Discipline that uses and develops techniques with the aim of providing intelligence to computers and predicting situations from data.
Published in Chapter:
Tools, Technologies, and Methodologies to Support Data Science: Support Technologies for Data Science
Ricardo A. Barrera-Cámara (Universidad Autónoma del Carmen, Mexico), Ana Canepa-Saenz (Universidad Autónoma del Carmen, Mexico),
Jorge A. Ruiz-Vanoye (Universidad Politécnica de Pachuca, Mexico), Alejandro Fuentes-Penna (Centro Interdisciplinario de Investigación y Docencia en Educación Técnica, Mexico), Miguel Ángel Ruiz-Jaimes (Universidad Politécnica de Morelos, Mexico), and Maria Beatriz Bernábe-Loranca (Benemérita Universidad Autónoma de Puebla, Mexico)
Copyright: © 2021
|Pages: 23
DOI: 10.4018/978-1-7998-3053-5.ch004
Abstract
Various devices such as smart phones, computers, tablets, biomedical equipment, sports equipment, and information systems generate a large amount of data and useful information in transactional information systems. However, these generate information that may not be perceptible or analyzed adequately for decision-making. There are technology, tools, algorithms, models that support analysis, visualization, learning, and prediction. Data science involves techniques, methods to abstract knowledge generated through diverse sources. It combines fields such as statistics, machine learning, data mining, visualization, and predictive analysis. This chapter aims to be a guide regarding applicable statistical and computational tools in data science.