How to Connect Power BI to Azure DevOps

Transforming your Azure DevOps data into insightful reports is easier than you think. While the built-in dashboards are useful, connecting to Power BI gives you the freedom to build completely custom, interactive reports that show exactly what your team and stakeholders need to see. This guide will walk you through the most popular methods for connecting Azure DevOps to Power BI, offering step-by-step instructions and practical tips along the way.

Graphed

Still Building Reports Manually?

Watch how growth teams are getting answers in seconds — not days.

Watch the Demo

Why Connect Power BI and Azure DevOps?

You might be wondering if it's worth the effort. Azure DevOps already has dashboards, right? Yes, but they have their limits. Integrating with Power BI unlocks a new level of analysis and visualization that can give you a much clearer picture of your team's performance, project health, and overall progress.

• Go Beyond Standard Dashboards: Create reports with the exact metrics, charts, and branding you want. Instead of being stuck with pre-built widgets, you have a blank canvas to tell your project's story.
• Analyze Data Across Multiple Projects: Need to see bug trends or team velocity across several projects at once? Power BI makes it simple to aggregate data from your entire organization into a single, unified view.
• Track Historical Trends: Dig deeper into your data to analyze performance over months or even years. You can answer questions like, "Is our sprint velocity improving over time?" or "How has our bug resolution time changed since last quarter?"
• Share Insights with Anyone: Build clean, easy-to-understand reports that are perfect for sharing with stakeholders who aren't in Azure DevOps every day. You can publish reports and dashboards to the Power BI service, making them accessible to leadership and other teams.

Graphed

Still Building Reports Manually?

Watch how growth teams are getting answers in seconds — not days.

Watch the Demo

Before You Begin: What You'll Need

Before connecting anything, let's make sure you have the right tools and permissions in place. A little preparation here will save you a lot of time later.

• Power BI Desktop: This is the free application from Microsoft where you'll build your reports. If you don't have it yet, you can download it from the Microsoft Store.
• Azure DevOps Permissions: To access the Analytics data, you need the right permissions. Your user account must be a member of the project with a Basic access level or higher, and the "View Analytics" permission must be enabled. Typically, if you're a Project Admin or a member of the Contributors group, you'll already have this.
• A Clear Goal: Know what you want to measure. Are you trying to track bug-fix rates, monitor cumulative flow, or analyze release burndowns? Having a specific question in mind will help you focus on the right data from the start.

Method 1: Using Analytics Views (The Recommended Approach)

By far the easiest and most common way to connect Power BI to Azure DevOps is by using Analytics Views. Think of these as pre-filtered, curated datasets that you define within Azure DevOps. This method simplifies the data for Power BI, improves performance, and removes the need to write complex queries.

Step 1: Create an Analytics View in Azure DevOps

First, you'll need to create a view that contains the specific slice of data you want to report on. It's best practice to make your view as specific as possible to avoid pulling in unnecessary data, which can slow down your refreshes.

1. Navigate to your project in Azure DevOps. In the left-hand menu, go to Boards > Analytics views.
2. Click the green "New View" button to start the creation process.
3. Name Your View: Give it a descriptive name that explains what it contains, like "Active User Stories and Bugs - Last 90 Days."
4. Configure the Filters: This is the most important part. You can filter by:
5. Select Fields: In the "Fields" tab, you can choose which data fields to include in your dataset. By default, it includes common fields. You can add more, but remember: the more fields you add, the slower your data will load in Power BI. Be selective!
6. Verify Your View: Before saving, click on the "Verification" tab. Azure DevOps will run a quick test to estimate the number of work items in your view and how long it should take to load. This is a great way to see if your filters are too broad before you commit.
7. Click "Save" when you are finished. Your view will now appear in your list of Analytics views.

Step 2: Connect to the View in Power BI Desktop

With your Analytics View created, it's time to pull that data into Power BI Desktop.

1. Open Power BI Desktop.
2. From the Home ribbon, click Get Data. Select Online Services from the list, then find and choose Azure DevOps (Boards only). Click Connect.
3. A dialog box will appear asking for your organization and project names. Enter them exactly as they appear in your Azure DevOps URL.
4. You will be prompted to sign in with your Microsoft account to authenticate with Azure DevOps.
5. Once connected, the Navigator window will appear. It shows a list of available data sources. Expand the Shared Views folder to find the Analytics View you created in the previous step.
6. Check the box next to your view's name. You’ll see a preview of the data on the right.
7. Click Load. Power BI will import the data from your view, and you'll see the fields appear in the "Fields" pane on the right. You're now ready to start building visuals!

Graphed

Still Building Reports Manually?

Watch how growth teams are getting answers in seconds — not days.

Watch the Demo

Method 2: Using a Direct OData Query (For More Control)

Analytics Views are great for most scenarios, but what if you need more flexibility? If you're comfortable working with more complex datasets or need to access data that isn't available through a simple view, you can connect directly using an OData feed.

This method gives you access to the entire Azure DevOps Analytics data model, but it can be more complex to navigate and slower to refresh if you're not careful with your queries.

Step 1: Get the OData Endpoint URL

The OData URL is the direct link to the analytics service. The format is generally the same for any project:

https://analytics.dev.azure.com/{YourOrganizationName}/{YourProjectName}/_odata/v3.0-preview/

Simply replace {YourOrganizationName} and {YourProjectName} with your specific details.

Step 2: Connect in Power BI Desktop

1. In Power BI Desktop, go to Get Data.
2. Search for and select OData Feed, then click Connect.
3. Paste the OData endpoint URL you constructed in the previous step into the URL field. Click OK.
4. After authenticating, the Navigator window will appear again. This time, instead of seeing simple views, you'll see a list of data entities like WorkItems, Iterations, Projects, and more.
5. Select the entities you need (e.g., WorkItems) and click Transform Data. It is highly recommended to use the Power Query Editor to filter your data at this stage before loading it. For example, you can filter for specific work item types or date ranges to reduce the load on your report.

Graphed

Still Building Reports Manually?

Watch how growth teams are getting answers in seconds — not days.

Watch the Demo

Tips for Building Effective Azure DevOps Reports

Getting the data into Power BI is just the first step. Here are a few best practices to help you create reports that are both powerful and performant.

• Filter Early and Often: The smaller your dataset, the faster your reports will run. Whether you're using Analytics Views or OData, apply filters as early as possible (in the view definition or in Power Query) to remove any data you don't need.
• Understand the Data Model: When using OData, take some time to learn about the key data entities. For instance, the WorkItems entity gives you the current state of all work items, while entities like WorkItemRevisions are needed to track historical changes over time (like cycle and lead time).
• Create Measures with DAX: For calculations, it's better to create measures using DAX (Data Analysis Expressions) formulas rather than creating calculated columns. Measures are calculated on the fly as you interact with your report, keeping your dataset smaller and more efficient.
• Set Up Scheduled Refreshes: Once your report is built and published to the Power BI service, you can schedule it to refresh automatically. This keeps your data current without requiring you to manually refresh and republish every day.

Final Thoughts

Connecting Azure DevOps to Power BI opens up a world of reporting possibilities far beyond the built-in dashboards. Whether you use the straightforward Analytics Views or custom OData queries, you can now build reports that track project health, analyze trends, and communicate progress to your entire organization.

Even though powerful, tools like Power BI often involve a steep learning curve to get right. We've experienced firsthand how time-consuming this can be, especially for marketing and sales teams who just need answers fast. That's why we created Graphed. It allows you to connect all your go-to-market data sources - like Google Analytics, HubSpot, or Shopify - and create real-time dashboards just by asking questions in plain English, helping you get insights in seconds, not hours.