Proposal of a BI/SSBI System for Knowledge Management of the Traffic of a Network Infrastructure – A University of Trás-os-Montes e Alto Douro Case Study

  • José Bessa
  • Frederico Branco
  • António Rio Costa
  • Ramiro Gonçalves
  • Fernando Moreira
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 745)

Abstract

The data volume in organizations has grown at an ever-increasing rate and part of it is associated with the operation of the network infrastructure used to support systems and applications. Given the importance of this infrastructure for organizations and the large amount of data that their operation originates, it is fundamental to manage and monitor it so that it can perform well. The previous concern is transversal to higher education institutions, where the research team assumed as important the development of a BI/SSBI system for the Informatics and Communications Services of the institution where it operates (UTAD), which allows the managing of all data volume; that enables it to be transformed into information and knowledge, which are fundamental resources to support decision-making processes. The purpose of this article is to demonstrate the usefulness of a BI/SSBI system in the described context, therefore a system of this type is presented, along with the adopted technologies, the performed tests and the obtained results.

References

  1. 1.
    Santos, V., Pereira, J., Martins, J., Gonçalves, R., Branco, F.: Creativity as a key ingredient of information systems. In: Mejia, J., Munoz, M., Rocha, Á., Calvo-Manzano, J. (eds.) Trends and Applications in Software Engineering: Proceedings of the 4th International Conference on Software Process Improvement CIMPS’2015, pp. 283–291. Springer, Cham (2016)Google Scholar
  2. 2.
    Gonçalves, R., Martins, J., Branco, F., Perez-Cota, M., Oliveira, A.-Y.M.: Increasing the reach of enterprises through electronic commerce: a focus group study aimed at the cases of Portugal and Spain. Comput. Sci. Inf. Syst. 13, 927–955 (2016)CrossRefGoogle Scholar
  3. 3.
    Taylor, M.J., Gresty, D., Askwith, R.: Knowledge for network support. Inf. Softw. Technol. 43, 469–475 (2001)CrossRefGoogle Scholar
  4. 4.
    Branco, F., Martins, J., Gonçalves, R., Bessa, J., Costa, A.: A decision support platform for IT infrastructure management: the university of Trás-os-Montes e Alto Douro services of information and communications case study. In: 10th Iberian Conference on Information Systems and Technologies (CISTI), 2015, pp. 1–7. IEEE (2015)Google Scholar
  5. 5.
    Branco, F., Gonçalves, R., Martins, J., Cota, M.P.: Decision support system for the agri-food sector-the sousacamp group case. In: WorldCIST 2015, pp. 553–563 (2015)CrossRefGoogle Scholar
  6. 6.
    Sterbenz, J.P.G., Hutchison, D., Çetinkaya, E.K., Jabbar, A., Rohrer, J.P., Schöller, M., Smith, P.: Resilience and survivability in communication networks: strategies, principles, and survey of disciplines. Comput. Netw. 54, 1245–1265 (2010)CrossRefGoogle Scholar
  7. 7.
    Lee, S., Levanti, K., Kim, H.S.: Network monitoring: present and future. Comput. Netw. 65, 84–98 (2014)CrossRefGoogle Scholar
  8. 8.
    Chen, H., Chiang, R.H.L., Storey, V.C.: Business intelligence and analytics: from big data to big impact. MIS Q. 36, 1165–1188 (2012)Google Scholar
  9. 9.
    Branco, F., Martins, J., Gonçalves, R.: Das Tecnologias e Sistemas de Informação à Proposta Tecnológica de um Sistema de Informação Para a Agroindústria: O Grupo Sousacamp. RISTI - Revista Ibérica de Sistemas e Tecnologias de Informação, pp. 18–32. RISTI (2016)Google Scholar
  10. 10.
    Ramakrishnan, T., Jones, M.C., Sidorova, A.: Factors influencing Business Intelligence (BI) data collection strategies: an empirical investigation. Decis. Support Syst. 52, 486–496 (2012)CrossRefGoogle Scholar
  11. 11.
    Sharda, R., Delen, D., Turban, E., King, D.: Business Intelligence: A Managerial Perspective on Analytics. Pearson Education Limited, New York (2015)Google Scholar
  12. 12.
    Stone, M., Woodcock, N.: Interactive, direct and digital marketing: a future that depends on better use of business intelligence. J. Res. Interact. Mark. 8, 4–17 (2014)CrossRefGoogle Scholar
  13. 13.
    Jang, Y., Ebert, D.S., Gaither, K.: Time-varying data visualization using functional representations. IEEE Trans. Vis. Comput. Graph. 18, 421–433 (2012)CrossRefGoogle Scholar
  14. 14.
    Janvrin, D.J., Raschke, R.L., Dilla, W.N.: Making sense of complex data using interactive data visualization. J. Account. Educ. 32, 31–48 (2014)CrossRefGoogle Scholar
  15. 15.
    Chhajed, S.: Learning ELK Stack. Packt Publishing, Birmingham (2015)Google Scholar
  16. 16.
    Kononenko, O., Baysal, O., Holmes, R., Godfrey, M.W.: Mining modern repositories with elasticsearch. In: Proceedings of the 11th Working Conference on Mining Software Repositories, pp. 328–331 (2014)Google Scholar
  17. 17.
    Sanjappa, S., Ahmed, M.: Analysis of Logs by Using Logstash, pp. 579–585. Springer, Singapore (2017)Google Scholar
  18. 18.
    Gupta, Y.: Kibana Essentials. Packt Publishing, Birmingham (2015)Google Scholar
  19. 19.
    Prakash, T., Kakkar, M., Patel, K.: Geo-identification of web users through logs using ELK stack. In: 2016 6th International Conference - Cloud System and Big Data Engineering (Confluence), pp. 606–610 (2016)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • José Bessa
    • 1
  • Frederico Branco
    • 1
    • 2
  • António Rio Costa
    • 1
  • Ramiro Gonçalves
    • 1
    • 2
  • Fernando Moreira
    • 3
  1. 1.University of Trás-os-Montes e Alto DouroVila RealPortugal
  2. 2.INESC TEC and UTADUniversity of PortoPortoPortugal
  3. 3.IJP, REMITUniversity PortucalensePortoPortugal

Personalised recommendations