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A review of sector-specific big data analytics models

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dc.citedby1
dc.contributor.authorDollah R.en_US
dc.contributor.authorAris H.en_US
dc.contributor.authorid57202188451en_US
dc.contributor.authorid13608397500en_US
dc.date.accessioned2023-05-29T06:53:05Z
dc.date.available2023-05-29T06:53:05Z
dc.date.issued2018
dc.descriptionDigital storage; Social networking (online); BDA comparison; Big Data Analytics; Case analysis; Data storage; Mobile applications; Mobile Technology; Online social medias; Big dataen_US
dc.description.abstractProliferation of mobile applications and platforms, including online social media has given birth to big data. These data that result from the unprecedented development in mobile technologies are regarded as the 'new oil' of the century, which is attributed to the contained value and changes that they can bring about. Various sectors are making attempts at leveraging the potential of big data and a number of sector-specific big data analytics (BDA) models have emerged as a result. In this study, a review on these sector-specific BDA models was performed to understand the current state of their implementation with respect to the five well-known layers found from the literature. The objective of this study is twofold. Firstly, to identify the sectors where BDA models have been proposed and secondly, to identify the implementation details with regard to the layers and respective components that constitute these models. Analysis results showed that the models vary in terms of the number of explicit layers that constitute them and the way the components are arranged into respective layers. It is also found that data storage layer that theoretically exists in the literature is not present explicitly in most models reviewed. Finding from this study helps to understand the difference between theoretical and practical implementation of BDA models, which will be beneficial in shaping future research on BDA models. � 2017 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ICBDAA.2017.8284110
dc.identifier.epage80
dc.identifier.scopus2-s2.0-85047423948
dc.identifier.spage72
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85047423948&doi=10.1109%2fICBDAA.2017.8284110&partnerID=40&md5=5ac6927ca68d161b64e06ce84444d39a
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23911
dc.identifier.volume2018-January
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2017 IEEE Conference on Big Data and Analytics, ICBDA 2017
dc.titleA review of sector-specific big data analytics modelsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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