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Real time analytics: algorithms and systems
V elocity is one of the 4 Vs commonly used to characterize Big Data [5]. In this regard, Forrester remarked the following in Q3 2014 [8]: "The high velocity, white-water flow of data from innumerable real-time data sources such as market data, Internet of Things, mobile, sensors, click-stream,...
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Main Authors: | , , |
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Format: | Conference Proceeding |
Language: | English |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | V
elocity is one of the
4 Vs
commonly used to characterize Big Data [5]. In this regard, Forrester remarked the following in Q3 2014 [8]:
"The high velocity, white-water flow of data from innumerable real-time data sources such as market data, Internet of Things, mobile, sensors, click-stream, and even transactions remain largely unnavigated by most firms. The opportunity to leverage streaming analytics has never been greater."
Example use cases of streaming analytics include, but not limited to: (a) visualization of business metrics in real-time (b) facilitating highly personalized experiences (c) expediting response during emergencies. Streaming analytics is extensively used in a wide variety of domains such as healthcare, e-commerce, financial services, telecommunications, energy and utilities, manufacturing, government and transportation.
In this tutorial, we shall present an in-depth overview of streaming analytics -- applications, algorithms and platforms -- landscape. We shall walk through how the field has evolved over the last decade and then discuss the current challenges -- the impact of the other three
V
s, viz.,
V
olume,
V
ariety and
V
eracity, on Big Data streaming analytics. The tutorial is intended for both researchers and practitioners in the industry. We shall also present state-of-the-affairs of streaming analytics at Twitter. |
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ISSN: | 2150-8097 2150-8097 |
DOI: | 10.14778/2824032.2824132 |