Ítem
Acceso Abierto
Gobierno de datos para la optimización operativa en FAM TEAM
| dc.contributor.advisor | Salazar Betancourth, Erika Johana | |
| dc.creator | Abella Tunjano, Andrés Felipe | |
| dc.creator | Castellanos Carrillo, David Santiago | |
| dc.creator | Gómez Zapata, María Paula | |
| dc.creator.degree | Magíster en Business Analytics | |
| dc.date.accessioned | 2026-01-30T14:51:57Z | |
| dc.date.available | 2026-01-30T14:51:57Z | |
| dc.date.created | 2025-06-24 | |
| dc.description | El proyecto “Gobierno de Datos para la Optimización Operativa en FAM TEAM” propone un marco integral de gobernanza de datos para mejorar la eficiencia operativa de FAM TEAM, un grupo logístico colombiano. Partiendo de un diagnóstico que evidenció fragmentación, errores y alta dependencia operativa, se diseñó un modelo TO-BE basado en DAMA-DMBOK v2, que incluye estándares, políticas, roles, arquitecturas de datos, modelos analíticos y dashboards. Su implementación permitirá estandarizar y centralizar la información, mejorar la calidad y accesibilidad de los datos, habilitar decisiones estratégicas basadas en evidencia y consolidar una cultura organizacional orientada al uso de datos como activo estratégico. | |
| dc.description.abstract | The project “Data Governance for Operational Optimization at FAM TEAM” proposes an integrated data governance framework to enhance operational efficiency at FAM TEAM, a Colombian logistics group. Based on a diagnostic assessment revealing fragmentation, errors, and high operational dependency, a TO-BE model was designed aligned with DAMA-DMBOK v2 principles. The proposed model includes standards, policies, roles, data architectures, predictive models, and dashboards. Its implementation will standardize and centralize information, improve data quality and accessibility, enable strategic data-driven decision-making, and foster an organizational culture that treats data as a strategic asset. | |
| dc.format.extent | 105 pp | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.doi | https://doi.org/10.48713/10336_47398 | |
| dc.identifier.uri | https://repository.urosario.edu.co/handle/10336/47398 | |
| dc.language.iso | eng | |
| dc.publisher | Universidad del Rosario | |
| dc.publisher.department | Escuela de Administración | |
| dc.publisher.department | Escuela de Ingeniería, Ciencia y Tecnología | |
| dc.publisher.program | Maestría en Business Analytics | |
| dc.rights | Attribution-NonCommercial-ShareAlike 4.0 International | * |
| dc.rights.accesRights | info:eu-repo/semantics/openAccess | |
| dc.rights.acceso | Abierto (Texto Completo) | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | * |
| dc.source.bibliographicCitation | Data Governance Institute. (n.d.). Definitions of Data Governance. Recuperado de https://datagovernance.com | |
| dc.source.bibliographicCitation | Khatri, V., & Brown, C. V. (2010). Designing data governance. Communications of the ACM, 53(1), 148-152. | |
| dc.source.bibliographicCitation | IBM Analytics. (n.d.). What is Data Governance? Recuperado de https://www.ibm.com/analytics/data-governance | |
| dc.source.bibliographicCitation | Redman, T. C. (2018). Getting in front on data: Who does what. Harvard Business Review Press. | |
| dc.source.bibliographicCitation | International Organization for Standardization (ISO). (2008). ISO/IEC 38500:2008 – Corporate governance of information technology. ISO. | |
| dc.source.bibliographicCitation | Davenport, T. H., & Harris, J. G. (2007). Competing on Analytics: The New Science of Winning. Harvard Business School Press | |
| dc.source.bibliographicCitation | Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165-1188. | |
| dc.source.bibliographicCitation | Few, S. (2012). Show Me the Numbers: Designing Tables and Graphs to Enlighten. 2nd Edition. Burlingame, CA: Analytics Press. | |
| dc.source.bibliographicCitation | ISO/IEC 25012:2008. (2008). Software engineering – Software product Quality Requirements and Evaluation (SQuaRE) – Data quality model. International Organization for Standardization. | |
| dc.source.bibliographicCitation | Scopesi, M., & Butelli, P. (2022). Data Governance y Data Analytics en el sector logístico: Buenas prácticas y casos de éxito. Journal of Logistics, 12(3), 345-36 | |
| dc.source.bibliographicCitation | Microsoft. (2024, septiembre 1). SMOTE: Referencia del componente | |
| dc.source.instname | instname:Universidad del Rosario | |
| dc.source.reponame | reponame:Repositorio Institucional EdocUR | |
| dc.subject | Gobierno de datos | |
| dc.subject | Eficiencia operativa | |
| dc.subject | Calidad de datos | |
| dc.subject | Arquitectura de datos | |
| dc.subject | Transformación digital | |
| dc.subject | Toma de decisiones | |
| dc.subject.keyword | Data governance | |
| dc.subject.keyword | Operational efficiency | |
| dc.subject.keyword | Data quality | |
| dc.subject.keyword | Data architectur | |
| dc.title | Gobierno de datos para la optimización operativa en FAM TEAM | |
| dc.title.TranslatedTitle | Data Governance for Operational Optimization at FAM TEAM | |
| dc.type | masterThesis | |
| dc.type.hasVersion | info:eu-repo/semantics/acceptedVersion | |
| dc.type.spa | Trabajo de grado | |
| local.department.report | Escuela de Administración | |
| local.regiones | Bogotá |
Archivos
Bloque original
1 - 1 de 1
Cargando...
- Nombre:
- Gobierno_de_datos_para_la_optimizacion_GomezZapata-MariaPaula2025.pdf
- Tamaño:
- 1.98 MB
- Formato:
- Adobe Portable Document Format
- Descripción:



