Power BI Usage Metrics Reports
This article outlines how Power BI generates, manages, and stores Usage Metrics reports, including their visibility, workspace behavior, report-level behavior, and dependency on system-generated semantic models. It also explains the differences between Power BI-managed usage metrics datasets and user-created semantic models.
Usage Metrics reports help monitor report and dashboard activity within Power BI. These reports are system-generated and behave differently from standard user-created PBIX reports.
Usage Metrics Reports
Usage Metrics Report Visibility
Usage Metrics reports are not displayed in the workspace Reports list by default because the reports are system-generated artifacts managed by the Power BI Service.
Unlike standard PBIX reports, Usage Metrics reports are accessible only through the Usage Metrics option available from the ellipsis (...) menu of a report or dashboard.
Key Details
Report creation
Power BI automatically generates Usage Metrics reports when usage metrics are accessed for a report or dashboard.
Workspace visibility
Usage Metrics reports do not appear in the workspace Reports list unless a manual copy of the report is saved.
Access method
Usage Metrics reports are accessible from the Usage Metrics option available in the ellipsis (...) menu of reports and dashboards.
Standard report conversion
Selecting Save a copy converts the system-generated Usage Metrics report into a standard report visible within the workspace.
Usage Metrics reports are not treated as standard user-created reports.
The reports become visible in the workspace only after selecting Save a copy.
Saving a copy converts the system-generated report into a standard PBIX report.
Workspace-Level Functionality
Power BI does not automatically generate a single Usage Metrics report for an entire workspace.
Usage metrics remain associated with individual reports and dashboards instead of the complete workspace.
Key Details
Default workspace summary report
Power BI does not create a built-in Usage Metrics report that summarizes activity across all reports and dashboards within a workspace.
Metrics scope
Usage metrics are tracked separately for each report and dashboard available in the workspace.
Workspace-wide monitoring
A consolidated workspace-level monitoring solution requires manual implementation using exported activity or telemetry data.
Workspace-wide usage analytics requires custom implementation using Power BI Activity Logs, Admin APIs, or exported telemetry data.
Report and Dashboard-Level Functionality
Each report and dashboard within a workspace can have an independent Usage Metrics report.
The Usage Metrics report is generated only after the Usage Metrics option is accessed for the first time.
Although telemetry collection occurs automatically in the background, the visual Usage Metrics report appears only after the request is initiated.
Key Details
Metrics availability
Each report and dashboard can maintain a separate Usage Metrics report containing individual activity and usage details.
Initial report generation
Power BI generates the Usage Metrics report only when the Usage Metrics option is opened for the first time.
Background telemetry collection
Power BI continuously collects usage and activity data in the background, even before the Usage Metrics report is opened.
Saved copy support
Usage Metrics reports can be saved as standard reports within the workspace using the Save a Copy option.
Usage Metrics reports are created independently for each report and dashboard.
Saved copies operate like standard reports within the workspace.
Saving a copy does not create a separate telemetry dataset.
Semantic Model (Dataset) Functionality
When Usage Metrics is opened for the first time within a workspace, Power BI automatically creates a hidden semantic model that stores telemetry and usage data for that workspace.
This semantic model is managed internally by the Power BI Service and supports both the system-generated Usage Metrics reports and saved report copies.
Key Details
Dataset creation
Power BI automatically creates a hidden Usage Metrics dataset when usage metrics are accessed for the first time within a workspace.
Dataset visibility
The Usage Metrics dataset remains hidden from the standard workspace view and is not treated as a regular semantic model.
Dataset management
The dataset is fully managed internally by the Power BI Service without manual administrative control.
Dataset usage
The same hidden dataset supports system-generated Usage Metrics reports and all saved report copies within the workspace.
Refresh management
Power BI controls dataset refresh operations internally without allowing manual or scheduled refresh configuration.
A single hidden Usage Metrics dataset is created per workspace.
Saved copies of Usage Metrics reports continue to reference the same hidden dataset.
The dataset cannot be manually refreshed, modified, or scheduled for refresh.
The hidden Usage Metrics dataset remains read-only and cannot be directly edited or customized.
Usage Metrics Datasets Vs User-Created Semantic Models
Power BI-managed Usage Metrics datasets differ significantly from user-created semantic models.
User-created semantic models provide full administrative control over refresh schedules, updates, APIs, and modifications, whereas Usage Metrics datasets remain read-only and service-managed.
Comparison
Dataset ownership
Managed internally by the Power BI Service.
Managed by the report or semantic model owner.
Refresh control
Refresh operations are controlled automatically by Power BI.
Manual and scheduled refresh operations are supported.
Scheduled refresh support
Scheduled refresh configuration is not available.
Scheduled refresh configuration is supported.
Manual refresh support
Manual refresh execution is not supported.
Manual refresh execution is supported.
API-based updates
Dataset updates through APIs are not supported.
API-based updates and management operations are supported.
Dataset modification
Direct modification or customization is not supported.
Dataset structure and logic can be modified as required.
Intended usage
Used internally for storing and displaying usage telemetry data.
Used for custom reporting, analytics, and business intelligence implementations.
Custom refreshable usage analytics solutions require the extraction of usage data through Power BI Activity Logs or Admin APIs, followed by the creation of an independent semantic model and reporting solution.
Implementation Considerations
The following approaches are commonly used for implementing Usage Metrics monitoring solutions in Power BI.
Standard usage monitoring
Use the built-in Usage Metrics reports available within Power BI reports and dashboards.
Workspace-wide analytics
Create custom reporting solutions using Power BI Activity Logs or Admin APIs.
Refreshable analytics solution
Build a separate semantic model using exported telemetry or activity log data.
Centralized monitoring
Use tenant-level usage datasets available for Power BI administrators to monitor activity across multiple workspaces.
Tenant-level usage monitoring provides centralized visibility across multiple workspaces and supports governance, auditing, and usage analysis requirements.
Summary
Visibility
Usage Metrics reports are not automatically visible in workspace report lists and require manual saving to appear as standard reports.
Report generation
Usage Metrics reports are created separately for each report and dashboard within a workspace.
Workspace-level report availability
Power BI does not automatically generate a consolidated workspace-wide Usage Metrics report.
Saved copy functionality
Saved copies appear as standard reports within the workspace while continuing to use the same hidden dataset.
Dataset architecture
Power BI creates one hidden Usage Metrics dataset for each workspace.
Dataset refresh management
Dataset refresh operations are fully controlled by the Power BI Service.
Saved report copy dependency
Saved Usage Metrics report copies continue to depend on the original hidden dataset.
Custom analytics implementation
Advanced analytics solutions require Activity Logs or Admin APIs combined with independently created semantic models and reports.
Advanced and refreshable usage analytics implementations require custom semantic models created using exported activity logs or Power BI Admin API data.
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