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dc.contributor.authorCardinale, Yudith
dc.contributor.authorGuehis, Sonia
dc.contributor.authorRukoz, Marta
dc.date.accessioned2019-07-09T10:57:32Z
dc.date.available2019-07-09T10:57:32Z
dc.date.issued2017
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/19208
dc.descriptionCommunications in Computer and Information Science book series (CCIS, volume 868)en
dc.language.isoenen
dc.subjectBig Data Analyticen
dc.subjectAnalytic models for big dataen
dc.subjectAnalytical data management applicationsen
dc.subject.ddc005en
dc.titleClassifying Big Data Analytic Approaches: A Generic Architectureen
dc.typeCommunication / Conférence
dc.description.abstractenThe explosion of the huge amount of generated data to be analyzed by several applications, imposes the trend of the moment, the Big Data boom, which in turn causes the existence of a vast landscape of architectural solutions. Non expert users who have to decide which analytical solutions are the most appropriates for their particular constraints and specific requirements in a Big Data context, are today lost, faced with a panoply of disparate and diverse solutions. To support users in this hard selection task, in a previous work, we proposed a generic architecture to classify Big Data Analytical Approaches and a set of criteria of comparison/evaluation. In this paper, we extend our classification architecture to consider more types of Big Data analytic tools and approaches and improve the list of criteria to evaluate them. We classify different existing Big Data analytics solutions according to our proposed generic architecture and qualitatively evaluate them in terms of the criteria of comparison. Additionally, we propose a preliminary design of a decision support system, intended to generate suggestions to users based on such classification and on a qualitative evaluation in terms of previous users experiences, users requirements, nature of the analysis they need, and the set of evaluation criteria.en
dc.identifier.citationpages268-295en
dc.relation.ispartoftitleSoftware Technologies,12th International Joint Conference (ICSOFT 2017)en
dc.relation.ispartofeditorCabello, Enrique
dc.relation.ispartofeditorCardoso, Jorge
dc.relation.ispartofeditorMaciaszek, Leszek A.
dc.relation.ispartofeditorvan Sinderen, Marten
dc.relation.ispartofpublnameSpringer International Publishingen
dc.relation.ispartofpublcityBerlin Heidelbergen
dc.relation.ispartofdate2017
dc.relation.ispartofpages309en
dc.relation.ispartofurl10.1007/978-3-319-93641-3en
dc.contributor.countryeditoruniversityotherVENEZUELA, BOLIVARIAN REPUBLIC OF
dc.subject.ddclabelProgrammation, logiciels, organisation des donnéesen
dc.relation.ispartofisbn978-3-319-93640-6en
dc.relation.conftitle12th International Conference on Software Technologies (ICSOFT 2017)en
dc.relation.confdate2017-07
dc.relation.confcityMadriden
dc.relation.confcountrySpainen
dc.relation.forthcomingnonen
dc.identifier.doi10.1007/978-3-319-93641-3_13en
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2019-07-09T10:52:26Z
hal.person.labIds100644
hal.person.labIds989
hal.person.labIds989
hal.faultCode{"duplicate-entry":{"hal-02096456":{"doi":"1.0"}}}


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