Integration Of The Enterprise Information To Facilitate Decision Making

Authors

  • Manuel Hilario
  • Doris Esenarro
  • Hugo Vega
  • Ciro Rodriguez

Keywords:

ETL, HEFESTO, BI, Pentaho, decision making, enterprise, services

Abstract

The research objective is to apply business intelligence techniques to take advantage of an existing system's conditions and increase the low-cost capabilities in its Extract, Transform and Load ETL processes with snapshots integrating the company's information web services. The methodology used for the development was HEFESTO, the development time was one week applying agile methodologies, achieving a short development with well- defined and easy-to-understand phases; the tool was the Pentaho BI Suite. Using open source tools, the cost was reduced through the proposed architecture with the repository type and the DataMart with a departmental approach to the problem, increasing its decision-making capacity.

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References

Ministerio de Educación - MINEDU. Gobierno del Perú. Available at: https://www.gob.pe/minedu

M Rodríguez. Implementation process of technology in Education: The case of Blackboard 9.1 in the University of Manchester. Actualidades Investigativas en Educación. 2013; 13(3), 150-167. https://doi.org/10.15517/aie.v13i3.12043

Y Ocaña-Fernández, L Valenzuela-Fernández and L. Garro-Aburto. Inteligencia artificial y sus implicaciones en la educación superior. Propósitos y Representaciones. 2019; 7(2), 536-568. https://doi.org/10.20511/pyr2019.v7n2.274

Alfaro, O., Esenarro, D., Rodriguez, C., y Alfaro, M. R. (2021). The Unified Enterprise Architecture (AEU) as a strategic tool organizational modeling for the funtional competitiveness of universities. 3C Empresa. Investigación y pensamiento crítico. Edición Especial Tourism and University: Backbone of Peruvian Economy, 63-79. https://doi.org/10.17993/3cemp.2021.specialissue1.63-79

D Rooein, Data-Driven Edu Chatbots. Companion Proceedings of The 2019 World Wide Web Conference. 2019; 46-49. https://doi.org/10.1145/3308560.3314191

Singh, J., Joesph, M. H., & Jabbar, K. B. A. (2019). Rule-based chabot for student enquiries. Journal of Physics: Conference Series, 1228, 012060. https://doi.org/10.1088/1742-6596/1228/1/012060

Molnar, G., & Szuts, Z. (2018). The Role of Chatbots in Formal Education. 2018 IEEE 16th International Symposium on Intelligent Systems and Informatics (SISY), 1. https://doi.org/10.1109/sisy.2018.8524609

Müller, Stefan and C. Keller. “Pentaho Data Integration.” (2014).

Lee, Y.-C., & Fu, W.-T. (2019). Supporting peer assessment in education with conversational agents. Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion, 7-8. https://doi.org/10.1145/3308557.3308695

Cordova, J., Vega, H., Rodriguez, C., y Escobedo, F. (2020). Firma digital basada en criptografía asimétrica para generación de historial clínico. 3C Tecnología. Glosas de

innovación aplicadas a la pyme, 9(4), 65-85. https://doi. org/10.17993/3ctecno/2020.v9n4e36.65-85

Pandey, B., Tomar, G.S., Bhadoria, R.S., Hussain, D., Rodriguez, C.,(2020). Environment-friendly FSM design on ultra-scale architecture: energy-efficient green computing approach World Journal of Engineering, DOI: https://doi.org/10.1108/WJE- 08-2020-0397

Cerna, F., Ubalde, R., Rodriguez, C., Sotomayor, J., Yucra, D., (2020). Automation psychological assessments with cloud computing. Journal of Critical Reviews, 2020, 7(15), pp. 1565-1569. doi: 10.31838/jcr.07.15.208

Atencio, Y., Marin, J., Enriquez, R., Rodriguez, C., Petrlik, I.,(2020). A collaborative ide for graphics programming. Journal of Critical Reviews, 2020, 7(15), pp. 1570-1577. doi: 10.31838/jcr.07.15.209

Azabache, I., Rodriguez, C., Gonzales, P.,(2019) M-Learning applied to the improvement of the learning of university engineering students. Proceedings of the 2019 International Symposium on Engineering Accreditation and Education, ICACIT 2019, 2019, 9130215. doi: 10.1109/ICACIT46824.2019.9130215

Motta, V., Guillen, R., Rodriguez, C., (2019). Artificial Neural Networks to optimize learning and teaching in engineering careers. Proceedings of the 2019 International Symposium on Engineering Accreditation and Education, ICACIT 2019, 2019, 9130296. EID: 2-s2.0-85084220713

Reyes, A., Rodriguez, C., Esenarro, D. (2019). Hyper converged systems applied (HSA) methodology to optimize the process of technological renewal in data centers. International Journal of Recent Technology and Engineering, 2019, 8(2 Special Issue 11), pp. 4052-4056. doi: 10.35940/ijrte.B1592.0982S1119

Bustamante, J.C., Rodriguez, C., Esenarro, D. (2019). Real time facial expression recognition system based on deep learning. International Journal of Recent Technology and Engineering, 2019, 8(2 Special Issue 11), pp. 4047-4051.

doi: 10.35940/ijrte.B1591.0982S1119

Rodriguez C., Luque D., La Rosa C., Esenarro D. and Pandey B., "Deep Learning Applied to Capacity Control in Commercial Establishments in Times of COVID- 19," 2020 12th International Conference on Computational Intelligence and Communication Networks (CICN), Bhimtal, India, 2020, pp. 423-428, doi: 10.1109/CICN49253.2020.9242584.

Rodriguez C., Angeles, D., Chafloque R., Kaseng F. and Pandey B., "Deep Learning Audio Spectrograms Processing to the Early COVID-19 Detection," 2020 12th International Conference on Computational Intelligence and Communication Networks (CICN), Bhimtal, India, 2020, pp. 429-434, doi: 10.1109/CICN49253.2020.9242583.

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Published

2021-02-28

How to Cite

Hilario, M. ., Esenarro, D. ., Vega, H. ., & Rodriguez, C. . (2021). Integration Of The Enterprise Information To Facilitate Decision Making. The Journal of Contemporary Issues in Business and Government, 27(1), 1042–1054. Retrieved from https://cibgp.com/au/index.php/1323-6903/article/view/617

Issue

Vol. 27 No. 1 (2021): The journal of contemporary issues in business and government

Section

Articles

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