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Big data streaming platforms : A review

Yesterday’s “Big Data” is today’s “data.” As technology advances, new difficulties and new solutions emerge. In recent years, as a result of the development of Internet of Things (IoT) applications, the area of Data Mining has been confronted with the difficulty of analyzing and interpreting data st...

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Main Authors:	Kumar, Harish, Soh, Ping Jack, Mohd Arfian, Ismail
Format:	Article
Language:	English English
Published:	College of Education, Al-Iraqia University 2022
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/38853/1/Big%20Data%20Streaming%20Platforms_A%20Review.pdf http://umpir.ump.edu.my/id/eprint/38853/2/Big%20data%20streaming%20platforms_A%20review_ABS.pdf http://umpir.ump.edu.my/id/eprint/38853/ https://doi.org/10.52866/ijcsm.2022.02.01.010 https://doi.org/10.52866/ijcsm.2022.02.01.010
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id	my.ump.umpir.38853
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spelling	my.ump.umpir.388532023-11-08T02:51:52Z http://umpir.ump.edu.my/id/eprint/38853/ Big data streaming platforms : A review Kumar, Harish Soh, Ping Jack Mohd Arfian, Ismail QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Yesterday’s “Big Data” is today’s “data.” As technology advances, new difficulties and new solutions emerge. In recent years, as a result of the development of Internet of Things (IoT) applications, the area of Data Mining has been confronted with the difficulty of analyzing and interpreting data streams in real time and at a high data throughput. This situation is known as the velocity element of big data. The rapid advancement of technology has come with an increased use of social media, computer networks, cloud computing, and the IoT. Experiments in the laboratory also generate a large quantity of data, which must be gathered, handled, and evaluated. This massive amount of data is referred to as “Big Data.” Analysts have seen an upsurge in data including valuable and worthless elements. In extracting usable information, data warehouses struggle to keep up with the rising volume of data collected. This article provides an overview of big data architecture and platforms, tools for data stream processing, and examples of implementations. Streaming computing is the focus of our project, which is building a data stream management system to deliver large-scale, cost-effective big data services. Owing to this study, the feasibility of large-scale data processing for distributed, real-time computing is improved even when the systems are overwhelmed. College of Education, Al-Iraqia University 2022 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/38853/1/Big%20Data%20Streaming%20Platforms_A%20Review.pdf pdf en http://umpir.ump.edu.my/id/eprint/38853/2/Big%20data%20streaming%20platforms_A%20review_ABS.pdf Kumar, Harish and Soh, Ping Jack and Mohd Arfian, Ismail (2022) Big data streaming platforms : A review. Iraqi Journal for Computer Science and Mathematics, 3 (2). pp. 95-100. ISSN 2788-7421. (Published) https://doi.org/10.52866/ijcsm.2022.02.01.010 https://doi.org/10.52866/ijcsm.2022.02.01.010
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
building	UMPSA Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang Al-Sultan Abdullah
content_source	UMPSA Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English English
topic	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General)
spellingShingle	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Kumar, Harish Soh, Ping Jack Mohd Arfian, Ismail Big data streaming platforms : A review
description	Yesterday’s “Big Data” is today’s “data.” As technology advances, new difficulties and new solutions emerge. In recent years, as a result of the development of Internet of Things (IoT) applications, the area of Data Mining has been confronted with the difficulty of analyzing and interpreting data streams in real time and at a high data throughput. This situation is known as the velocity element of big data. The rapid advancement of technology has come with an increased use of social media, computer networks, cloud computing, and the IoT. Experiments in the laboratory also generate a large quantity of data, which must be gathered, handled, and evaluated. This massive amount of data is referred to as “Big Data.” Analysts have seen an upsurge in data including valuable and worthless elements. In extracting usable information, data warehouses struggle to keep up with the rising volume of data collected. This article provides an overview of big data architecture and platforms, tools for data stream processing, and examples of implementations. Streaming computing is the focus of our project, which is building a data stream management system to deliver large-scale, cost-effective big data services. Owing to this study, the feasibility of large-scale data processing for distributed, real-time computing is improved even when the systems are overwhelmed.
format	Article
author	Kumar, Harish Soh, Ping Jack Mohd Arfian, Ismail
author_facet	Kumar, Harish Soh, Ping Jack Mohd Arfian, Ismail
author_sort	Kumar, Harish
title	Big data streaming platforms : A review
title_short	Big data streaming platforms : A review
title_full	Big data streaming platforms : A review
title_fullStr	Big data streaming platforms : A review
title_full_unstemmed	Big data streaming platforms : A review
title_sort	big data streaming platforms : a review
publisher	College of Education, Al-Iraqia University
publishDate	2022
url	http://umpir.ump.edu.my/id/eprint/38853/1/Big%20Data%20Streaming%20Platforms_A%20Review.pdf http://umpir.ump.edu.my/id/eprint/38853/2/Big%20data%20streaming%20platforms_A%20review_ABS.pdf http://umpir.ump.edu.my/id/eprint/38853/ https://doi.org/10.52866/ijcsm.2022.02.01.010 https://doi.org/10.52866/ijcsm.2022.02.01.010
_version_	1822923764825849856
score	13.235362

Big data streaming platforms : A review

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