Towards an improved ASUM-DM process methodology for cross-disciplinary multi-organization big data & analytics projects

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dc.contributor.authorAngée, S.
dc.contributor.authorLozano-Argel, S.I.
dc.contributor.authorMontoya-Munera, E.N.
dc.contributor.authorOspina-Arango, J.-D.
dc.contributor.authorTabares-Betancur, M.S.
dc.contributor.departmentUniversidad EAFIT. Departamento de Ingeniería de Sistemasspa
dc.contributor.researchgroupI+D+I en Tecnologías de la Información y las Comunicacionesspa
dc.date.accessioned2021-04-12T21:07:08Z
dc.date.available2021-04-12T21:07:08Z
dc.date.issued2018-01-01
dc.description.abstractThe development of big data & analytics projects with the participation of several corporate divisions and research groups within and among organizations is a non-trivial problem and requires well-defined roles and processes. Since there is no accepted standard for the implementation of big data & analytics projects, project managers have to either adapt an existing data mining process methodology or create a new one. This work presents a use case for a big data & analytics project for the banking sector. The authors found out that an adaptation of ASUM-DM, a refined CRISP-DM, with the addition of big data analysis, application prototyping, and prototype evaluation, plus a strong project management work with an emphasis in communications proved the best solution to develop a cross-disciplinary, multi-organization, geographically-distributed big data & analytics project. © 2018, Springer Nature Switzerland AG.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8223
dc.identifier.doi10.1007/978-3-319-95204-8_51
dc.identifier.issn18650929
dc.identifier.issn18650937
dc.identifier.otherWOS;000558244200050
dc.identifier.otherSCOPUS;2-s2.0-85051970837
dc.identifier.urihttp://hdl.handle.net/10784/28767
dc.language.isoeng
dc.publisherSpringer Verlag
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85051970837&doi=10.1007%2f978-3-319-95204-8_51&partnerID=40&md5=c34d0655327792e6c45a9c8698c1a5f3
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/1865-0929
dc.sourceCommunications in Computer and Information Science
dc.subject.keywordDataeng
dc.subject.keywordminingeng
dc.subject.keywordKnowledgeeng
dc.subject.keywordmanagementeng
dc.subject.keywordProjecteng
dc.subject.keywordmanagementeng
dc.subject.keywordSoftwareeng
dc.subject.keywordprototypingeng
dc.subject.keywordAnalyticseng
dc.subject.keywordASUM-DMeng
dc.subject.keywordBankingeng
dc.subject.keywordsectorseng
dc.subject.keywordCRISP-DMeng
dc.subject.keywordCross-disciplinaryeng
dc.subject.keywordDataeng
dc.subject.keywordminingeng
dc.subject.keywordprocesseng
dc.subject.keywordNoneng
dc.subject.keywordtrivialeng
dc.subject.keywordproblemseng
dc.subject.keywordProjecteng
dc.subject.keywordmanagerseng
dc.subject.keywordBigeng
dc.subject.keyworddataeng
dc.titleTowards an improved ASUM-DM process methodology for cross-disciplinary multi-organization big data & analytics projectseng
dc.typeinfo:eu-repo/semantics/conferencePapereng
dc.typeconferencePapereng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localDocumento de conferenciaspa

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