Palabras clave
toma de decisiones
análisis de datos
inteligencia artificial
aprendizaje automático
Categorías
Cómo citar
Resumen
La inteligencia de negocios (BI) se ha consolidado como una herramienta esencial para la toma de decisiones estratégicas y operativas en diversos sectores. Mediante la recopilación, análisis y visualización de datos, BI optimiza procesos internos, mejora la precisión en la toma de decisiones y potencia la competitividad organizacional. Su aplicación en sectores como el bancario, educativo y comercial ha demostrado beneficios significativos, como la personalización en la atención al cliente, la gestión eficiente de recursos y la optimización de operaciones. Tecnologías emergentes como la inteligencia artificial (IA), el aprendizaje automático y los sistemas basados en la nube amplían las capacidades de BI, permitiendo análisis en tiempo real y mayor escalabilidad. Sin embargo, su implementación presenta desafíos relacionados con la inversión en infraestructura, la gobernanza de datos y cuestiones éticas sobre privacidad. A pesar de esto, modelos innovadores como el análisis predictivo y las plataformas en la nube destacan por su capacidad para transformar grandes volúmenes de datos en información accionable. BI no solo redefine la gestión empresarial, sino que también se posiciona como un elemento clave para enfrentar los desafíos del mercado global.
Referencias
Adeniran, I. A., Efunniyi, C. P., Osundare, O. S., & Abhulimen, A. O. (2024). Integrating business intelligence and predictive analytics in banking: A framework for optimizing financial decision-making. Finance & Accounting Research Journal. https://doi.org/10.51594/farj.v6i8.1505
Agu, E. E., Obiki-Osafiele, A. N., & Chiekezie, N. R. (2024). Enhancing market analysis using artificial intelligence for strategic business decision-making. World Journal of Engineering and Technology Research. https://doi.org/10.53346/wjetr.2024.3.1.0053
Alsibhawi, I. A. A., Yahaya, J., & Mohamed, H. (2023). Business Intelligence Adoption for Small and Medium Enterprises: Conceptual Framework. Applied Sciences. https://doi.org/10.3390/app13074121
Atmaja, P., Maulana, D. I., & Adiono, T. (2020). AI-based Customer Behavior Analytics System using Edge Computing Device. 2020 International Conference on Electronics, Information, and Communication (ICEIC), 1-2. https://doi.org/10.1109/ICEIC49074.2020.9051138
Badmus, O., Anas, S., Arogundade, J. B., & Williams, M. (2024). AI-driven business analytics and decision making. World Journal of Advanced Research and Reviews. https://doi.org/10.30574/wjarr.2024.24.1.3093
Daraojimba, A. I., Victoria, C., Ibeh, Asuzu, O. F., Olorunsogo, T., Elufioye, O. A., & Nduubuisi, N. L. (2024). Business analytics and decision science: A review of techniques in strategic business decision making. World Journal of Advanced Research and Reviews. https://doi.org/10.30574/wjarr.2024.21.2.0247
Dashora, S. (2023). Cloud-based Data Analytics for Business Intelligence. International Journal for Research in Applied Science and Engineering Technology. https://doi.org/10.22214/ijraset.2023.57219
Eboigbe, E. O., Farayola, O. A., Olatoye, F. O., Nnabugwu, O. C., & Daraojimba, C. (2023). BUSINESS INTELLIGENCE TRANSFORMATION THROUGH AI AND DATA ANALYTICS. Engineering Science & Technology Journal. https://doi.org/10.51594/estj.v4i5.616
Fruhwirth, M., Breitfuss, G., & Pammer-Schindler, V. (2020). The Data Product Canvas—A Visual Collaborative Tool for Designing Data-Driven Business Models. https://consensus.app/papers/the-data-product-canvas-a-visual-collaborative-tool-for-fruhwirth-breitfuss/c1e8a8d5ae6351ebbcc32a56352a6baf/
Haro, A., Martínez, A., Nuela, R., Criollo, M., & Pico, J. (2023). Inteligencia de negocios en la gestión empresarial: Un análisis a las investigaciones científicas mundiales. En LATAM Revista Latinoamericana De Ciencias Sociales y Humanidades (Vol. 4, Número 1, pp. 5-10).
Hossain, Q., Yasmin, F., Biswas, T. R., & Asha, N. B. (2024). Integration of Big Data Analytics in Management Information Systems for Business Intelligence. Saudi Journal of Business and Management Studies. https://doi.org/10.36348/sjbms.2024.v09i09.002
Kultygin, O., & Lokhtina, I. (2021). Business intelligence as a decision support system tool. 16, 52-58. https://doi.org/10.37791/2687-0649-2021-16-1-52-58
Kyaw, K. S., Tepsongkroh, P., Thongkamkaew, C., & Sasha, F. (2023). Business Intelligent Framework Using Sentiment Analysis for Smart Digital Marketing in the E-Commerce Era. Asia Social Issues. https://doi.org/10.48048/asi.2023.252965
Li, Y., & Li, L. (2024). Optimization of data model-driven design thinking in the software development process. Applied Mathematics and Nonlinear Sciences. https://doi.org/10.2478/amns-2024-2406
Michael, C. I., Ipede, O. J., Adejumo, A. D., Adenekan, I. O., Adebayo, D., Ojo, A. S., & Ayodele, P. A. (2024). Data-driven decision making in IT: Leveraging AI and data science for business intelligence. World Journal of Advanced Research and Reviews. https://doi.org/10.30574/wjarr.2024.23.1.2010
Moreno, C. V., Rodriguez, C., Puente, F. G., Petrlik, I., Lezama, P., & Pomachagua, Y. (2022). Business Intelligence Architecture to Improve Decision Making. 2022 14th International Conference on Computational Intelligence and Communication Networks (CICN), 7-15. https://doi.org/10.1109/CICN56167.2022.10008297
Muniswamaiah, M., Agerwala, T., Tappert, C., & Seidenberg. (2019). BUSINESS INTELLIGENCE IN BIG DATA. https://consensus.app/papers/business-intelligence-in-big-data-muniswamaiah-agerwala/de77fb5453085301a49fd237257c9bec/
Najdawi, A., & Patkuri, S. karan. (2021). Modeling Business Intelligence Process: Toward Smart Data-Driven Strategies. 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 198-202. https://doi.org/10.1109/ICCIKE51210.2021.9410804
Oskooei, A. R., & Adak, T. E. (2023). B2B Customer Engagement Customer Behaviour Forecast Application. Orclever Proceedings of Research and Development. https://doi.org/10.56038/oprd.v3i1.323
Rouhani, S., Ashrafi, A., Ravasan, A. Z., & Afshari, S. (2018). Business Intelligence Systems Adoption Model: An Empirical Investigation. J. Organ. End User Comput., 30, 43-70. https://doi.org/10.4018/JOEUC.2018040103
Salamai, A. (2021). Transforming E-commerce Operations: An Intelligent Business Intelligence Approach for Improving Customer Transaction Management. American Journal of Business and Operations Research. https://doi.org/10.54216/ajbor.020203
Sarango, A. F. H., Sinchiguano, B. E. O., Belduma, R. G. B., Herrera, B. J. S., & Alcívar, S. J. N. (2024). Riesgo Crediticio en Mutualistas: Modelos de Predicción Basados en Morosidad y Rendimiento Financiero : Credit Risk in Mutuals: Predictive Models Based on Delinquency and Financial Performance. Know Press. https://doi.org/10.70180/978-9942-7273-5-0
Sarango, A. F. H., Villamarin, J. S. V., Riera, J. V. P., Tenorio, L. E. D., Aldás, V. A. I., Cajape, N. del J. G., & Carranza, E. A. G. (2024). Avances y aportes a las ciencias económicas, financieras y empresariales: Advances and contributions to economic, financial and business sciences. Know Press. https://doi.org/10.70180/978-9942-7273-2-9
Shatat, A., Altahoo, M., & Almannaei, M. (2024). The Impact of Business Intelligence on Decision-Making Process and Customer Service. 2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS), 355-360. https://doi.org/10.1109/ICETSIS61505.2024.10459599
Sudiantini, D., Fadhilah, E. S. N., Wijayanti, M., Pratiwi, R., & Hanifah, R. N. (2024). UTILIZATION OF BUSINESS INTELLIGENCE IN BUSINESS DECISION MAKING. SENTRI: Jurnal Riset Ilmiah. https://doi.org/10.55681/sentri.v3i6.2966
Tarmizi. (2023). Big Data Analysis for Strategic Decision Making in Business Information Systems. Journal Informatic, Education and Management (JIEM). https://doi.org/10.61992/jiem.v5i2.75
Vysotska, V., Berko, A., Chyrun, L., Chyrun, S., Havrylyshyn, O., Smirnova, O., Sokulska, N., Sokhatska, O., & Shakleina, I. (2024). Formal Data Integration Models Development for Intelligent Electronic Commerce Systems. 298-327. https://doi.org/10.31110/colins/2024-3/021
Yulianto, A. A., & Kasahara, Y. (2018). Implementation of Business Intelligence With Improved Data-Driven Decision-Making Approach. 2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI), 966-967. https://doi.org/10.1109/IIAI-AAI.2018.00204
Zhang, Y. (2024). Utilizing machine learning algorithms for consumer behaviour analysis. Applied and Computational Engineering. https://doi.org/10.54254/2755-2721/49/20241186
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Derechos de autor 2025 Multidisciplinary Latin American Journal (MLAJ)