Azure IoT: Turn Device Data into Insights and Action

Hands-on guide to sending, processing, and turning IoT data into actionable insights in Azure

What you’ll learn
✓ Send IoT data to the cloud
✓ Securely store IoT data in the cloud
✓ Learn about device-to-cloud messages
✓ Create Insights by querying and visualizing your IoT data
✓ Create an IoT solution in Azure based on a typical IoT Architecture
✓ Analyze IoT data in near real-time and take action
✓ Route IoT data to Azure services

Requirements
● No programming experience needed
● No cloud or IoT experience needed
● No IoT hardware needed
● An Azure subscription is recommended to follow along with the demos, but not required. We’ll use free services where possible, and any paid services easily fit within the $100 credit you get with a new account — so your bill should be close to zero. No subscription? No problem, you can still follow along and learn everything!

Description
Have you ever sent device data to the cloud and then wondered how to make sense of that constant stream of incoming data?
Do you want to learn how to process your IoT data effectively in Azure?
Are you ready to turn raw telemetry into real insights — and real business value?

If you answered “yes” to any of these questions, then you’re in the right place.

Here’s what you’ll walk away with after this course

• You’ll know how to build a complete IoT data processing solution in Azure.

• You’ll understand how to turn IoT data into meaningful business value.

• And you’ll have the confidence to apply what you’ve learned in real-world scenarios.

The course is split into six modules, with more than four hours of video content.

After a general introduction to the course we kick things off with the basics: the cloud, the Internet of Things, and a high-level IoT architecture. In the modules that follow, we’ll use that architecture as the foundation and start building an actual IoT solution in Azure.

In the third module, we get hands-on and see how easy it is to get started. And this might surprise you: by the end of that module, you will already have a device set up and you’ll have sent your first IoT messages to the cloud. I think that will get you excited for what’s ahead!

After that, in module four, we zoom in on IoT messages themselves. What kind of data is typically sent? How is it structured? Which protocols are used? And how can we route messages in the cloud?

In the next three modules, we’ll fully build out the IoT architecture. These are very demo-heavy modules.

We start gently in module five, where the focus is on long-term storage of IoT data.

In module six, we move on to insights. You’ll learn how to query the data, explore it, and create graphs and dashboards to really understand what your data is telling you.

Then in module seven, we focus on action. In real IoT solutions, data keeps streaming in all the time — far too much to monitor manually. In this module, I’ll show you how to automatically detect patterns or critical conditions and trigger actions. We’ll build an example where we detect an overheating device and send out an alert so someone can step in.

And finally, in the last module, we’ll take a step back and review everything we’ve built. After going deep into the details, it’s nice to see the full picture and understand how data flows through the entire architecture.

By the end of this course, you’ll know which Azure services to use for which part of an IoT solution. You’ll have the skills to build this architecture yourself — and the confidence to adapt it to your own business requirements.

And remember: no heavy coding. We’ll keep code to a minimum, and any scripts or queries we use are available in the GitHub repository that comes with this course. You’ll also find links to all relevant documentation there.

Alright — I hope you’re excited, ready to learn, and ready to build your own IoT message processing solution in Azure.

Who this course is for
■ Beginner IoT developers who want to learn not just how to send data to the cloud, but how to actually do something useful with it.
■ Architects who want to design systems for processing IoT data in the cloud
■ Data engineers who want to expand their knowledge to IoT systems

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