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How to Think Like a Data Scientist: Application of a Variable Order Markov Model to Indicators Management

  • Gustavo IllescasEmail author
  • Mariano Martínez
  • Arturo Mora-Soto
  • Jose Roberto Cantú-González
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 405)

Abstract

The growing demand for specialists in analyzing large volumes of data has led to an emerging profile of knowledge managers known as data scientists. How to address the different and complex scenarios with mathematical methods makes a difference when to apply them successfully in a dynamic environment such as the management indicators. For this reason, the authors present in this article a case study of prognostic indicators, developed in the field of finance, making use of mathematical Markov model which has prototyped in an abstract technological implementation with the capabilities to implement cases in other contexts. The purpose of the case study is to verify if the different levels of analysis of the Markov model provide knowledge to the prognosis by indicators while the application of the proposed methodology is shown. Thus, this work introduces to the threshold of a methodology that leads to one of the ways on how to think like a data scientist.

Keywords

Data scientist Markov chains Indicators Knowledge management Forecast 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Gustavo Illescas
    • 1
    Email author
  • Mariano Martínez
    • 1
  • Arturo Mora-Soto
    • 2
  • Jose Roberto Cantú-González
    • 3
  1. 1.Faculty of Exact Sciences, Computer Science DepartmentUniversidad Nacional del Centro de la Provincia de Buenos AiresTandilArgentina
  2. 2.Mathematics Research CenterZacatecasMexico
  3. 3.Department of Industrial & Systems EngineeringSystems School, Universidad Autónoma de CoahuilaAcuñaMexico

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