Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas
Descripción del Articulo
The objective of this research is to design a Data Mart to identify tactical actions and increase the use of POS (points of sale) in the bodega business sector of Lima, Peru. A quantitative approach, using transaction history data, is applied using the Kimball methodology. This involves the ETL (Ext...
Autores: | , , , , , , , |
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Formato: | artículo |
Fecha de Publicación: | 2025 |
Institución: | Universidad Peruana de Ciencias Aplicadas |
Repositorio: | UPC-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorioacademico.upc.edu.pe:10757/684683 |
Enlace del recurso: | http://hdl.handle.net/10757/684683 |
Nivel de acceso: | acceso abierto |
Materia: | Business intelligence dashboard data mart Extract Load (ETL) Point of Sale (POS) Transform |
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repository_id_str |
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dc.title.es_PE.fl_str_mv |
Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas |
title |
Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas |
spellingShingle |
Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas Morales-Arevalo, Juan Carlos Business intelligence dashboard data mart Extract Load (ETL) Point of Sale (POS) Transform |
title_short |
Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas |
title_full |
Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas |
title_fullStr |
Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas |
title_full_unstemmed |
Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas |
title_sort |
Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas |
author |
Morales-Arevalo, Juan Carlos |
author_facet |
Morales-Arevalo, Juan Carlos Aquise-Gonzales, Erick Manuel Carpio-Ore, William Yohani Sáenz, Emmanuel Victor Mendoza Mazzarri-Rodriguez, Carlos Javier Remotti-Becerra, Erick Enrique Plata, Edison Humberto Medina La Luque-Vega, Luis F. |
author_role |
author |
author2 |
Aquise-Gonzales, Erick Manuel Carpio-Ore, William Yohani Sáenz, Emmanuel Victor Mendoza Mazzarri-Rodriguez, Carlos Javier Remotti-Becerra, Erick Enrique Plata, Edison Humberto Medina La Luque-Vega, Luis F. |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Morales-Arevalo, Juan Carlos Aquise-Gonzales, Erick Manuel Carpio-Ore, William Yohani Sáenz, Emmanuel Victor Mendoza Mazzarri-Rodriguez, Carlos Javier Remotti-Becerra, Erick Enrique Plata, Edison Humberto Medina La Luque-Vega, Luis F. |
dc.subject.es_PE.fl_str_mv |
Business intelligence dashboard data mart Extract Load (ETL) Point of Sale (POS) Transform |
topic |
Business intelligence dashboard data mart Extract Load (ETL) Point of Sale (POS) Transform |
description |
The objective of this research is to design a Data Mart to identify tactical actions and increase the use of POS (points of sale) in the bodega business sector of Lima, Peru. A quantitative approach, using transaction history data, is applied using the Kimball methodology. This involves the ETL (Extract, Transform, Load) process to create a dimensional model and to develop a dashboard to visualize key indicators using Power BI. This solution is expected to improve the detection and analysis of transactional errors, categorized by geographic location and business sector while enhancing decision-making processes. This research improves the transactional flow and digital payment adoption in small businesses, fostering greater financial inclusion in the Peruvian market. Therefore, the methodology and tools to be applied in this research offer a framework as a model for similar contexts, especially in emerging markets, which will allow closing gaps in digital payment adoption and financial inclusion. |
publishDate |
2025 |
dc.date.accessioned.none.fl_str_mv |
2025-04-30T03:36:04Z |
dc.date.available.none.fl_str_mv |
2025-04-30T03:36:04Z |
dc.date.issued.fl_str_mv |
2025-01-01 |
dc.type.es_PE.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
dc.identifier.issn.none.fl_str_mv |
2158107X |
dc.identifier.doi.none.fl_str_mv |
10.14569/IJACSA.2025.0160216 |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10757/684683 |
dc.identifier.eissn.none.fl_str_mv |
21565570 |
dc.identifier.journal.es_PE.fl_str_mv |
International Journal of Advanced Computer Science and Applications |
dc.identifier.eid.none.fl_str_mv |
2-s2.0-86000306402 |
dc.identifier.scopusid.none.fl_str_mv |
SCOPUS_ID:86000306402 |
identifier_str_mv |
2158107X 10.14569/IJACSA.2025.0160216 21565570 International Journal of Advanced Computer Science and Applications 2-s2.0-86000306402 SCOPUS_ID:86000306402 |
url |
http://hdl.handle.net/10757/684683 |
dc.language.iso.es_PE.fl_str_mv |
eng |
language |
eng |
dc.rights.es_PE.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.*.fl_str_mv |
Attribution 4.0 International |
dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
dc.format.es_PE.fl_str_mv |
application/pdf |
dc.publisher.es_PE.fl_str_mv |
Science and Information Organization |
dc.source.none.fl_str_mv |
reponame:UPC-Institucional instname:Universidad Peruana de Ciencias Aplicadas instacron:UPC |
instname_str |
Universidad Peruana de Ciencias Aplicadas |
instacron_str |
UPC |
institution |
UPC |
reponame_str |
UPC-Institucional |
collection |
UPC-Institucional |
dc.source.journaltitle.none.fl_str_mv |
International Journal of Advanced Computer Science and Applications |
dc.source.volume.none.fl_str_mv |
16 |
dc.source.issue.none.fl_str_mv |
2 |
dc.source.beginpage.none.fl_str_mv |
157 |
dc.source.endpage.none.fl_str_mv |
166 |
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A quantitative approach, using transaction history data, is applied using the Kimball methodology. This involves the ETL (Extract, Transform, Load) process to create a dimensional model and to develop a dashboard to visualize key indicators using Power BI. This solution is expected to improve the detection and analysis of transactional errors, categorized by geographic location and business sector while enhancing decision-making processes. This research improves the transactional flow and digital payment adoption in small businesses, fostering greater financial inclusion in the Peruvian market. 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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).