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tutorial

Streaming Analytics

Published:13 August 2016Publication History

ABSTRACT

Recently we have seen emergence and huge adoption of social media, internet of things for home, industrial internet of things, mobile applications and online transactions. These systems generate streaming data at very large scale. Building technologies and distributed systems that can capture, process and analyze this streaming data in real time is very important for gaining real time insights. Real-time analysis of streaming data can be used for applications as diverse as fraud detection, in-session targeting and recommendations, control systems for transportation systems and smarter cities, earthquake prediction and control of autonomous vehicles. This tutorial will provide overview of streaming systems and hands on tutorial on building streaming analytics systems using open source technologies.

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kdd2016_tutorial_streaming_analytics_01-acm.mp4

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kdd2016_tutorial_streaming_analytics_02-acm.mp4

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  1. Streaming Analytics

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    • Published in

      cover image ACM Conferences
      KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
      August 2016
      2176 pages
      ISBN:9781450342322
      DOI:10.1145/2939672

      Copyright © 2016 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 13 August 2016

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      Acceptance Rates

      KDD '16 Paper Acceptance Rate66of1,115submissions,6%Overall Acceptance Rate1,133of8,635submissions,13%

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