dshimo0 / IOT

Internet-of-things (IOT) is driving some compelling application scenarios in our industry that in turn result in new business opportunities. It's also creating some challenges. Smart devices and sensors are generating massive amounts of data in real-time. How is this data ingested? Where is it stored? What are the services available to perform analytics on this data? These challenges and patterns for addressing them are covered in this session.

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Archititecting IOT Solutions in Azure

Internet-of-things (IOT) is driving some compelling application scenarios in our industry that in turn result in new business opportunities. It's also creating some challenges. Smart devices and sensors are generating massive amounts of data in real-time. How is this data ingested? Where is it stored? What are the services available to perform analytics on this data? These challenges and patterns for addressing them are covered in this session.

Presentation

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The PowerPoint includes full speaker notes helping you understand the slides, and everything you need to deliver the session.

Demos

Session objectives

  • Understand the Microsoft IoT Reference Architecture
  • Understand how to use the Azure IoT Suite pre-configured solutions to accelerate solution development
  • Understand IoT Hub capabilities such as device identity, security, device-to-cloud, cloud-to-device, and device management (ie: firmware update)
  • Understand how to perform analytics on ingested data and presentation (ie: dashboards, PowerBI, etc.)

Session Prerequisits

  • None

Azure Services Covered

Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

About

Internet-of-things (IOT) is driving some compelling application scenarios in our industry that in turn result in new business opportunities. It's also creating some challenges. Smart devices and sensors are generating massive amounts of data in real-time. How is this data ingested? Where is it stored? What are the services available to perform analytics on this data? These challenges and patterns for addressing them are covered in this session.