Data science methodologies selection with hierarchical analytical process and personal construction theory

The amount of data currently available for Strategic Decision Making is substantial; which is why Data Science find itself in apogee in various areas where it can be applied. Expertise respecting the areas’ methodologies is fundamental; which is why, the objective of this paper is to compare and pon...

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Detalles Bibliográficos
Autores principales: Eckert, Karina, Britos, Paola Verónica
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2019
Materias:
Ciencias Informáticas
Data Science Methodologies
Analytic Hierarchy Process
Personal Construction Theory
Linguistic tags
Criteria
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/91028
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-91028
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Data Science Methodologies
Analytic Hierarchy Process
Personal Construction Theory
Linguistic tags
Criteria
spellingShingle Ciencias Informáticas
Data Science Methodologies
Analytic Hierarchy Process
Personal Construction Theory
Linguistic tags
Criteria
Eckert, Karina
Britos, Paola Verónica
Data science methodologies selection with hierarchical analytical process and personal construction theory
topic_facet Ciencias Informáticas
Data Science Methodologies
Analytic Hierarchy Process
Personal Construction Theory
Linguistic tags
Criteria
description The amount of data currently available for Strategic Decision Making is substantial; which is why Data Science find itself in apogee in various areas where it can be applied. Expertise respecting the areas’ methodologies is fundamental; which is why, the objective of this paper is to compare and ponder them, for which, Analytic Hierarchy Process, was utilized along with linguistic tags and Personal Construction Theory, with the purpose of establishing and prioritizing characteristics according to their degree of compliance in real validation cases. The sub-criteria were grouped in different levels, conforming a hierarchy for the present problem. The validation case consisted in determining causes for breakdowns in new automobiles as they are being transported from the factory to the concessionaires; in which the proposed model proved useful and MoProPEI could be identified as the most adequate methodology.
format Objeto de conferencia
Objeto de conferencia
author Eckert, Karina
Britos, Paola Verónica
author_facet Eckert, Karina
Britos, Paola Verónica
author_sort Eckert, Karina
title Data science methodologies selection with hierarchical analytical process and personal construction theory
title_short Data science methodologies selection with hierarchical analytical process and personal construction theory
title_full Data science methodologies selection with hierarchical analytical process and personal construction theory
title_fullStr Data science methodologies selection with hierarchical analytical process and personal construction theory
title_full_unstemmed Data science methodologies selection with hierarchical analytical process and personal construction theory
title_sort data science methodologies selection with hierarchical analytical process and personal construction theory
publishDate 2019
url http://sedici.unlp.edu.ar/handle/10915/91028
work_keys_str_mv AT eckertkarina datasciencemethodologiesselectionwithhierarchicalanalyticalprocessandpersonalconstructiontheory
AT britospaolaveronica datasciencemethodologiesselectionwithhierarchicalanalyticalprocessandpersonalconstructiontheory
bdutipo_str Repositorios
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