In this chapter, we will learn the following recipes:
Analytics are essential for the success of IoT solutions. It plays an important role in converting data into an intelligent action.
For any IoT solution, connecting a device and taking decisions are the core components and they are the main drivers for business transformations and digital business. IoT analytics solutions drives the business insight outcome. They help enhance and improve operational efficiency and asset performance by generating new revenue opportunities. With IoT implementation more business operation are getting automated. Because of which more data is getting generated, the data is of different variety and more complex.
IoT analytics provides a platform for data collection for Edge devices; it helps discover actionable insights. The Azure platform has the right tools and techniques at the right time to help an organization achieve business outcomes...
Azure Stream Analytics provides the key capability of IoT solutions: real-time analytics on the data ingested. As Microsoft says, Azure Stream Analytics is a fully managed service providing low latency, highly availability, and scalable complex event processing over streaming data in the cloud.
Azure Streaming Analytics (ASA) accepts IoT Hub as the input for the Stream Analytics job. The output can be stored into the database or we can connect with Power BI to do the presentation.
Let's work in the next section to send sample data to the IoT Hub and connect with Stream Analytics.
An Azure Stream Analytics job provides various output methods; one of them is to directly provide data for Microsoft Power BI, a visualization tool that helps to take advantage of business intelligence with the most important metrics available at a glance.
We will continue to use the Azure subscription for the IoT Hub and Stream Analytics job; for Power BI we need to create an account. Navigate to the Power BI website, www.powerbi.com.
In this section, we will use the IoT Hub data to...
Time is the important factor in any IoT solution, as business outcomes are time-driven. The data that IoT solutions generate at every time interval just increases the huge data size. We need to implement a technology that can scale and provide analytics, and visualize it quickly.
As Microsoft says, Azure Time Series Insights is a fully managed analytics, storage and visualization service that makes it simple to explore and analyze billions of IoT events simultaneously. It helps you to quickly validate your IoT solution and avoid costly downtime to mission critical devices by helping you discover hidden trends, spot anomalies, and conduct root-cause analysis in near real-time.
Edge computing is the next stage for IoT solutions, with Microsoft recently releasing a new service for running analytics at Edge devices. Azure IoT platform is extending the capabilities; this service is called IoT Edge.
The new platform can run on Windows and Linux OS. It can run on devices with 128 MB memory. It provides modules to run Azure services like Azure functions, Stream Analytics, Azure's machine learning, and artificial intelligence capabilities which will all be available on IoT Edge.
As Microsoft Azure states, some of the benefits and advantages of using Azure IoT Edge are as follows:
Azure functions are small running pieces of code, or functions, in the cloud. You can write small pieces of code that you need for a specific problem without worrying about the complete application or the infrastructure where we can run it.
There are various existing connectivity options available along with language support.
We will be exposing communication with IoT Hub and exploring how Azure functions can work with our small piece of code.
We will create a Azure function and see how to access IoT Hub real time:
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