Visualise data in Power BI

End-to-end diagram

Before you start this tutorial, make sure you’ve completed Setup your device. By Setup your device, you set up your IoT device and IoT hub, and deploy a sample application to run on your device. The application sends collected sensor data to your IoT hub.

What you learn

You learn how to visualize real-time sensor data that your Azure IoT hub receives by Power BI. If you want to try visualize the data in your IoT hub with Web Apps, please see Use Azure Web Apps to visualize real-time sensor data from Azure IoT Hub.

What you do

• Create, configure and run a Stream Analytics job for data transfer from your IoT hub to your Power BI account.

• Create and publish a Power BI report to visualize the data.

What you need

• Tutorial Setup your device completed which covers the following requirements:

  • An active Azure subscription.

  • An Azure IoT hub under your subscription.

  • A client application that sends messages to your Azure IoT hub.

• A Power BI account. (Try Power BI for free)

Video Tutorial

Visualise Streaming Sensor Data in Power BI

Create, configure, and run a Stream Analytics job

Create a Stream Analytics job

1. In the Azure portal, click New > Internet of Things > Stream Analytics job.

2. Enter the following information for the job.

   Job name: The name of the job. The name must be globally unique.

   Resource group: Use the same resource group that your IoT hub uses.

   Location: Use the same location as your resource group.

   Pin to dashboard: Check this option for easy access to your IoT hub from the dashboard.

3. Click Create.

4. Select Create and you should see a Deployment in progress... notification displayed in the top right of your browser window.

5. Check the Pin to dashboard box to place your job on your dashboard when the option is available.

Add an input to the Stream Analytics job

1. Navigate to your Stream Analytics job.

2. Under Job Topology, click Inputs.

3. In the Inputs pane, click Add, and then enter the following information:

   Input alias: The unique alias for the input.

   Source: Select IoT hub.

   Consumer group: Select the consumer group you just created.

4. Click Create.

Add an output to the Stream Analytics job

1. Under Job Topology, click Outputs.

2. In the Outputs pane, click Add, and then enter the following information:

   Output alias: The unique alias for the output.

   Sink: Select Power BI.

3. Click Authorize, and then sign into your Power BI account.

4. Once authorized, enter the following information:

   Group Workspace: Select your target group workspace.

   Dataset Name: Enter a dataset name.

   Table Name: Enter a table name.

5. Click Create.

Configure the query of the Stream Analytics job

1. Under Job Topology, click Query.

2. Replace [YourInputAlias] with the input alias of the job.

3. Replace [YourOutputAlias] with the output alias of the job.

4. Click Save.

Run the Stream Analytics job

In the Stream Analytics job, click Start > Now > Start. Once the job successfully starts, the job status changes from Stopped to Running.

Create and publish a Power BI report to visualize the data

1. Ensure the sample application is running on your device. If not, you can refer to the tutorials under Setup your device.

2. Sign in to your Power BI account.

3. Go to the group workspace that you set when you created the output for the Stream Analytics job.

4. Click Datasets.

   You should see the listed dataset that you specified when you created the output for the Stream Analytics job.

5. Under your workspace, click your dataset to create a visualisation.

6. Create a line chart to show real-time temperature over time.

   1. On the report creation page, add a line chart.

   2. On the Fields pane, expand the table that you specified when you created the output for the Stream Analytics job.

   3. Drag EventEnqueuedUtcTime to Axis on the Visualizations pane.

   4. Drag temperature to Values.

      Now a line chart is created. The x-axis of chart displays date and time in the UTC time zone. The y-axis displays temperature from the sensor.

7. Create another line chart to show real-time humidity over time. To do this, follow the same steps above and place EventEnqueuedUtcTime on the x-axis and humidity on the y-axis.

8. Click Save to save the report.

Microsoft also offers the Power BI mobile apps for viewing and interacting with your Power BI dashboards and reports on your mobile device.