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Building a Real-time IoT Dashboard with Power BI: A Step-by-Step Tutorial

Tallan Partner

Last month, Microsoft released a set of features in preview designed to make it easier than ever to display real-time streaming data in your Power BI dashboards. Check out the announcement if you haven’t already. Today, Microsoft wants to show you just how easy this can be.

Many of you have expressed interest in using Power BI to display real-time sensor data. In this tutorial, Microsoft will walk you step-by-step through the entire process of setting up a Raspberry Pi weather station, and showing the resulting temperature and humidity data in real-time with Power BI. Here’s a sneak peek of the end result:

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Have other use cases in mind? Don’t have access to the materials below? No sweat. The lessons and sample code in this tutorial are broadly applicable for a wide range of IoT scenarios. And, as always, please let Microsoft know if you have any questions, either in the comments below, or in our community forums.

With that in mind, let’s get started! For this tutorial, we’ll be using the following materials:

  • Raspberry Pi 3 w/ Rapsbian Jessie installed
  • DHT22 temperature sensor

Using Windows 10 IoT instead? No problem. Most of the steps below will apply to you as well, and we’ll call out the differences where necessary.

Preparing the streaming dataset in Power BI

Streaming datasets in Power BI represent streams of incoming data. In this tutorial, the constant stream of temperature and humidity data from our weather station will be represented as a streaming dataset. In this step, we’ll create an API streaming dataset. This exposes an API endpoint that our Raspberry Pi can call to push data to Power BI.

To create a streaming dataset, expand the navigation bar at the left, and click on the “Streaming datasets” button at under the Datasets tab.

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From there, click the “Add streaming dataset” button at the top right.

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Select the API option.

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Give your new streaming dataset a name, and add three fields: timestamp, temperature and humidity. In this step, we’re specifying that the data stream has three fields:

1.timestamp: when the weather measurements were taken

2.temperature: the temperature at that point time

3.humidity: the humidity at that point in time

Important: to use the sample code as is, it is important that your data fields (e.g. “temperature”) and their types (e.g. “Number”) exactly match the ones in the screenshot below!

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Select “Create” to confirm the creation of the streaming dataset. On the following screen, copy the Push URL and set that aside – we’ll need it for later.

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We’ve now successfully created a streaming dataset.

 

CLICK HERE to read the full article and learn how to finalize your Real-Time IoT Dashboard with the help of Power BI!

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