When digitized entities, connected devices and microservices interact purposefully, we end up with a massive amount of multi-structured streaming (real time) data that is continuously generated by different sources at high speed. Streaming analytics allows the management, monitoring, and real-time analytics of live streaming data. The topic has grown in importance due to the emergence of online analytics and edge and IoT platforms. A real digital transformation is being achieved across industry verticals through meticulous data collection, cleansing and crunching in real time. Capturing and subjecting those value-adding events is considered as the prime task for achieving trustworthy and timely insights.
The authors articulate and accentuate the challenges widely associated with streaming data and analytics, describe data analytics algorithms and approaches, present Edge and Fog computing concepts and technologies and show how streaming analytics can be accomplished in Edge device clouds. They also delineate several industry use cases across cloud system operations in transportation and cyber security and other business domains.