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

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.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.identifier.doi 10.24251/HICSS.2017.712
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41876
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
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