Data Sources: Implementing Edge on the Cloud

Data Sources: Implementing Edge on the Cloud

• Course Overview
• identify the approaches and the steps involved in setting up AWS IoT Greengrass
• recognize the essential components of GCP IoT Edge
• connect a web application to AWS IoT using MQTT over WebSockets
• demonstrate the essential approaches of using IoT Device Simulator
• generate streams of weather data using the MQTT messaging protocol
• create a device type, a user, and a device using IoT Device Simulator

To become proficient in data science, users have to understand edge computing. This is where data is processed near the source or at the edge of the network while in a typical cloud environment, data processing happens in a centralized data storage location. In this 7-video course, learners will explore the implementation of IoT (Internet of Things) on prominent cloud platforms like AWS (Amazon Web Services) and GCP (Google Cloud Platform). Discover how to work with IoT Device Simulator and generate data streams with MQTT (Message Queuing Telemetry Transport). You will next examine the approaches and steps involved in setting up AWS IoT Greengrass, and the essential components of GCP IoT Edge. Then learn how to connect a web application to AWS IoT by using MQTT over WebSockets. The next tutorial demonstrates the essential approach of using IoT Device Simulator, then on to generating streams of data by using the MQTT messaging protocol. The concluding exercise involves creating a device type, a user, and a device by using IoT Device Simulator.

Data Sources: Integration

Data Sources: Integration

• Course Overview
• recognize required elements for deploying IoT solutions
• describe the prominent service categories of IoT solutions
• recognize the capabilities provided by IoT solutions and the maturity models of IoT solutions
• list the critical design principles that need to be implemented when building IoT solutions
• describe the cloud architectures of IoT from the perspective of Microsoft Azure, AWS, and GCP
• compare the features and capabilities provided by the MQTT and XXMP protocols for IoT solutions
• identify key features and applications that can be implemented using IoT controllers
• recognize the concept of IoT data management and the applied lifecycle of IoT data
• list the essential security techniques that can be implemented to secure IoT solutions
• generate weather data streams and connect web applications to AWS IoT

In this 11-video course, you will examine the architecture of IoT (Internet of Things) solutions and the essential approaches of integrating data sources. Begin by examining the required elements for deploying IoT solutions and its prominent service categories. Take a look at the capabilities provided and the maturity models of IoT solutions. Explore the critical design principles that need to be implemented when building IoT solutions and the cloud architectures of IoT from the perspective of Microsoft Azure, Amazon Web Services, and GCP (Google Cloud Platform). Compare the features and capabilities provided by the MQTT (Message Queuing Telemetry Transport) and XMPP (Extensible Messaging and Presence Protocol) protocols for IoT solutions. Identify key features and applications that can be implemented by using IoT controllers; learn to recognize the concept of IoT data management and the applied lifecycle of IoT data. Examine the list of essential security techniques that can be implemented to secure IoT solutions. The concluding exercise focuses on generating data streams.