Gather Inventory Data for a Fabric Digital Estate

Developing an inventory is the first step in planning your Microsoft Fabric adoption. This inventory provides visibility into the current landscape of data assets, pipelines, reports, and storage components that support business domains. It enables structured rationalization, cost modeling, and modernization planning across workspaces and domains.

This article assumes a bottom-up, asset-driven approach for inventory building. For more details, see: Approaches to Digital Estate Planning.

Take Inventory of Your Fabric Estate

The structure of your inventory depends on the transformation goals—whether you're migrating, modernizing, consolidating, or scaling. Examples include:

Fabric Consolidation or Migration:

Use tenant-level tools such as:

• Power BI Activity Logs (e.g., to track reports, datasets, and usage patterns)
• Fabric Capacity Metrics App (to analyze CU usage across workspaces)
• Admin APIs or REST APIs to extract workspace configurations, pipelines, and Lakehouses
• Microsoft Purview to scan and classify sensitivity, domains, and data lineage

This inventory should include:

• Workspaces, domains, and workspace types (shared/dedicated)
• Fabric artifacts: Reports, Datasets, Pipelines, Notebooks, Lakehouses, Warehouses
• Refresh schedules and last-used timestamps
• Dataset ownership and usage patterns
• Dependencies (shortcuts, linked tables, Power BI composite models)

Data Product Innovation:

When data products are the foundation of your transformation, start with:

• Use case discovery workshops with business teams
• Mapping user needs to semantic models, pipelines, and source data
• Identifying duplication of datasets and dashboards
• Understanding user journeys across Power BI apps and reports

Governance and Security:

Inventory is essential for:

• Identifying ungoverned datasets or shadow IT artifacts
• Analyzing workspace roles, permissions, and external sharing
• Reviewing DLP policy violations and data classification gaps
• Assessing security risk (e.g., sensitivity vs. exposure vs. capacity)

Accuracy and Completeness of Inventory

Inventory building in Fabric is iterative. It improves over time through automation and stakeholder validation.

Best practices:

• Involve Power BI admins, Fabric platform owners, and domain data stewards early
• Use Microsoft Purview, Log Analytics, or Tenant APIs to enrich metadata
• Schedule review loops with power users to detect missing or inactive assets
• Identify high-risk or orphaned assets through usage telemetry