Using Power BI to visualize Edge data sent to Azure IoT Hub

Introduction

Azure IoT Runtime enables you to collect information and execute commands on Edge devices remotely. When installed on e-RT3 Plus, the features of both e-RT3 Plus and Azure Runtime Environment can be utilized to perform various operations.

This is the last part of a five-part series that demonstrates how to use Azure Runtime Environment with e-RT3 Plus. The first two parts describe how to use Azure IoT Runtime environment to create and deploy Azure IoT Edge Python modules that read and upload data to an IoT Hub. In the first part we read data from a sample temperature module, in the second part we read data from an Analog Input Edge device.

• Deploying a sample Python module on an Edge Device installed with Azure IoT Edge Runtime
• Create an Azure IoT Edge Python module to gather data from an Edge device and transmit it to the IoT Hub

The third part describes creating and deploying an Azure IoT Edge Python module that writes data to an Edge device.

• Create an Azure IoT Edge Python module that writes data to an Edge device

The fourth part describes visualizing the data received at the IoT Hub using a web application created by using Azure App Service.

• Using Azure App Service to visualize Edge data sent to Azure IoT Hub

In this article, we visualize the data received at the IoT Hub by using Power BI. To send the data to Power BI, an Azure Stream Analytics job is created which connects to the Power BI workspace. The data visualizations are then configured in the designer of Power BI.

The ultimate goal for this article series is to demonstrate how to:

1. Create a Python data collection module to gather data, process it and upload it to IoT Hub
2. Create a Python module for writing data to an Edge device
3. Visualize the collected data using Azure App Service and Power BI.

This article is based on the Microsoft tutorial Visualize real-time sensor data from Azure IoT Hub using Power BI. For more information about installing and deploying Azure IoT Runtime environment, refer to Deploying Azure Runtime Environment on e-RT3 Plus.

Hardware modules

The following table describes the hardware modules used in this article.

The module configuration and wiring is the same as described in the previous article.

For more information on the hardware modules, refer to this page.

Note: The IoT Edge module development and device operations are performed on Windows 10 using Google Chrome as the web browser.

Prerequisites

Before trying to visualize the data in the IoT Hub using Power BI, you must complete the steps mentioned in the previous articles Create an Azure IoT Edge Python module to gather data from an Edge device and transmit it to the IoT Hub and Create an Azure IoT Edge Python module that writes data to an Edge device.

Workflow

To visualize the data sent to the IoT Hub in Power BI, you must complete the following:

1. Install Power BI
2. Create IoT Hub consumer group
3. Create Stream Analytics
4. Configure Stream Analytics settings
5. Configure and visualize data in Power BI

Installing Power BI Desktop

Power BI is a data analytics and reporting tool from Microsoft that helps you to visualize data. You can use it as a desktop application with Power BI Desktop or as a web service with Power BI service. In this demonstration, we use Power BI Desktop which is signed into a personal account.

Note: The steps described in this article are the same if you use Power BI Desktop with a corporate account.

Follow these steps to install Power BI Desktop on your computer:

1. Navigate to the official website and click Download free.

   The Open Microsoft Store dialog box appears.

2. Click Open Microsoft Store.

3. In the Microsoft Store window that opens, click Get to download the installer.

4. Install Power BI and open it.

5. To sign in, in the upper-right corner, click Sign-in and follow the instructions displayed.
   

Creating IoT Hub consumer group

To create a IoT Hub consumer group from Azure Portal, follow the steps mentioned in the previous article. For this demonstration, we have created a consumer group with the name ert3-visualization-powerbi.

Note: Ensure that you save the name of the consumer group as you will need to use it later.

Creating Stream Analytics

To send data from the IoT Hub to Power BI, we create a Steam Analytics job in Azure Portal.

Follow these steps to create a stream analytics job:

1. Navigate to Azure Portal.
2. In the upper left corner of the page, click Create a resource.

3. In the search box, type Stream Analytics job and select the same from the search results.

   

4. Click Create.

5. Configure the mandatory details as shown in the following table.

   Parameter	Value
   Project details - Subscription	Select any existing subscription
   Project details - Resource Group	Create a new Resource Group or select any existing Resource Group
   Instance details - Name	Specify any unique name
   Instance details - Region	Select any region as applicable
   Instance details - Hosting environment	Select Cloud
   Streaming unit details - Streaming unit	In this demonstration, as we are not using any special processing for the stream data, streaming unit 3 is sufficient.

   

   Note: Stream Analytics usage is billed based on the start time and the number of streaming units. For more information on pricing, click here.

6. Click Review + create.

7. After verifying the configured information, click Create.

A message is displayed indicating that the Stream Analytics job is deployed.

Configuring Stream Analytics settings

Follow these steps to configure the settings for the Stream Analytics job:

1. Navigate to Azure Portal and open the Stream Analytics job that you created.

   The overview page appears.

   

2. To add an input to the Stream Analytics job, perform these steps:

   1. Click Add input and select IoT Hub from the drop-down list.
      The IoT Hub pane appears.

      

   2. Configure the parameters as shown in the following table.

      Parameter	Value
      Input alias	Specify any name to use as an alias
      Subscription	Select the Azure subscription that you are using for the IoT Hub from which you want to visualize data
      IoT Hub	Select the IoT Hub from which you want to to visualize data
      Consumer group	Specify the consumer group created in Creating IoT Hub consumer group

   3. Click Save.

      The IoT hub is added to the input list and a message is displayed indicating that the connection test is successful.

3. To add an output to the Stream Analytics job, perform these steps:

   1. From the overview page, click Add output and then select Power BI from the drop-down list.

      The Power BI - New output pane appears.

      

   2. Select Authorize and follow the instructions displayed to sign in to your Power BI account.

      

   3. After you sign in to Power BI, configure the parameters as shown in the following table.

      Parameter	Value
      Output alias	Specify any name to use as an alias
      Subscription	Select your target group workspace
      Dataset name	Specify a dataset name
      Table name	Specify a table name

   4. Click Save.
      The Power BI settings are added to the ouput list and a message is displayed indicating that the connection test is successful.

4. To configure the query for the Stream Analytics job, perform these steps:

   1. On the left pane, under Job topology, select Query.

      

   2. In the editor that appears, type the query as follows:
      

      SELECT
      messageID,
      deviceID,
      CAST([datetime] AS datetime) AS datetime,
      ch1, ch2, ch3, ch4, ch5, ch6, ch7, ch8
      INTO
      [<Set output alias>]
      FROM
      [<Set input alias>]
      

   3. Click Save query.

      A notification appears indicating that the settings are saved.

5. To start the Stream Analytics job, from the overview page, click Start.

   After the job is started successfully, the job status changes from Stopped to Running.

Configure and visualize data in Power BI

Follow these steps to visualize the data in Power BI:

1. Open Power BI Desktop.

2. From the menu bar, select Home > Get data >Power BI Datasets.

   The Data hub page appears.

   

3. Select the dataset that you specified in step 3 of Configuring Stream Analytics settings.

   The data set is loaded and the designer appears. The Filter, Visualizations, and Fields panes appear on the right.

   

4. To design the visualization chart, perform these steps:

   1. To visualize the data in a particular channel, in the Fields pane, select the checkbox next to channel name.

   2. In the Visualizations pane, select the Line graph icon. You can resize the chart screen displayed in the centre as necessary.

      The sum of values is displayed, since the horizontal axis is not yet configured.

      

   3. On the Fields pane, select the datetime check box and drag it to the X-axis section in the Visualizations pane.

      The date and time is displayed on the horizontal axis.

   4. In the Filters pane, expand datetime.

   5. From the Filter type drop-down list, select Relative time.

   6. From the Show items when the value drop-down list, select is in the last.

   7. In the value box, type 5.

   8. From the drop-down list, select minutes

      The chart is updated to display data from the last five minutes.

      

5. To refresh the data displayed on the chart click Update.

   If the visualization is successful, the following chart is displayed.

   

6. To stop sending data, after the verification is complete, in Azure Portal, expand the Stream Analytics job summary and click Stop.

Note: The Stream Analytics billing is calculated based on operation time and streaming units.

Conclusion

The data that is sent to the IoT Hub is visualized in Power BI Desktop. This concludes the article series that demonstrates how to use Azure IoT Runtime to send data to IoT Hub from an Edge device, write data to an Edge device, and visualize the data in Power BI and Azure App Service.

References

1. Real-time OS controller e-RT3 Plus F3RP70-2L
2. Azure Certified Device catalog
3. Visualize real-time sensor data from your Azure IoT hub in a web application
4. Tutorial: Visualize real-time sensor data from Azure IoT Hub using Power BI