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A review data cube analysis method in big data environment

With the development of computer technologies, the amount of data has explosive growth and the data volumes have approximately doubled each year. One of the tools that affect scalability and flexibility to handle structured as well as unstructured data called Hadoop. However, data cubes are widely u...

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Main Authors: Ghazali, Dewi Puspa Suhana, Latip, Rohaya, Hussin, Masnida, Abd Wahab, Mohd Helmy
Format: Article
Language:English
Published: Asian Research Publishing Network 2015
Online Access:http://psasir.upm.edu.my/id/eprint/43561/1/A%20review%20data%20cube%20analysis%20method%20in%20big%20data%20environment.pdf
http://psasir.upm.edu.my/id/eprint/43561/
http://www.arpnjournals.org/jeas/research_papers/rp_2015/jeas_1015_2756.pdf
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spelling my.upm.eprints.435612016-11-14T09:26:05Z http://psasir.upm.edu.my/id/eprint/43561/ A review data cube analysis method in big data environment Ghazali, Dewi Puspa Suhana Latip, Rohaya Hussin, Masnida Abd Wahab, Mohd Helmy With the development of computer technologies, the amount of data has explosive growth and the data volumes have approximately doubled each year. One of the tools that affect scalability and flexibility to handle structured as well as unstructured data called Hadoop. However, data cubes are widely used as a powerful tool to provide multi-dimensional views in data warehousing and On-Line Analytical Processing (OLAP). Therefore, it is becoming expensive to perform the data cube analysis when the data sizes increases. In this paper, we will investigate and review the methods of MapReduce in Hadoop. Asian Research Publishing Network 2015 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/43561/1/A%20review%20data%20cube%20analysis%20method%20in%20big%20data%20environment.pdf Ghazali, Dewi Puspa Suhana and Latip, Rohaya and Hussin, Masnida and Abd Wahab, Mohd Helmy (2015) A review data cube analysis method in big data environment. ARPN Journal of Engineering and Applied Sciences, 10 (19). pp. 8525-8532. ISSN 1819-6608 http://www.arpnjournals.org/jeas/research_papers/rp_2015/jeas_1015_2756.pdf
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description With the development of computer technologies, the amount of data has explosive growth and the data volumes have approximately doubled each year. One of the tools that affect scalability and flexibility to handle structured as well as unstructured data called Hadoop. However, data cubes are widely used as a powerful tool to provide multi-dimensional views in data warehousing and On-Line Analytical Processing (OLAP). Therefore, it is becoming expensive to perform the data cube analysis when the data sizes increases. In this paper, we will investigate and review the methods of MapReduce in Hadoop.
format Article
author Ghazali, Dewi Puspa Suhana
Latip, Rohaya
Hussin, Masnida
Abd Wahab, Mohd Helmy
spellingShingle Ghazali, Dewi Puspa Suhana
Latip, Rohaya
Hussin, Masnida
Abd Wahab, Mohd Helmy
A review data cube analysis method in big data environment
author_facet Ghazali, Dewi Puspa Suhana
Latip, Rohaya
Hussin, Masnida
Abd Wahab, Mohd Helmy
author_sort Ghazali, Dewi Puspa Suhana
title A review data cube analysis method in big data environment
title_short A review data cube analysis method in big data environment
title_full A review data cube analysis method in big data environment
title_fullStr A review data cube analysis method in big data environment
title_full_unstemmed A review data cube analysis method in big data environment
title_sort review data cube analysis method in big data environment
publisher Asian Research Publishing Network
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/43561/1/A%20review%20data%20cube%20analysis%20method%20in%20big%20data%20environment.pdf
http://psasir.upm.edu.my/id/eprint/43561/
http://www.arpnjournals.org/jeas/research_papers/rp_2015/jeas_1015_2756.pdf
_version_ 1643833602241200128
score 13.244109

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