The Internet of Things: Big Data Processing and Analytics

Course Description

How are you harnessing the immense amount of data embedded inside The Internet of Things (IoT)? This phenomenon promises many new technological innovations and business benefits. The prospect of connecting potentially millions or even billions of embedded devices, sensors, appliances and other data-collecting gear to the cloud is daunting yet exciting. It requires new processes and tools for collecting and processing IoT big data and analyzing the device information to glean insights embedded within vast amounts of data. Discover how to transform this data deluge into actionable insights by using state-of-the-art AI and machine learning techniques, and by utilizing modern big data processing tools.

The course first defines IoT and why IoT data processing is very different from typical big data analytics, with its unique requirements for data security, device identity, huge data volume, and real-time processing. The course reviews the challenges and current architectures of IoT data collection to the cloud. Using a hands-on approach in Amazon Web Services (AWS) with simulated data, you will learn to build a messaging and data streaming system with Apache Spark and Kafka. You will explore current IoT architectures and learn how to build robust data pipelines that can handle the scale and complexity of IoT data.

You will work with simulated and real IoT device data, designing and implementing your own data flows to extract valuable business intelligence. The course provides a deep dive into industrial practices of IoT big data processing and analytics, with a focus on practical application of tools and frameworks.