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Streaming Analytics: Concepts, architectures, platforms, use cases and applications

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Editors: Pethuru Raj 1 ; Chellammal Surianarayanan 2 ; Koteeswaran Seerangan 3 ; George Ghinea 4
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Publication Year: 2022

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 to be 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.

The book will be of interest to ICTs industry and academic researchers, scientists and engineers as well as lecturers and advanced students in the fields of data science, cloud/fog/edge architecture, internet of things and artificial intelligence and related fields of applications. It will also be useful to cloud/edge/fog and IoT architects, analytics professionals, IT operations teams and site reliability engineers (SREs).

Inspec keywords: learning (artificial intelligence); cloud computing; data analysis; Big Data; Internet of Things

Other keywords: big data; business data processing; internet of things; data analysis; unsupervised learning; data mining; pattern classification; Internet; cloud computing; learning artificial intelligence

Subjects: Internet software; Mobile, ubiquitous and pervasive computing; Information networks; Data handling techniques; Data security; General and management topics; Unsupervised learning

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