Using Power BI Desktop to Create Data Visualizations and Explore Data


In previous posts, I discussed how to create an Azure SQL Database using data from the City of Chicago Data portal. (See previous posts on this blog for more information) Part of the process was showing how Microsoft Excel can be used in conjunction with Power Pivot and Power View in order to create data visualizations. Using tools such as Excel to build visualizations is very practical because many people are comfortable working with Excel, and sharing the data visualizations is a matter of simply sharing the Excel workbook. There are, however, situations where a richer design canvas is required, or you want to publish your visualizations to a wide audience that may not have Excel installed.

Microsoft has recently released the Power BI Desktop, a tool that will allow you to create full-featured data visualizations on your desktop, and then publish them to the Power BI service (which has a free tier as well as a professional, paid tier) allowing you to share your visualizations with anyone that has a web browser and Internet connectivity.

Downloading and Installing Power BI Desktop

Before attempting to install the Power BI Desktop application, read through the system requirements to make sure that your system will support it. To download, click on the download button on the Power BI Desktop page: https://powerbi.microsoft.com/desktop Save the file to a local folder and then double-click to install. Follow the instructions on the screen and install the Power BI Desktop application along with any pre-requisites that the installer determines that it needs. Once the install completes, start Power BI Desktop which will open the following screen:

Once the application starts, you are ready to build your first dashboard. For the purposes of this post, we'll recreate the visualizations that we built from the same data source using Excel Power View. (See Part 3 in my previous posts)

Connecting to Azure SQL Database and Loading Data

Click on the Get Data button and select the Microsoft Azure SQL Database option.

Click the Connect button and then enter your Azure SQL Database Server and Database information and then click OK.

When prompted, select Database Authentication and enter your connection credentials.

If you receive an error related to the firewall rules, follow the instructions from Managing the Database in Part 1 and then click the Refresh Preview button to refresh the data connection. If you do not receive an error, skip to the Navigator section below.

Once the refresh is complete you will see a list of objects in the database (which will look slightly different than the picture below as there are more objects in my database than what I've documented in previous posts)

On the Close & Load button, select Close to return to the blank canvas. When the canvas loads, select the Recent Sources button and select your database connection. This will open the Navigator.

Select the ChicagoCrimes, Community, DateDimension, PoliceStations and SocioEconomicFactors tables and then click the Load button.

The data load will start (during this process, Power BI Desktop is loading the data into a local Data Model that is using the same xVelocity data engine that Power Pivot uses) and will take some time to complete.

Once the data is loaded, we will want to ensure all of the appropriate relationships are in place and will also use the DAX language to create a very simple calculated measure to ensure that appropriate visualizations are easy to create. You will also want to click the Save command to save the data model at this time.

Managing Data Relationships

When the data load completes, you'll be returned to the Power BI Desktop canvas. You will want to verify that the relationships between the fact table and dimension tables were properly detected. (At the time I'm writing this article, there is an issue with Power BI Desktop where it did not detect the relationship between the DateDimension table and the ChicagoCrimes fact table). Click on the Relationships icon on the left side (the bottom button) to open the data diagram view.

If there are any missing relationships (in the image above, the relationship between the ChicagoCrimes table and the DateDimension table is missing), click the Manage Relationships button on the ribbon to open the Manage Relationships dialog.

Click New to create a new relationship. Select the ChicagoCrimes table from the first drop-down, and then highlight the DateOnly column. In the next drop down select the DateDimension table and verify that the Date column is selected. And then select OK.

Select Close and verify that the relationship has been created. When all the relationships are created, the data model should look like this:

 

Once the relationships are properly created, we'll want to add a calculated measure to simplify the creation of visualizations using the model.

Creating a New Calculated Measure

For the purposes of this post, we will create a very simple calculated measure that provides a count of the number of crime reports in the data. To create the measure, we'll use the DAX language (that is typically thought of as a Power Pivot language, but since Power BI Desktop uses the same engine, the language is used here as well) to create the measure.

Select the Data icon on the left side (the middle icon) to open the data view, and ensure that the ChicagoCrimes table is selected in the Fields area on the right.

Click the New Measure button in the ribbon to enable the formula bar. Enter the DAX expression TotalReports = COUNT([ID]) and then click the checkmark icon to ensure that the expression is correct.

 

Once the new measure is created, we will want to make a change to the data type of the Year column in the DateDimension table to ensure that appropriate reports can be easily created. Because Power BI Desktop is designed to minimize errors and simplify the creation of reports, there are sometimes manipulations to the data that need to be made in order for Power BI to properly render visualizations of that data. In the case of the DateDimension table, we will want to use the Year column as an axis in a timeline. Because the Year column is currently defined as an Integer type, PowerBI Desktop will consider that column a measure and will make it difficult to use on a chart axis. The simple workaround is to change the data type of the column to Text.

In the fields section, select the DateDimension table and then select the Year column. From the ribbon, change the Data Type to Text.

Once these changes are made, you are ready to create a report based on the model.

Creating a Report

For the purposes of this post, we'll recreate the visualization that was created in Excel Power View in Part 3 of the earlier blog series. Click the Report icon on the left side (the top icon) to open the report design canvas.

From the Fields area, select the TotalReports measure in the ChicagoCrimes table and then expand the DateDimension table and select the Year column. A column chart will be created on the canvas.

In the Visualizations area, select the Line Chart icon to change the visualization to a line chart. On the canvas, click a blank area and then in the Fields section, select the TotalReports measure as well as the Location Description field in the ChicagoCrimes table. On the canvas, drag the resulting visualization to the right of the line chart and resize it appropriately.

With the new chart selected, in the Visualizations area select the Bar Chart icon to change the visualization type to a bar chart. On the Bar chart, click the ellipsis (3 dots in the upper right) and sort the chart by the TotalReports field.

Click in a blank area on the canvas and then in the Fields area, select TotalReports from the ChicagoCrimes table and then expand the Community table and select the Communityad field. In the Visualizations area select the Map icon to change the visualization to a map, and then from the Fields area drag the Communityad field to the Location area under Visualizations. Resize the visualization appropriately.

 

After completing all of the steps above you will have a report that details all types of crime reports in Chicago from 2001 until the last date you loaded into your database. To filter the date to a specific type of crime, drag the Primary Type field from the ChicagoCrimes table to the Page Level Filters area under Visualizations. To replicate the report that was created in Excel, select the Homicide type in the filter.

Conclusion

In this blog post, we created a report using Power BI Desktop that connected to a Microsoft Azure SQL Database and detailed Homicides in the City of Chicago from 2001 until the last day of data that you loaded into your database.

Power BI Desktop is a powerful data analysis and visualization tool that allows you to gain insight from your data very quickly, and also share that insight by posting reports to the Power BI Service (future posts will discuss posting reports to the Power BI service).

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