What is Analytics?
Azure DevOps Server 2019
Analytics is the reporting platform for Azure DevOps, replacing the previous platform based on SQL Server Reporting Services. Built for reporting, Analytics is optimized for fast read-access and server-based aggregations. Use it to answer quantitative questions about the past or present state of your projects.
Note
If you are looking for information about Azure Analysis Services, see Azure Analysis Services.
Specifically, Analytics provides you with insights about your Azure DevOps projects through the following tools:
- Analytics widgets that you can add to your dashboards
- Custom reports you can create using Power BI
- Custom reports you can create using OData queries
- Support to develop and add your custom Analytics widgets you can add to dashboards
Note
The Analytics service is in preview for Azure DevOps Server 2019. You can enable or install it for a project collection. Power BI integration and access to the OData feed of the Analytics Service are in Preview. We encourage you to use it and give us feedback.
Available data is version-dependent. The latest supported version is v2.0, and the latest preview version is v4.0-preview. For more information, see OData API versioning.
Data available in Analytics
Analytics is generally available for Azure DevOps Service and Azure DevOps Server 2020 and later versions. It is in preview for Azure DevOps Server 2019. The service provides a concise data model over Azure DevOps.
Data available via the Analytics service depends on your version and platform. For specifics, read Data available in Analytics and Data model for Analytics.
Once you've enabled or installed Analytics, the service populates itself with all available Azure DevOps data. Once populated, it updates itself as data changes occur. For more information, read Data available in Analytics and Performance and latency.
Dashboard widgets
You can create dashboards and add widgets to them. We provide several widgets based on Analytics. These widgets take advantage of the power of Analytics. Widgets provide the easiest way to get insights from your data.
For example, the Velocity widget shown in the following image provides insights into a team's historical performance over six iterations.
Here, the Velocity widget shows that this team has a history of closing stories late. It also shows a discrepancy between planned and completed work across all the sprints displayed. The team can drill into the data to determine the root causes. After implementing new practices, the team can use the Velocity widget to track their effectiveness.
Check out Add an Analytics widget to a dashboard for a step-by-step guide to get started with the Velocity widget.
If you want to develop your own widget based on Analytics, see Create an Analytics widget.
Analytic views
Analytics views is a web portal feature that supports filtering work tracking data for status and trend reports. With Analytics views, you can use default or custom views to generate reports in Power BI. Power BI provides a data connector for Analytics views.
For more information, see What are Analytics views?.
Metadata & OData queries
Analytics is fully accessible via OData. From a web browser, you can query the Analytics metadata or data using an OData query. To learn how, see Construct OData queries for Analytics.
If you would like to prepare custom queries and tooling with our OData API, review Sample reports and quick reference index.
Data connectors and Power BI
Power BI is a suite of business analytics tools. The following data connectors have been implemented to support importing data into Power BI.
- Analytics views
- Odata query
- OData feed
With Power BI, you can perform impromptu analysis, produce beautiful reports, and publish dashboards for enterprise consumption.
To get started with Power BI and Azure DevOps Analytics:
- Read the Power BI integration overview
- Check out the Power BI Sample Reports. They'll get you started quickly on the most popular reports.
Support for custom fields and custom work item types
Custom fields and custom work item types are automatically added to the Analytics data model. Through OData queries, you can view the properties and enumerated lists added to the Analytics service based on process customization.