Power BI Excel Connection: 5 Easy Steps


Power BI Excel | Hevo Data

One of the most common ways to collect and maintain data in organizations is through Excel sheets. But getting deeper insights from Excel may not always be possible, especially when you are dealing with massive volumes of data. To remedy this, you can use data visualization tools such as Power BI.

You can easily set up the Power BI Excel connection and start making attractive reports and dashboards. Using the simple UI, you can import data from your excel files and begin designing your reports. Power BI has a huge collection of charts, graphs, etc that can be customized according to your business needs.

In this article, you will learn how to effectively set up the Power BI Excel connection in 5 easy steps. 

Table of Contents

What is Power BI?

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Power BI is a data visualization and business intelligence tool that transforms data from a variety of data sources into interactive dashboards and BI reports. The Power BI suite offers multiple software, connectors, and services Power BI Desktop, Power BI services based on SaaS, and  Power BI mobile apps available on a variety of platforms. This set of services is used by business users to consume data and create BI reports.

Key Features of Power BI

  • DAX Functions: The DAX function is a Data analysis expression included in PowerBI. These analytic functions are predefined codes for performing analytics-related operations on your data. Currently, there are about 200 functions in the PowerBI function library.
  • Data Security: Power BI Protects your data with industry-leading data security features such as sensitivity labeling, end-to-end encryption, and real-time access monitoring.
  • Flexibility: Power BI allows you to extract data from a variety of sources. For instance, you can easily set up the Power BI Excel Connection and visualize excel data in Power BI. From On-premise to Cloud-based databases, structured to unstructured data Power BI allows you to work with a broader range of datasets. 
  • Data Filteration: In Power BI, you can create data subsets from several databases and work only on the filtered data that has contextual relevance.

What is Excel?

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Microsoft Excel is a spreadsheet application developed by Microsoft to organize and record data in a tabular format. Launched in 1985, Microsoft Excel is a widely used Spreadsheet software in businesses worldwide allowing you to organize and manipulate data through formulas in columns and rows. MS Excel is loaded with functionalities to perform several operations such as calculations, pivot tables, graph tools, etc.

Compatible with Microsoft Windows, macOS, Android, and iOS, MS Excel is included with the MS Office Suite. It is typically used by firms to record, organize and analyze financial data. MS Excel also offers VBA programming that can assist you in automating repetitive tasks.

Key Features of Excel

  • Conditional Formatting: MS Excel allows you to apply formats to a cell or range of cells, and have that formatting change depending on the value of the cell or the value of a formula.
  • Built-in Formulae: MS Excel provides you with basic and advanced built-in formulae for sum, average, minimum, etc. You can use formula auditing to graph or trace the relationship between cells and formulas with blue arrows. You can track precedents (cells that provide data for a particular cell) or the cells that depend on the value of a particular cell. 
  • Data Protection: Excel spreadsheets can be password protected on your laptop or PC. MS Excel also provides a robust system to recover data.
  • Data Sorting & Filtering: You can easily perform the basic data sorting and filtering operation on your data in excel. MS Excel also provides Advanced filtering options for complex criteria.

What are the benefits of setting up Power BI Excel Integration?

Setting up the Power BI Excel Integration can help assist you in the following aspects:

  • Deal with large volumes of data: Power BI has great compression capabilities for Microsoft Excel and text / .csv files that allow you to view, analyze, and visualize large amounts of data that cannot be opened in Excel. Most computers have a hard time opening a 300MB .csv file, which makes it difficult to analyze and report in Excel.
  • Analyze Trends Quickly: Analyzing trends with Power BI is very easy. With built-in time intelligence analysis features, it only takes a few seconds to view massive amounts of data. You can see data by various dimensions and attributes, including date and time dimensions.
  • Share your Reports: You can now publish to a secure Microsoft cloud service called Power BI Service and automate basic data updates. Just click Publish in the upper-right corner of the Power BI home feed. You can then easily share these reports with your colleagues and collaborate with them.
  • Visualization Made-Easy: The great thing about Power BI is that with basic design ideas, it allows you to easily create something visually appealing and neat. Drag-and-drop functionality, easy resizing, and copy and paste make it feel like you’re at home for those familiar with the Microsoft Office suite.
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What are the Steps to Export data from Power BI to Excel?

Power BI provides a beginner-friendly interface to quickly load data from Excel and start visualizing it. To begin setting up the Power BI Excel Integration, ensure that you have Power BI installed on your system. If not done already, you can download Power BI Desktop. You can start building the Power BI Excel Integration by following the simple steps given below:

Power BI Excel Connection Step 1: Extract Data

  • Step 1: For this Power BI Excel Connection article, you download a sample Financial Excel Workbook. You can also work with any of your Excel workbooks.
  • Step 2: Open Power BI Desktop. Navigate to the Home ribbon and click on the Excel option present in the Data section.
  • Step 3: Go to the folder where you have saved your workbook and click on the Open button after selecting the file.

Power BI Excel Connection Step 2: Prepare Your Data

Now, a Navigator window will pop up on your screen. It displays an overview of the data so you can be sure that the range of the data is correct. For instance, all the numeric data types are shown in italics. Navigator allows you to transform your data before loading it. Transforming the data can often assist you in creating visualizations that are easier to understand. Follow the steps given below to perform various transformations:

  • Step 1: Check the box next to Financials and click on the Transform Data button.
  • Step 2: In the given sample data, values of units sold in decimal don’t make sense. Hence, you can transform it into whole numbers. Select the Units sold column and navigate to Transform Tab > Data Type > Whole Number. Click on the Replace current option to change the data type. 
  • Step 3: To make the segments easier to observe in the visualizations, later on, you can change its format to uppercase. To do that, select the Segments column and navigate to Transform tab > Format > UPPERCASE.
  • Step 4: You can shorten the Month Name Column header to Month by just double-clicking the Month Name column, and renaming it to just Month.
  • Step 5: For this sample data, it is assumed that the Montana product was discontinued last month, so you can filter this data from your report to avoid confusion. To do that, go to the Product column. Click on the dropdown and clear the box next to Montana.

You can now observe that each transformation has been added to the list under Query Settings in Applied Steps.

  • Step 6: Since your data is now prepared, you can go to the Home tab and save the modification by clicking on the Close & Apply option.

You can also notice that Power BI has recognized various filed such as Sales, Discounts, etc of numeric data types by placing a Sigma symbol. It has also denoted the Date field as a Date time entity by placing a Calendar icon.

Power BI Excel Connection Step 3: Generate Your Report

After the data preparation step of the Power BI Excel Connection, you can now move toward creating your reports. To do that, follow these simple steps:

  • Step 1: Go to the Insert ribbon on the top, and click on the Text Box option. You can now type the title for this report as “Executive Summary – Finance Report”.
  • Step 2: Select the text you typed and set the font size to 20 and bold. You can also resize the box for the text to be in one line.
  • Step 3: To create a line chart to see which month and year had the maximum profit, go to the Fields pane. Drag the Profit field to a blank area on the report canvas. You will notice that Power BI displays a column chart with one column, Profit.
  • Step 4: Similarly, drag the Date field. You now will see the profit columns for 2 years.
  • Step 5: To view profits for each month, go to the Fields section of the Visualizations pane. Click on the drop-down in the Axis value and change Date from Date Hierarchy to Date.

Now, Power BI will display profits month-wise.

  • Step 6: You can change the bar chart to a line chart from the Visualization pane.
  • Step 7: To see which country had the highest profits, drag the Country field from the Fields pane to a blank area on your report canvas to create a map. Then, drag the Profit field to the map.
  • Step 8: You can also find out which companies and segments to invest in. To do that, first, you can create some space by dragging the two charts you’ve built to be aligned side by side in the top half of the canvas.
  • Step 9: Click on the blank area in the lower half of your report canvas and select the Sales, Product, and Segment fields from the Fields pane. After you observe a chart, you can drag it to fill the space under the two upper charts.
  • Step 10: A slicer is an effective tool for filtering report page visual elements for certain selections. In this case, you can build two different slicers to narrow down the performance for each month and each year. The slicer uses the date field of the original table. You can drag the Date option from the Fields pane to the blank area on the left of the canvas.
  • Step 11: Now, select Slicer from the visualization pane. You can also drag the ends to filter, or select the arrow in the upper-right corner and change it to a different type of slicer.

Power BI Excel Connection Step 4: Format Your Report

After preparing the basic report in the 3rd step of Power BI Excel Connection, you can start modifying its format for better visualization:

  • Step 1: You can change the theme to Executive from the View pane.
  • Step 2: You can also make specific changes to your graphs and charts individually in the Format tab of the Visualizations pane. Select Visual 2 (profits by month & year graph) and change the title text in the title section to “Profit by Month and Year” and Text size to 16 pt with the Toggle Shadow set to On. 
  • Step 3: Similarly for Visual 3, change the Theme to Grayscale in the Maps section. Like Visual 2, change the title Text size to 16 pt with the. Toggle Shadow set to On for both Visual 3 & 4.
  • Step 4: For Visual 5, go to the Selection controls section & toggle the “Select all” option to On. In the Slicer header section, set the Text size to 16 pt.
  • Step 5: You can also add a background for the title. For that, go to the Insert ribbon on the top and navigate to Shapes > Rectangle. You can place the rectangle at the top of the page, and stretch it according to the width of the page and the height of the title.
  • Step 6: Go to the Format shape pane, in the Outline section and set the Transparency to 100%. You can also set the Fill color to Theme color 5 #6B91C9 (blue).
  • Step 7: Now navigate to the Format tab and select Send backward > Send to back. For the title to appear clearly, select the text in Visual 1, the title, and change the font color to White.
  • Step 8: Similarly, create and place the rectangle shape for Visuals 2 & 3. Here also, change the Transparency to 100%. & set the color to White 10% darker in the fill section. Finally, go to the Format tab & select Send backward > Send to back.

Power BI Excel Connection Step 5: Save Your Report and Publish to Power BI Service

Coming to the last Power BI Excel Connection Step, you can now save this report by going to the File menu and clicking on the Save option.

Power BI allows you to share your reports with your colleagues via its Power BI service. This allows Power BI account holders to interact with your report but they can’t save changes. To publish your report, follow these steps:

  • Step 1: Go to the Home ribbon and click on the Publish option. If you don’t have a Power BI service account, you can opt for a free trial also.
  • Step 2: You need to choose a destination such as My workspace in the Power BI service > Select.
  • Step 3: Click on the Open ‘your-file-name’ in the Power BI option.

This will open your report in the browser.

  • Step 4: Click on the share icon at the top of your report to share it with your colleagues. This completes setting up your Power BI Excel Connection.

How to Connect to Power BI Datasets with Analyze in Excel?

Another aspect of Power BI Excel Integration is bringing Power BI Datasets to Excel using the Analyse in Excel feature. You can then view and interact with them using PivotTables, charts, slicers, and other Excel features.

Steps to Establish Power BI Excel Connection

Follow these simple steps to easily set up the Power BI Excel Connection and analyze your data in Excel:

  • Step 1:  In the Power BI Service, go to the dataset or report you want to analyze in Excel. Click on the More options (…) next to the dataset or report name and select Analyze in Excel.
  • Step 2: Another way for the Power BI Excel Connection is by opening the report and selecting Export > Analyze in Excel.
  • Step 3: You can also select a dataset and then click on the Analyze in Excel in the menu bar of the Dataset details pane.
  • Step 4: Using any of the above Power BI Excel Connection steps, the Analyze in Excel feature should install automatically. Finally, click on the Download button.

A new Excel workbook will be downloaded to your system that contains an OLAP connection to a Power BI dataset.

After opening the file, you may have to Enable Editing & Enable Content depending on your systems settings.

Limitations of Analyze in Excel 

Though Analyze in Excel is an excellent feature for utilizing Power BI Excel Integration, there are some challenges that you might encounter:

  • Some firms may have Group Policy rules that prohibit the installation of required updates for Excel. If you are unable to install the update, please contact your administrator. 
  • Row-level security (RLS) is supported for Analyse in Excel. RLS is applied at the data model level and to all users who access the data in the report. 
  • When using Analyze in Excel, you may get unexpected results or the function may not work as expected. 
  • Only PowerBI datasets that use import mode maintain hierarchies in Excel workbook analysis. When using Analyze in Excel, the hierarchy of PowerBI datasets created with DirectQuery or composite models is not preserved. 
  • While using Analyse In Excel, you cannot change the connection string to specify the locale after the workbook is generated. 
  • When data exceeds 2GB, an error message may be displayed. In this case,  you can reduce the amount of data by applying a filter or using an XMLA endpoint. 
  • For guest users,  Power BI data can’t be analyzed in Excel for datasets sent (from) by another tenant.  
  • Analyzing PowerBI data in Excel is a PowerBI service feature. It is not possible to analyze Power BI data in Excel using Power BI Report Server or Power BI Embedded.

What are the Limitations to Importing an Excel Workbook in Power BI?

While trying to set up the Power BI Excel connection, there are some challenges that you may face when you import an Excel Workbook in Power BI:

  • External Connections to SQL Server Analysis Services Tabular Models: Excel 2013 allows you to connect to SQL Server Analysis Services tabular models and create PowerView reports based on those models without having to import the data. This connection type is not currently supported when importing an Excel workbook into Power BI Desktop. Alternatively, you need to recreate these external connections in Power BI Desktop.
  • Hierarchy: Power BI Desktop doesn’t support this type of data model object. Therefore, when you import an Excel workbook into Power BI Desktop, the hierarchy is skipped.
  • Binary Data Columns: This data model column type is not currently supported by Power BI Desktop. The binary column of data is removed from the Power BI Desktop result table. 
  • Unsupported PowerView Elements: PowerView has some features that are not available in Power BI Desktop like Themes or specific types of visualizations (scatter plots using playback axes, drill-down behavior, etc.). These unsupported visualizations display unsupported visualization messages in the appropriate places in Power BI Desktop reports that you can edit or omit as needed. 
  • Named range using PowerQuery’s FromTable or M’s Excel CurrentWorkbook: Importing this named range data into Power BI Desktop is not currently supported, but is a planned update. These named ranges are now loaded into Power BI Desktop as a connection to an external Excel workbook.  
  • PowerPivot to SSRS: External PowerPivot connections to SQL Server Reporting Services (SSRS) are not currently supported because this data source is not currently available in Power BI Desktop.


In this article, you have learned how to effectively set up the Power BI Excel integration. Power BI Excel connection enables you to easily import data from Excel and gets you started with your report generation in minutes. With a user-friendly interface and a vast collection of visualization features, you can create visually stunning and informative dashboards and reports.  

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Tell us about your experience of setting up the Power BI Excel Connection! Share your thoughts with us in the comments section below.

Sanchit Agarwal
Research Analyst, Hevo Data

Sanchit Agarwal is an Engineer turned Data Analyst with a passion for data, software architecture and AI. He leverages his diverse technical background and 2+ years of experience to write content. He has penned over 200 articles on data integration and infrastructures, driven by a desire to empower data practitioners with practical solutions for their everyday challenges.

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