, this includes Capacities, Workspaces, Lakehouses, Warehouses, Pipelines, Notebooks, Dataflows, KQL databases, Real-Time Hubs, and OneLake integration.

Skills & Roles​

Clearly defined roles such as Data Product Owner, Fabric Admin, Platform Engineer, and BI Developer are required. Each role maps to required skills and contributes to the delivery and governance of Fabric workloads.

For a deeper dive into how these concepts apply specifically to decentralized data ownership and mesh-based architecture, see the Data Mesh Introduction.

For a structured application of these terms in a Microsoft Fabric target operating model, see Define your Fabric Operating Model.

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