Getting Started with Power BI Desktop

Abhishek Baxi

Power BI Desktop lets you build data models and reports to visualize data while allowing you to share your work by publishing to the Power BI service.

Power BI Desktop is a free download – no you don’t need an Office 365 subscription or anything. You can download it directly as an MSI package (Windows 7/Windows Server 2008 R2, or later) or install the app from the Microsoft Store. The latter of course brings you automatic updates and does not require administrator privileges for installation.

Note that installing the downloaded version and the store version of Power BI Desktop on the same computer (side-by-side installation) is not supported.

To get started with Power BI Desktop, let’s walk through the steps to connect to some data and put it into a report.

In the Power BI Desktop app, click Get Data to begin, and open the sample dataset (I used a sample Excel file on Trump’s approval rating for this article). Power BI Desktop will connect to the Excel sheet and show you the data that’s within the spreadsheet, and you’d need to select the table that you wish to work with, and click Load.

The Power BI Desktop then connects to the spreadsheet and reads the rows of data and you can find the list of columns available under Fields. All you need to start building visualizations based on this data is select the fields you want to visualize, and then click on any visualization under the Visualizations tab to add it to the canvas (the empty white area). Just drag and drop!

You could alter the axis and add more than one visualization with the same data. Power BI understands your data and will plot the charts as you move between the available options. If you hover over any of the data values on the chart, a window will appear showing you the specific values.

There are several options available to customize the presentation and slice the data. Make sure you go through those in the Visualizations tab to get a hang of Power BI Desktop.

In the next tutorial, we’ll finalize the chart we need, and publish it to Power BI Service. Stay tuned!