Benchmarking business analytics techniques in Big Data

dc.contributor.authorOliveira, Catiapor
dc.contributor.authorGuimarães, Tiago André Saraivapor
dc.contributor.authorPortela, Filipepor
dc.contributor.authorSantos, Manuelpor
dc.date.accessioned2020-10-29T22:42:08Z
dc.date.available2020-10-29T22:42:08Z
dc.date.issued2019
dc.date.updated2020-10-28T11:07:55Z
dc.description.abstractTechnological developments and the growing dependence of organizations and society in the world of the internet led to the growth and variety of data. This growth and variety have become a challenge to the traditional techniques of Business Analytics. In this project, we conducted a benchmarking process that aimed to assess the performance of some Data Mining tools, like RapidMiner, in Big Data environment. Firstly, was analyzed a study where a group of Data Mining tools are evaluated and determined what is the best Data Mining tool, according to the evaluation criteria. After that, the best two tools considered in the study are analyzed regarding their ability to analyze data in a Big Data environment. Finally, studies were carried out on the evaluations of the RapidMiner and KNIME tools for their performance in the Big Data environment.por
dc.description.sponsorshipThis work has been supported by national funds through FCT -Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2019 and Deus ex Machina (DEM): Symbiotic technology for societal efficiency gains -NORTE-01-0145-FEDER-000026.por
dc.distributioninternationalpor
dc.identifier.doi10.1016/j.procs.2019.11.026por
dc.identifier.issn1877-0509
dc.identifier.urihttps://hdl.handle.net/1822/67912
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherElsevier Sciencepor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FCEC%2F00319%2F2019/PTpor
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S1877050919317260por
dc.rightsopenAccesspor
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/por
dc.subjectBig Datapor
dc.subjectAnalyticspor
dc.subjectData Miningpor
dc.subjectBenchmarkingpor
dc.subject.fosCiências Naturais::Ciências da Computação e da Informaçãopor
dc.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
dc.subject.wosScience & Technology
dc.titleBenchmarking business analytics techniques in Big Datapor
dc.typeconferencePaperpor
dspace.entity.typePublicationen
oaire.citationEndPage695por
oaire.citationStartPage690por
oaire.citationVolume160por
oaire.versionVoRpor
sdum.conferencePublication10TH INT CONF ON EMERGING UBIQUITOUS SYST AND PERVAS NETWORKS (EUSPN-2019) / THE 9TH INT CONF ON CURRENT AND FUTURE TRENDS OF INFORMAT AND COMMUN TECHNOLOGIES IN HEALTHCARE (ICTH-2019) / AFFILIATED WORKOPSpor
sdum.export.identifier7389
sdum.journalProcedia Computer Sciencepor

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