Metodologías para la construcción de soluciones de inteligencia de negocios
DOI:
https://doi.org/10.51252/rcsi.v4i1.612Palabras clave:
datos, integración, metodologías, procesamiento, soluciones, warehouseResumen
En las organizaciones, la inteligencia de negocios es una herramienta tecnológica por excelencia para el análisis y procesamiento de datos históricos internos explotados a favor de la organización, generando información oportuna y confiable. Nuestro objetivo fue identificar cuáles son las metodologías para la implantación de soluciones de inteligencia de negocios basadas en data warehouse, así como la adaptabilidad de las mismas a los diferentes tipos de empresas. Para ello realizamos una revisión del estado del arte de artículos publicados en revistas indexadas en base de datos bibliográficas como: Web Of Science, Scopus, ScienceDirect, SciELO a través de Google Scholar con el propósito de tener una selección de información de calidad que nos proporcionen aportes importantes para esta revisión. Identificamos que las metodologías permiten una construcción de la solución de manera eficiente mediante fases apoyadas en herramientas, modelos y frameworks para su construcción; siendo la metodología empírica la más utilizada para la construcción de estas soluciones de inteligencia de negocios.
Descargas
Citas
Al-Okaily, A., Al-Okaily, M., Teoh, A. P., & Al-Debei, M. M. (2022). An empirical study on data warehouse systems effectiveness: the case of Jordanian banks in the business intelligence era. EuroMed Journal of Business, May. https://doi.org/10.1108/EMJB-01-2022-0011 DOI: https://doi.org/10.1108/EMJB-01-2022-0011
Ali Qhal, E. M. (2022). Role of Business Intelligence and Knowledge Management in Solving Business Problems. Tehnički Glasnik, 16(3), 371–378. https://doi.org/10.31803/tg-20220531145604 DOI: https://doi.org/10.31803/tg-20220531145604
Antoniolli, A. F., Naspolini, H. F., de Abreu, J. F., & Rüther, R. (2022). Development of technical and statistical algorithm using Business Intelligence tools for energy yield assessment of large rooftop photovoltaic system ensembles. Sustainable Energy Technologies and Assessments, 49(November 2021). https://doi.org/10.1016/j.seta.2021.101686 DOI: https://doi.org/10.1016/j.seta.2021.101686
Azevedo, J., Duarte, J., & Santos, M. F. (2021). Implementing a business intelligence cost accounting solution in a healthcare setting. Procedia Computer Science, 198(2021), 329–334. https://doi.org/10.1016/j.procs.2021.12.249 DOI: https://doi.org/10.1016/j.procs.2021.12.249
Basile, L. J., Carbonara, N., Pellegrino, R., & Panniello, U. (2022). Business intelligence in the healthcare industry: The utilization of a data-driven approach to support clinical decision making. Technovation, March 2021, 102482. https://doi.org/10.1016/j.technovation.2022.102482 DOI: https://doi.org/10.1016/j.technovation.2022.102482
Biagi, V., Patriarca, R., & Di Gravio, G. (2022). Business intelligence for IT governance of a technology company. Data, 7(1). https://doi.org/10.3390/data7010002 DOI: https://doi.org/10.3390/data7010002
Bimonte, S., Billaud, O., Fontaine, B., Martin, T., Flouvat, F., Hassan, A., Rouillier, N., & Sautot, L. (2021). Collect and analysis of agro-biodiversity data in a participative context: A business intelligence framework. Ecological Informatics, 61(December 2020). https://doi.org/10.1016/j.ecoinf.2021.101231 DOI: https://doi.org/10.1016/j.ecoinf.2021.101231
Božič, K., & Dimovski, V. (2019). Business intelligence and analytics use, innovation ambidexterity, and firm performance: A dynamic capabilities perspective. Journal of Strategic Information Systems, 28(4), 101578. https://doi.org/10.1016/j.jsis.2019.101578 DOI: https://doi.org/10.1016/j.jsis.2019.101578
Castiblanco Montañez, R. A., Coronado Veloza, C. M., Morales Ballesteros, L. V., Polo González, T. V., & Saavedra Leyva, A. J. (2022). Hemorragia postparto: intervenciones y tratamiento del profesional de enfermería para prevenir shock hipovolémico. Revista Cuidarte. https://doi.org/10.15649/cuidarte.2075 DOI: https://doi.org/10.15649/cuidarte.2075
Castillo Abarca, L., Vega Zepeda, V., & Meneses Villegas, C. (2020). Alineando el ciclo de vida de un proyecto con un modelo de madurez BI: una propuesta para la etapa de análisis preliminar. Ingeniare. Revista Chilena de Ingeniería, 28(4), 629–644. https://doi.org/10.4067/s0718-33052020000400629 DOI: https://doi.org/10.4067/S0718-33052020000400629
Cerda-Leiva, L., Araya-Castillo, L., & Barrientos Oradini, N. (2020). ¿Cuánto Se Ha Avanzado En Proporcionar Analítica E Inteligencia De Negocios a Las Pymes? Investigacion & Desarrollo, 19(2), 167–175. https://doi.org/10.23881/idupbo.019.2-11e DOI: https://doi.org/10.23881/idupbo.019.2-11e
Cruz, L. M. H., Lao, F. J. B., Alvarez, D. C. M., Téllez, M. C., Canul, R. C. C., May, J. I. S., & Guerrero, M. D. F. (2022). Use of the Hefesto v2.0 methodology to implement a Data warehouse: Case applied COVID-19. Iberian Conference on Information Systems and Technologies, CISTI, 2022-June. https://doi.org/10.23919/CISTI54924.2022.9820132 DOI: https://doi.org/10.23919/CISTI54924.2022.9820132
Dahr, J. M., Hamoud, A. K., Najm, I. A., & Ahmed, M. I. (2022). Implementing Sales Decision Support System Using Data Mart Based on Olap, Kpi, and Data Mining Approaches. Journal of Engineering Science and Technology, 17(1), 275–293.
Díaz Vásquez, R. A., Espinoza Acosta, L. J., & Cabrera Checa, A. M. (2022). Power BI como herramienta de apoyo a la toma de decisiones. Revista Universidad y Sociedad, 14(S3), 195–207.
Duarte, R., Guimarães, T., & Santos, M. F. (2021). A Business Intelligence Platform for Portuguese Misericórdias. Procedia Computer Science, 198(2021), 341–346. https://doi.org/10.1016/j.procs.2021.12.251 DOI: https://doi.org/10.1016/j.procs.2021.12.251
Duque, J., Godinho, A., & Vasconcelos, J. (2021). Knowledge data extraction for business intelligence A design science research approach. Procedia Computer Science, 204(2022), 1301–139. https://doi.org/10.1016/j.procs.2022.08.016 DOI: https://doi.org/10.1016/j.procs.2022.08.016
Figalist, I., Elsner, C., Bosch, J., & Olsson, H. H. (2022). Breaking the vicious circle: A case study on why AI for software analytics and business intelligence does not take off in practice. Journal of Systems and Software, 184, 111135. https://doi.org/10.1016/j.jss.2021.111135 DOI: https://doi.org/10.1016/j.jss.2021.111135
Fraihat, S., Salameh, W. A., Elhassan, A., Tahoun, B. A., & Asasfeh, M. (2021). Business Intelligence Framework Design and Implementation: A Real-estate Market Case Study. Journal of Data and Information Quality, 13(2). https://doi.org/10.1145/3422669 DOI: https://doi.org/10.1145/3422669
Freitas Júnior, O. de G., de Carvalho, V. D. H., Barros, P. A. M., & Braga, M. de M. (2022). Uma Experiência com Business Intelligence para apoiar a Gestão Acadêmica em uma Universidade Federal Brasileira. RISTI - Revista Ibérica de Sistemas e Tecnologias de Informacão, 46, 5–20. https://doi.org/10.17013/risti.46.5 DOI: https://doi.org/10.17013/risti.46.5-20
García Estrella, C. W., Barón Ramírez, E., & Sánchez Gárate, S. K. (2021). La inteligencia de negocios y la analítica de datos en los procesos empresariales. Revista Científica de Sistemas e Informática, 1(2), 38–53. https://doi.org/10.51252/rcsi.v1i2.167 DOI: https://doi.org/10.51252/rcsi.v1i2.167
Gonzales, R., & Wareham, J. (2019). Analysing the impact of a business intelligence system and new conceptualizations of system use. Journal of Economics, Finance and Administrative Science, 24(48), 345–368. https://doi.org/10.1108/JEFAS-05-2018-0052 DOI: https://doi.org/10.1108/JEFAS-05-2018-0052
Guitarra Romero, R. (2019). Prospectiva e Inteligencia Estratégica Aplicada a la Micro, Pequeña y Mediana Empresa. Tendencias, 20(1), 107–129. https://doi.org/10.22267/rtend.192001.110 DOI: https://doi.org/10.22267/rtend.192001.110
Hamoud, A. K., Hussein, M. K., Alhilfi, Z., & Sabr, R. H. (2021). Implementing data-driven decision support system based on independent educational data mart. In International Journal of Electrical and Computer Engineering (Vol. 11, Issue 6, pp. 5301–5314). https://doi.org/10.11591/ijece.v11i6.pp5301-5314 DOI: https://doi.org/10.11591/ijece.v11i6.pp5301-5314
Hindle, G. A., & Vidgen, R. (2018). Developing a business analytics methodology: A case study in the foodbank sector. European Journal of Operational Research, 268(3), 836–851. https://doi.org/10.1016/j.ejor.2017.06.031 DOI: https://doi.org/10.1016/j.ejor.2017.06.031
Khatibi, V., Keramati, A., & Shirazi, F. (2020). Deployment of a business intelligence model to evaluate Iranian national higher education. Social Sciences & Humanities Open, 2(1), 100056. https://doi.org/10.1016/j.ssaho.2020.100056 DOI: https://doi.org/10.1016/j.ssaho.2020.100056
Lokaadinugroho, I., Girsang, A. S., & Burhanudin, B. (2021). Tableau Business Intelligence Using the 9 Steps of Kimball’s Data Warehouse & Extract Transform Loading of the Pentaho Data Integration Process Approach in Higher Education. Engineering, MAthematics and Computer Science (EMACS) Journal, 3(1), 1–11. https://doi.org/10.21512/emacsjournal.v3i1.6816 DOI: https://doi.org/10.21512/emacsjournal.v3i1.6816
Lopes, J., Guimarães, T., & Santos, M. F. (2020). Adaptive business intelligence: A new architectural approach. Procedia Computer Science, 177, 540–545. https://doi.org/10.1016/j.procs.2020.10.075 DOI: https://doi.org/10.1016/j.procs.2020.10.075
Marzouk, M., & Hanafy, M. (2022). Modelling maintainability of healthcare facilities services systems using BIM and business intelligence. Journal of Building Engineering, 46(December 2021), 103820. https://doi.org/10.1016/j.jobe.2021.103820 DOI: https://doi.org/10.1016/j.jobe.2021.103820
Mora-Vicarioli, F. R., Arce-Solano, J. L., Padilla-Romero, K., & Muñiz-Umaña, G. (2021). Implementación de un sistema de inteligencia de negocios. Escuela de Ciencias de la Administración UNED. Revista Electrónica Calidad En La Educación Superior, 12(1), 76–103. https://doi.org/10.22458/caes.v12i1.3520 DOI: https://doi.org/10.22458/caes.v12i1.3520
Moreno, V., Cavazotte, F., & de Souza Carvalho, W. (2020). Business intelligence and analytics as a driver of dynamic and operational capabilities in times of intense macroeconomic turbulence. Journal of High Technology Management Research, 31(2), 100389. https://doi.org/10.1016/j.hitech.2020.100389 DOI: https://doi.org/10.1016/j.hitech.2020.100389
Nakhal A, A. J., Patriarca, R., Di Gravio, G., Antonioni, G., & Paltrinieri, N. (2021). Investigating occupational and operational industrial safety data through Business Intelligence and Machine Learning. Journal of Loss Prevention in the Process Industries, 73(February), 104608. https://doi.org/10.1016/j.jlp.2021.104608 DOI: https://doi.org/10.1016/j.jlp.2021.104608
Nithya, N., & Kiruthika, R. (2021). Impact of Business Intelligence Adoption on performance of banks: a conceptual framework. Journal of Ambient Intelligence and Humanized Computing, 12(2), 3139–3150. https://doi.org/10.1007/s12652-020-02473-2 DOI: https://doi.org/10.1007/s12652-020-02473-2
Niu, Y., Ying, L., Yang, J., Bao, M., & Sivaparthipan, C. B. (2021). Organizational business intelligence and decision making using big data analytics. Information Processing and Management, 58(6), 102725. https://doi.org/10.1016/j.ipm.2021.102725 DOI: https://doi.org/10.1016/j.ipm.2021.102725
Olszak, C. M. (2022). Business Intelligence Systems for Innovative Development of Organizations. Procedia Computer Science, 207, 1754–1762. https://doi.org/10.1016/j.procs.2022.09.233 DOI: https://doi.org/10.1016/j.procs.2022.09.233
Orcajo, J., & Fonseca, P. (2022). Business Intelligence’s Self-Service Tools Evaluation. Technologies. https://doi.org/10.3390/technologies10040092 DOI: https://doi.org/10.3390/technologies10040092
Phillips-Wren, G., Daly, M., & Burstein, F. (2021). Reconciling business intelligence, analytics and decision support systems: More data, deeper insight. Decision Support Systems, 146(September 2020), 113560. https://doi.org/10.1016/j.dss.2021.113560 DOI: https://doi.org/10.1016/j.dss.2021.113560
Risco-Ramos, R., Pérez-Aguilar, D., Casaverde-Pacherrez, L., & Vásquez-Díaz, E. (2022). Use of a business intelligence framework in the management of the quality of electricity supply in small and medium-sized companies. Revista DYNA, 89(221), 31–40. DOI: https://doi.org/10.15446/dyna.v89n221.99085
Saura, J. R., & Bennett, D. R. (2019). A three-stage method for data text mining: Using UGC in business intelligence analysis. Symmetry, 11(4). https://doi.org/10.3390/sym11040519 DOI: https://doi.org/10.3390/sym11040519
Schwade, F. (2021). Social Collaboration Analytics Framework: A framework for providing business intelligence on collaboration in the digital workplace. Decision Support Systems, 148(July 2020), 113587. https://doi.org/10.1016/j.dss.2021.113587 DOI: https://doi.org/10.1016/j.dss.2021.113587
Shao, C., Yang, Y., Juneja, S., & GSeetharam, T. (2022). IoT data visualization for business intelligence in corporate finance. Information Processing and Management, 59(1), 102736. https://doi.org/10.1016/j.ipm.2021.102736 DOI: https://doi.org/10.1016/j.ipm.2021.102736
Tardío, R., Maté, A., & Trujillo, J. (2022). Beyond TPC-DS, a benchmark for Big Data OLAP systems (BDOLAP-Bench). Future Generation Computer Systems, 132, 136–151. https://doi.org/10.1016/j.future.2022.02.015 DOI: https://doi.org/10.1016/j.future.2022.02.015
Tavera Romero, C. A., Hamilton Ortiz, J., Khalaf, O. I., & Ríos Prado, A. (2021). Web application commercial design for financial entities based on business intelligence. Computers, Materials and Continua, 67(3), 3177–3188. https://doi.org/10.32604/cmc.2021.014738 DOI: https://doi.org/10.32604/cmc.2021.014738
Tešendić, D., & Krstićev, D. B. (2019). Business intelligence in the service of libraries. Information Technology and Libraries, 38(4), 98–113. https://doi.org/10.6017/ital.v38i4.10599 DOI: https://doi.org/10.6017/ital.v38i4.10599
Torres, R., & Sidorova, A. (2019). Reconceptualizing information quality as effective use in the context of business intelligence and analytics. International Journal of Information Management, 49(July 2018), 316–329. https://doi.org/10.1016/j.ijinfomgt.2019.05.028 DOI: https://doi.org/10.1016/j.ijinfomgt.2019.05.028
Tunowski, R. (2020). Sustainability of commercial banks supported by business intelligence system. Sustainability (Switzerland), 12(11), 1–17. https://doi.org/10.3390/su12114754 DOI: https://doi.org/10.3390/su12114754
Ulloa, P. A. G., Castillo, D. V. C., Mena, V. M. P., & Jacome, D. J. R. (2020). Business Intelligence in the Administrative Management of a Distribution Company in the Electricity Sector. 3C Tic, 9(3), 43–67. DOI: https://doi.org/10.17993/3ctic.2020.93.43-67
Václav, C., Gabriel, F., Blanka, K., Libor, K., & Michal, T. (2021). Utilization of business intelligence tools in cargo control. Transportation Research Procedia, 53(2019), 212–223. https://doi.org/10.1016/j.trpro.2021.02.028 DOI: https://doi.org/10.1016/j.trpro.2021.02.028
Vanegas, D. A., Tarazona Bermudez, G. M., & Rodriguez Rojas, L. A. (2020). Mejora de la toma de decisiones en ciclo de ventas del subsistema comercial de servicios en una empresa de IT. Revista Científica, 38(2), 174–183. https://doi.org/10.14483/23448350.15241 DOI: https://doi.org/10.14483/23448350.15241
Varona-Taborda, M.-A., Mosquera-Ramírez, J.-C., Medina-Moreno, C.-A., Lemus-Muñoz, D.-F., Muñoz-Hernández, C.-J., Arias-Iragorri, C.-G., Varona-Taborda, M.-A., Mosquera-Ramírez, J.-C., Medina-Moreno, C.-A., Lemus-Muñoz, D.-F., Muñoz-Hernández, C.-J., & Arias-Iragorri, C.-G. (2021). Business Intelligence for the Programs of the Secretaries of Health, Education and Planning in a Territorial Entity. Revista Facultad de Ingeniería, 30(58), 2021. DOI: https://doi.org/10.19053/01211129.v30.n58.2021.13826
Villegas-Ch, W., Palacios-Pacheco, X., & Luján-Mora, S. (2020). A business intelligence framework for analyzing educational data. Sustainability (Switzerland), 12(14), 1–21. https://doi.org/10.3390/su12145745 DOI: https://doi.org/10.3390/su12145745
Vinicio, F., Pineda, C., & Nuñez, W. (2022). Revista Ciencias Pedagógicas e Innovación Aplicación de técnicas de Business Intelligence ( BI ) y Big Data Analytics en entornos de aprendizaje virtual Applying Business Intelligence ( BI ) and Big Data Analytics techniques in virtual learning environmen. IX, 7–19. https://doi.org/10.26423/rcpi.v9i2.463 DOI: https://doi.org/10.26423/rcpi.v9i2.463
Viteri, A. E., Cruzado, J. G., & Huaman, L. A. (2022). Methodology for Business Intelligence Solutions in Internet Banking Companies. International Journal on Advanced Science, Engineering and Information Technology, 12(3), 1173–1181. https://doi.org/10.18517/ijaseit.12.3.13670 DOI: https://doi.org/10.18517/ijaseit.12.3.13670
Wang, J., Omar, A. H., Alotaibi, F. M., Daradkeh, Y. I., & Althubiti, S. A. (2022). Business intelligence ability to enhance organizational performance and performance evaluation capabilities by improving data mining systems for competitive advantage. Information Processing and Management, 59(6), 103075. https://doi.org/10.1016/j.ipm.2022.103075 DOI: https://doi.org/10.1016/j.ipm.2022.103075
Xavier Reyes-Mena, F., Marcelo Fuertes-Diaz, W., Enrique Guzman-Jaramillo, C., Perez-Estevez, E., Fernando Bernal-Barzallo, P., & Javier Villacis-Silva, C. (2018). Application of business intelligence for analyzing vulnerabilities to increase the security level in an academic CSIRT. Revista Facultad De Ingenieria, Universidad Pedagogica Y Tecnologica De Colombia, 27(47), 21–29. DOI: https://doi.org/10.19053/01211129.v27.n47.2018.7747
Xu, J. J., & Babaian, T. (2021). Artificial intelligence in business curriculum: The pedagogy and learning outcomes. International Journal of Management Education, 19(3), 100550. https://doi.org/10.1016/j.ijme.2021.100550 DOI: https://doi.org/10.1016/j.ijme.2021.100550
Xu, Y., Li, X., Mustakim, F. bin, Alotaibi, F. M., & Abdullah, N. N. (2022). Investigating the business intelligence capabilities’ and network learning effect on the data mining for start-up’s function. Information Processing and Management, 59(5), 1–10. https://doi.org/10.1016/j.ipm.2022.103055 DOI: https://doi.org/10.1016/j.ipm.2022.103055
Yasir, M., Attique, M., Latif, K., Chaudhary, G. M., Afzal, S., Ahmed, K., & Shahzad, F. (2021). Deep-learning-assisted business intelligence model for cryptocurrency forecasting using social media sentiment. Journal of Enterprise Information Management, ahead-of-print(ahead-of-print). https://doi.org/10.1108/JEIM-02-2020-0077 DOI: https://doi.org/10.1108/JEIM-02-2020-0077
Yiu, L. D., Andy, C. Y., & Abe PL, J. (2020). Business Intelligence Systems and Operational Capability: An Empirical Analysis of High- Tech Sectors. 120(6), 1–42. DOI: https://doi.org/10.1108/IMDS-12-2019-0659
Zheng, W., Wu, Y. C. J., & Chen, L. (2018). Business intelligence for patient-centeredness: A systematic review. Telematics and Informatics, 35(4), 665–676. https://doi.org/10.1016/j.tele.2017.06.015 DOI: https://doi.org/10.1016/j.tele.2017.06.015
Žigienė, G., Rybakovas, E., Vaitkienė, R., & Gaidelys, V. (2022). Setting the Grounds for the Transition from Business Analytics to Artificial Intelligence in Solving Supply Chain Risk. Sustainability, 14(19), 11827. https://doi.org/10.3390/su141911827 DOI: https://doi.org/10.3390/su141911827
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2024 Cristian Perales-Domínguez, Jeison Eli Sánchez-Calle, Danny Lévano-Rodriguez, Katherine Gallegos-Carrillo
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Los autores retienen sus derechos:
a. Los autores retienen sus derechos de marca y patente, y tambien sobre cualquier proceso o procedimiento descrito en el artículo.
b. Los autores retienen el derecho de compartir, copiar, distribuir, ejecutar y comunicar públicamente el articulo publicado en la Revista Científica de Sistemas e Informática (RCSI) (por ejemplo, colocarlo en un repositorio institucional o publicarlo en un libro), con un reconocimiento de su publicación inicial en la RCSI.
c. Los autores retienen el derecho a hacer una posterior publicación de su trabajo, de utilizar el artículo o cualquier parte de aquel (por ejemplo: una compilación de sus trabajos, notas para conferencias, tesis, o para un libro), siempre que indiquen la fuente de publicación (autores del trabajo, revista, volumen, número y fecha).
