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Customers leverage Azure Databricks for Industrial IoT Analytics
Scaling IoT isn’t easy, but by implementing the best practices higlighted in this whitepaper, organizations will find their experience moving from proof of concept to production to be much simpler. One of the common threads in simplifying every element of the IoT lifecycle is to think about scale from day one, whether that means designing how IoT will interact with business processes or implementing a common data model as early as the proof of concept. By planning for scale from the beginning, organizations save themselves from a lot of complexity down the road. Microsoft and Cognizant aim to help organizations move to IoT at scale as quickly and easily as possible.
This guide will show you how to create the next generation of applications using Azure IoT in only 4 weeks. By committing less than an hour each day—think coffee fueled morning ritual or mid-afternoon break— you’ll be able to build intelligent apps confidently with the tools and frameworks of your choice. Each week you’ll watch a video on foundational concepts of Azure IoT, complete a step-by-step training, and try what you’ve learned with a hands-on exercise. This will give you the expertise you need to successfully complete your Azure IoT Fundamentals certification.
The partnership between PTC and Microsoft brings together ThingWorx, one of the world's leading industrial IoT platforms, with Azure, the world's supercomputer to accelerate digital transformation across the enterprise. From manufacturing, supply chain and engineering to sales, marketing, and customer service, organizations get seamless, secure, pre-built solutions that intelligently decrease time to value and unlock new growth opportunities.
The purpose of the document is to provide an overview of the recommended architecture and implementation technology choices for how to build Azure IoT solutions. This architecture describes terminology, technology principles, common configuration environments, and composition of Azure IoT services, physical devices, and Intelligent Edge Devices. The primary targets of this document are architects, system designers, developers, and other IoT technical decision makers who are building IoT solutions..
In this paper we review the principles of Zero Trust security, and the aspects of IoT that make proactive application of Zero Trust to IoT different than its application to the workforce. The key capabilities of Zero Trust for IoT are defined for companies with an IoT strategy, and next steps highlight Microsoft solutions enabling your journey of Zero Trust for IoT.
This whitepaper is intended to provide a view on how to improve security in IT and OT environments based on the experiences of Microsoft, ABB, and NXP.
Forged within the Microsoft Azure ecosystem, the collaboration between ABB, Microsoft, and NXP provides end-to-end, co-engineered solutions for the industrial Internet of Things (IIoT) that help reduce risk, time to market, and cost.
The path to secure IoT deployments starts with a hardware root-of-trust at the device level, a simple concept that belies the complexity of managing a chain of trust that extends from every edge device to the core of the network. The solution to this management challenge, based on a coordinated effort of domain experts, is a zero touch “chip-to-cloud” provisioning service for certificates-based identity lifecycle management for connected devices.
Published by Infineon Technologies AG with contributions from Microsoft GlobalSign and Eurotech
Each remote monitoring project will be unique—tailored to the needs of your business and your equipment. But at its core, the principles and considerations for a remote monitoring solution are very similar. In this document, you will see details you should consider when getting started on a remote monitoring project.
Imagine if you could predict equipment failures before they happen, and systematically prevent them. That’s what predictive maintenance offers. It involves using data to identify warning signs of potential problems, predict when equipment needs maintenance and preemptively service that equipment before problems occur. This paper presents details and steps you should consider as you plan a predictive maintenance solution.