Visualize real-time sensor data from Azure IoT Hub using Power BI
Before you start this tutorial, complete the Raspberry Pi online simulator tutorial or one of the device tutorials; for example, Raspberry Pi with node.js. In these articles, you set up your Azure IoT device and IoT hub, and you 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 using Power BI. If you want to try toe 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
Get your IoT hub ready for data access by adding a consumer group.
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
- 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)
Add a consumer group to your IoT hub
Consumer groups are used by applications to pull data from Azure IoT Hub. In this tutorial, you create a consumer group to be used by a coming Azure service to read data from your IoT hub.
To add a consumer group to your IoT hub, follow these steps:
In the Azure portal, open your IoT hub.
In the left pane, click Built-in endpoints, select Events on the top pane, and enter a name under Consumer groups on the right pane. Click Save after you change the Default TTL value and return it back to the original value.
Create, configure, and run a Stream Analytics job
Let's start by creating a Stream Analytics job. After you create the job, you define the inputs, outputs, and the query used to retrieve the data.
Create a Stream Analytics job
In the Azure portal, click Create a resource > Internet of Things > Stream Analytics job.
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.
Add an input to the Stream Analytics job
Open the Stream Analytics job.
Under Job Topology, click Inputs.
In the Inputs pane, click Add stream input, and then enter the following information:
Input alias: The unique alias for the input and select Provide IoT Hub settings manually below.
Source: Select IoT hub.
Endpoint: Click Messaging.
Consumer group: Select the consumer group you just created.
Add an output to the Stream Analytics job
Under Job Topology, click Outputs.
In the Outputs pane, click Add and Power BI, and then enter the following information:
Output alias: The unique alias for the output.
Group Workspace: Select your target group workspace.
Dataset Name: Enter a dataset name.
Table Name: Enter a table name.
Click Authorize, and then sign into your Power BI account.
Configure the query of the Stream Analytics job
Under Job Topology, click Query.
[YourInputAlias]with the input alias of the job.
[YourOutputAlias]with the output alias of the job.
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
Ensure the sample application is running on your device. If not, you can refer to the tutorials under Setup your device.
Sign in to your Power BI account.
Click the workspace you used, My Workspace.
You should see the dataset that you specified when you created the output for the Stream Analytics job.
For the dataset you created, click Add Report (the first icon to the right of the dataset name).
Create a line chart to show real-time temperature over time.
On the report creation page, add a line chart.
On the Fields pane, expand the table that you specified when you created the output for the Stream Analytics job.
Drag EventEnqueuedUtcTime to Axis on the Visualizations pane.
Drag temperature to Values.
A line chart is created. The x-axis displays date and time in the UTC time zone. The y-axis displays temperature from the sensor.
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.
Click Save to save the report.
Click Reports on the left pane, and then click the report that you just created.
Click File > Publish to web.
Click Create embed code, and then click Publish.
You're provided the report link that you can share with anyone for report access and a code snippet to integrate the report into your blog or website.
Microsoft also offers the Power BI mobile apps for viewing and interacting with your Power BI dashboards and reports on your mobile device.
You’ve successfully used Power BI to visualize real-time sensor data from your Azure IoT hub.
There is an alternate way to visualize data from Azure IoT Hub. See Use Azure Web Apps to visualize real-time sensor data from Azure IoT Hub.
To continue to get started with Azure IoT Hub and to explore all extended IoT scenarios, see the following:
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