Abstract
Streaming analytics is the application of analytic operations to streaming data. We begin the chapter with a short history of streaming analytics, followed by a review of streaming fundamentals. In the third section of the chapter, we review popular streaming data sources, such as Apache Kafka and Amazon Kinesis, followed by a survey of the top open source streaming engines. We close the chapter with some examples of streaming analytics in action, and some observations about the economics of streaming.
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Usability researchers report varying maximum acceptable response times; context matters. For example, see https://www.nngroup.com/articles/powers-of-10-time-scales-in-ux/ for a discussion of standards in customer-facing applications. For internal applications, standards are lower. See https://www.microstrategy.com/it/press-releases/microstrategy-introduces-new-high-performance-standards-for-business-intelligence .
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© 2016 Thomas W. Dinsmore
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Dinsmore, T.W. (2016). Streaming Analytics. In: Disruptive Analytics. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-1311-7_6
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DOI: https://doi.org/10.1007/978-1-4842-1311-7_6
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