• DocumentCode
    162676
  • Title

    Methodological framework for data processing based on the Data Science paradigm

  • Author

    Pacheco, F. ; Rangel, C. ; Aguilar, Jesus S ; Cerrada, M. ; Altamiranda, J.

  • Author_Institution
    Centro de Estudios en Microcomputacion y Sist. Distribuidos CEMISID, Univ. de Los Andes Merida, Merida, Venezuela
  • fYear
    2014
  • fDate
    15-19 Sept. 2014
  • Firstpage
    1
  • Lastpage
    12
  • Abstract
    This paper describes the steps for achieving data processing in a methodological context, which take part of a methodology previously proposed by the authors for developing Data Mining (DM) applications, called "Methodology for the development of data mining applications based on organizational analysis". The methodology has three main phases: Knowledge of the Organization, Preparation and treatment of data, and finally, development of the DM application. We will focus on the second phase. The main contribution of this proposal is the design of a methodological framework of the second phase based on the paradigm of Data Science (DS), in order to get what we have called “Vista Minable Operacional” (VMO) from the “Vista Minable Conceptual” (VMC). The VMO built is used in the third phase. This methodological framework has been applied in two different cases of study, oil and public health.
  • Keywords
    data handling; data mining; VMC; VMO; Vista Minable Conceptual; Vista Minable Operacional; data mining applications; data processing; data science paradigm; organizational analysis; Context; Data mining; Data processing; Organizations; Silicon compounds; Surges; Synthetic aperture sonar; data mining; data science; health management; industrial processes; knowledge engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing Conference (CLEI), 2014 XL Latin American
  • Conference_Location
    Montevideo
  • Type

    conf

  • DOI
    10.1109/CLEI.2014.6965184
  • Filename
    6965184