How to Link a Power BI Report to Excel

Connecting a Power BI report to Excel lets you leverage the powerful data modeling of Power BI inside the familiar, flexible environment of a spreadsheet. This guide will walk you through the most effective methods to link your data, whether you need a dynamic, refreshable connection or just a quick data export. We'll cover everything from the classic "Analyze in Excel" feature to the latest connected-table experiences.

Why Connect Power BI to Excel, Anyway?

You've already done the hard work of cleaning, modeling, and visualizing your data in Power BI. So why bring it back into Excel? There are a few very practical reasons:

• Familiarity and Flexibility: Let's be honest - almost everyone knows their way around Excel. It's the perfect tool for quick, ad-hoc analysis, creating one-off tables, or using specific formulas your team relies on without needing to create new DAX measures in Power BI.
• Satisfying Stakeholders: Sometimes, your boss or a client just wants a spreadsheet. Linking Power BI to Excel allows you to provide them with the accurate, governed data they need in the format they prefer.
• Powerful PivotTables: Power BI is great for curated dashboards, but Excel’s PivotTables are legendary for a reason. By connecting to a Power BI semantic model (formerly called a dataset), you get the best of both worlds - a robust data source powering an infinitely flexible PivotTable.
• Combining Data Sources: You might need to combine your trusted Power BI data with a small, local dataset that isn’t part of your official model. Excel makes this easy.

Essentially, this integration lets you use the right tool for the job. Power BI serves as your single source of truth for data, while Excel becomes the ultimate playground for granular exploration.

Before You Begin: What You'll Need

To ensure a smooth connection, make sure you have the following prerequisites sorted out. A missing permission or an outdated app is the number one reason these connections fail.

• A Power BI Pro or Premium License: The features that allow you to connect to external tools like Excel are part of the paid Power BI tiers. A free Power BI license won't cut it.
• Microsoft Office Account: You need to be signed in to Excel with the same work or school account you use for Power BI.
• Excel for the web or Desktop: While a desktop version of Excel (preferably Microsoft 365) provides the best experience, some functionality is also available in Excel for the web.
• Permissions to the Data: You need "Build" permission for the Power BI semantic model (dataset) you want to connect to. If you only have "Read" permissions, you'll be able to view the report but not connect its underlying model to Excel. If the options are greyed out, this is usually the culprit.

Method 1: The Classic "Analyze in Excel"

"Analyze in Excel" is the most well-known method for creating a dynamic link. It generates a PivotTable in Excel that is directly connected to your Power BI data model. When data is updated in Power BI, you can simply hit "Refresh" in Excel to get the latest numbers.

Step 1: Locate Your Report or Dataset in Power BI Service

Sign in to your Power BI account online (app.powerbi.com). Navigate to the workspace containing the report or semantic model you want to analyze.

You can start from two places:

1. From a Report: Open the report. In the top menu, click the dropdown for Export and you'll see the Analyze in Excel option.
2. From a Workspace or Dataset: In your workspace view, find the semantic model (it will have a different icon than the report). Click the three dots (...) for More options and select Analyze in Excel.

Step 2: Start the Analysis and Download the Connection File

After you click “Analyze in Excel,” Power BI will create an Office Data Connection (.odc) file. Your browser will prompt you to download this file. Save it to a memorable location on your computer. This small file contains all the information Excel needs to connect securely to your Power BI data model in the cloud.

Step 3: Open the File in Excel

Find the downloaded .odc file and open it. Excel will launch automatically. For security purposes, it will likely show a yellow warning bar asking if you want to enable the data connection. Click Enable.

Step 4: Build Your PivotTable

Success! You now have a blank PivotTable in your Excel sheet. On the right side of the screen, the PivotTable Fields pane will be populated with all the tables, columns, and measures from your Power BI model.

You can now drag and drop these fields into the Rows, Columns, Values, and Filters areas just like you would with any other PivotTable. The key difference is that this data isn't stored in your worksheet, it's being queried directly from the Power BI service in real-time. Simply click the "Refresh All" button under the Data tab in Excel to pull in the latest data whenever the Power BI dataset is updated.

Method 2: Export Data Directly from a Visual

What if you don't need a whole PivotTable? Sometimes, you just want the raw data behind a specific bar chart, table, or matrix in your report. This method is for when you need a quick, static snapshot.

Step 1: Open Your Report and Find the Visual

Navigate to the Power BI report and locate the specific visual from which you want to export data.

Step 2: Access the Export Option

Hover your mouse over the visual. A few icons will appear in the top-right corner. Click the three dots (...) for More options. In the dropdown menu that appears, select Export data.

Step 3: Choose Your Export Format

A dialog box will pop up offering a few choices:

• Data with current layout (.xlsx): This option exports the data exactly as it appears in your visual - the summarized values. This is great for quickly grabbing data from a pre-formatted table. This format has a limit of 150,000 rows.
• Summarized data (.csv): This also gives you the summarized data, but in a universal .csv format. The row limit here is 30,000.
• Underlying data (.xlsx): If enabled by the report creator and your permissions allow it, this option gives you the detailed, row-level data that makes up the visual. This is incredibly useful for deep-dive analysis but is often limited to a large row count (typically 150,000 rows in most scenarios).

After making your selection, click Export. Your file will download, ready to be used. Just remember, this is a one-time static export. It is not connected to your Power BI model and will not update if the source data changes.

Method 3: Linking Data with "Connected Tables"

This is a more modern and integrated approach available in recent versions of Excel for Microsoft 365. Instead of confining you to a PivotTable, it allows you to pull tables of data directly into your Excel grid as a refreshable, connected table. This is often called "insertable data tables" or "connected tables."

Step 1: Start from Inside Excel

Open a blank Excel workbook. Go to the Data tab on the ribbon. Click Get Data > From Power Platform > From Power BI.

Note: If you don't see this option, you might need to update your version of Office or your organization might have it disabled.

Step 2: Choose Your Dataset

A Power BI pane will open on the right side of your Excel window, listing all the semantic models you have access to. You can browse or search to find the one you need.

When you click on a dataset, it will expand to show you all the tables and interactive report elements available within it. You can pick and choose columns to create your own custom table or insert a pre-built table from a report visual.

Step 3: Insert the Table into Excel

Once you've selected your desired data, click the Insert Table button. The data will be dropped directly into your spreadsheet as a standard Excel table. The magic is that this table is directly connected to Power BI. You can right-click anywhere in the table and select Refresh (or use the Refresh All button on the Data tab) to pull in new data.

You can also see information about the connection, such as the last refresh time, from the right-hand Datasets pane.

Quick Tips & Troubleshooting

• "Analyze in Excel Option is Greyed Out": This almost always means you don't have Build permissions for the underlying semantic model. Ask the owner of the dataset to adjust your access level in the Power BI service.
• Give Your Measures Good Names: The names you give your columns and measures in your Power BI model are what will show up in the Excel PivotTable Fields. Clear, descriptive names will make analysis much easier for your end-users.
• Live Connection vs. Export: Be clear with your team about the difference. "Analyze in Excel" and "Connected Tables" (Methods 1 & 3) create a live, refreshable link. Exporting data from a visual (Method 2) is just a static snapshot in time.
• Check Your Excel Version: The best experience with full connectivity is on Microsoft 365. Older, static versions of Excel may have limited or no functionality for connecting to Power BI.

Final Thoughts

Connecting Power BI and Excel bridges the gap between structured, governed reporting and flexible, self-service data exploration. Whether you're using Analyze in Excel to feed a powerful PivotTable, inserting a Connected Table for refreshable reports, or just exporting raw data for a quick check, you are extending the value of your data model and empowering teams to find insights in the tools they know best.

While connecting Power BI to Excel streamlines analysis, it often involves moving data between apps for manual digging. This is why we created Graphed. We wanted to skip the CSV downloads and eliminate the need to jump between different tools. By connecting your sources like Google Analytics, Shopify, and Salesforce directly, anyone on your team can create live dashboards and get analysis simply by asking questions in plain English - no extra steps, no exports, and no complex BI software required.