Microsoft Azure IoT Lab 3

Visualizing IoT Data

In this lab you will create visualizations of IoT data.

Table of Contents

If you haven’t already done so, please follow the instructions in ‘Getting Started’ section.

In this lab you will process the data that you are sending into Azure IoT Hub using Azure Stream Analytics so that you can visualize it using Power BI.

Bill of Materials

What you will need:

  1. The Thing from the previous lab running
  2. Microsoft Azure account

In a previous labs you provisioned an Azure IoT Hub and a physical device, and you wrote a Node.js application to collect data from the board and weather shield and send it to your IoT Hub. At the end of the previous lab you had data going into your IoT Hub but you weren’t yet doing anything with it. Let’s change that.

Using Stream Analytics to Process and Route IoT Data

Azure Stream Analytics is a service that does real-time data processing in the cloud. You will create a new Stream Analytics job and define the input data stream as the data coming from your IoT Hub. Next you will define an output data stream that sends data to Power BI. Finally, you will write a SQL-like query that collects data coming in on the input stream and routes it to the output stream.

Create the Stream Analytics Job

Open a new browser tab and navigate to the Click on the NEW icon in the lower-left corner.

Select DATA SERVICES > STREAM ANALYTICS > QUICK CREATE and enter the following:

  1. JOB NAME: You can use anything you’d like here…I recommend iotlab or something similar so you can identify it easily later.
  2. REGION: Select East US (or whatever region you created your IoT Hub in). NOTE: If you are using a new Azure Account and experience errors, try creating the Stream Analytics job in the East US 2 region.
  3. REGIONAL MONITORING STORAGE ACCOUNT: Select or create a storage account.

Click CREATE STREAM ANALYTICS JOB. It will take a few minutes for the Steam Analytics job to get created and become available.

When the job indicates that it is created, click into it to create the data streams and query.

Define the Input Data Stream

Once you are in the Stream Analytics job, click on the INPUTS header.

Click on ADD AN INPUT. Select Data stream and click on the forward arrow in the lower-right. Select IoT Hub and click on the forward arrow in the lower-right. Complete the form as follows:

  1. INPUT ALIAS - DeviceInputStream
  2. SUBSCRIPTION - choose your subscription
  3. CHOOSE AN IOT HUB - choose the IoT Hub you created earlier
  4. IOT HUB SHARED ACCESS POLICY NAME - leave this as the default, which should be iothubowner
  5. IOT HUB CONSUMER GROUP - select Create a new consumer group and name it AnalyticsConsumerGroup

Click on the forward arrow in the lower-right.

On the Serialization settings form, leave the defaults (Event Serialization Format:JSON and Encoding:UTF8) click on the checkmark in the lower-right.

After a few seconds, a new input will be listed.

Define the Output Data Stream

Click on the OUTPUTS header.

Click on ADD AN OURPUT. Select Power BI and click on the forward arrow in the lower-right. Follow the instructions for either Existing Microsoft Power BI User or New User

Power BI is a data visualization toolkit for organizations. To create a new user account, you will have to use an account that belongs to an organization, such as your place of employment. You will not be able to create a new user account using an email address that ends in,, or other general email provider accounts.

After you have authorized the connection to Power BI, complete the form as follows:

  1. OUTPUT ALIAS - WeatherBI
  2. DATASET NAME - WeatherData
  3. TABLE NAME - Weather
  4. GROUP NAME - My Workplace

Click on the checkmark in the lower-right.

Write the Query

Click on the QUERY header.

In the query, you want to select data from the input stream and put it into the output stream. With data like temperature and humidity you can do interesting things like apply operations on the data as you query it. For this example, you will write a query that selects from the input stream and send the output stream the minimum, maximum and average values from the data coming in, and enables you to group the data by either location or device ID. Using a TumblingWindow you will send data to the output stream in rolling increments of 5-seconds. Write the following query:

    MAX(fahrenheit) MaxTempF,
    MIN(fahrenheit) MinTempF,
    AVG(fahrenheit) AvgTempF,
    MAX(celsius) MaxTempC,
    MIN(celsius) MinTempC,
    AVG(celsius) AvgTempC,
    MAX(relativeHumidity) MaxHumidity,
    MIN(relativeHumidity) MinHumidity,
    AVG(relativeHumidity) AvgHumidity,
    System.Timestamp AS Timestamp
    TumblingWindow (second, 5), deviceId, sensorName, location 

Click SAVE in the lower middle of the screen. Once the query is saved, click _START to start the Stream Analytics job. If your Node.js app from the previous lab isn’t still running, go ahead and start it up. It will take a few minutes for the Stream Analytics job to get started and to start sending data to Power BI, but you should see the TemperatureDataSet show up in Power BI within a few minutes.

Build Reports in Power BI

Go back to the browser tab where you have Power BI open. Look in the Datasets node in the left-hand navigation. The TemperatureDataSet should appear there within a few minutes of IoT Hub data streaming into the Stream Analytics job.

  1. Click on the WeatherData dataset to open the report designer.
  2. Select the Line chart from the Visualizations toolbox on the right side.
  3. Select maxtempf to set it as the Value
  4. Click on the dropdown arrow for maxtempf in the Values box and select Maximum
  5. Repeat steps 3-4 for avgtempf and mintempf, changing their field type to Average and Minimum respectively.
  6. Click on timestamp and set it as the _Axis__

As you are setting the values you should see the line chart updating with the changes. Click File > Save_ and give the report the name __Weaher. Hover over the upper-right corner of the chart and click on the pin icon. Create a new dashboard to pin the chart to. Next, click on the dashboard in the left sidebar. On the dashboard you can watch the data update in near-real-time. While you are watching the dashboard, pinch or blow on the sensors on the weather shield and you will see the data change in the chart.

You can experiment with creating and pinning other types of charts to make an interesting and useful dashboard.

Conclusion & Next Steps

Congratulations! In this lab you learned how to create an Azure Stream Analytics job to query data coming in to Azure IoT Hub, process it and send it to Power BI. In Power BI you learned how to create reports and pin the data visualizations to a dashboard for near real-time updates.