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Batch to Real-Time: Incremental Data Collection & Analytics Platform

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dc.contributor.author Aydin, Ahmet
dc.contributor.author Anderson, Ken
dc.date.accessioned 2016-12-29T02:10:56Z
dc.date.available 2016-12-29T02:10:56Z
dc.date.issued 2017-01-04
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41876
dc.description.abstract Real-time data collection and analytics is a desirable but challenging feature to provide in data-intensive software systems. To provide highly concurrent and efficient real-time analytics on streaming data at interactive speeds requires a well-designed software architecture that makes use of a carefully selected set of software frameworks. In this paper, we report on the design and implementation of the Incremental Data Collection & Analytics Platform (IDCAP). The IDCAP provides incremental data collection and indexing in real-time of social media data; support for real-time analytics at interactive speeds; highly concurrent batch data processing supported by a novel data model; and a front-end web client that allows an analyst to manage IDCAP resources, to monitor incoming data in real-time, and to provide an interface that allows incremental queries to be performed on top of large Twitter datasets.
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject big data
dc.subject data analytics
dc.subject incremental
dc.subject real-time
dc.title Batch to Real-Time: Incremental Data Collection & Analytics Platform
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2017.712
Appears in Collections: Big Data Engineering Minitrack


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