  Velocity is one of the 4 Vs commonly used to characterize Big Data. In this
regard, Forrester remarked the following in Q3 2014: "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 Vs, viz., Volume, Variety
and Veracity, 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.

Databases;Machine Learning