Exploring Logical Challenges in Data Visualization and Analysis in Big data Architectures: A Focus on Fallacies, Biases, and Paradoxes

 

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Библиографические подробности
Автор: Zárate-Sánchez, Roberto
Формат: artículo original
Статус:Versión publicada
Дата публикации:2024
Описание:In this qualitative research, an identification and characterization of some of the main logical errors made when analyzing and visualizing data in Big Data architectures are conducted through a documentary and bibliographic review. It is worth noting that errors are systematized considering three categories: fallacies, biases, and paradoxes. The article aims to serve as guidance for individuals engaged in these tasks in both public and private sectors. Additionally, it provides insight into research lines related to epistemology and ethics in Big Data.
Страна:Portal de Revistas UNED
Институт:Universidad Estatal a Distancia
Repositorio:Portal de Revistas UNED
Язык:Español
OAI Identifier:oai:revistas.investiga.uned.ac.cr:article/5150
Online-ссылка:https://revistas.uned.ac.cr/index.php/rna/article/view/5150
Ключевое слово:Big data
falacias
sesgos
paradojas
análisis de datos
fallacies
biases
paradoxes
data analysis
sophismes
biais
analyse de données
falácias
vieses
paradoxos
análise de dados