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

 

Na minha lista:
Detalhes bibliográficos
Autor: Zárate-Sánchez, Roberto
Formato: artículo original
Estado:Versión publicada
Data de Publicação:2024
Descrição: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.
País:Portal de Revistas UNED
Recursos:Universidad Estatal a Distancia
Repositorio:Portal de Revistas UNED
Idioma:Español
OAI Identifier:oai:revistas.investiga.uned.ac.cr:article/5150
Acesso em linha:https://revistas.uned.ac.cr/index.php/rna/article/view/5150
Palavra-chave:Big data
falacias
sesgos
paradojas
análisis de datos
fallacies
biases
paradoxes
data analysis
sophismes
biais
analyse de données
falácias
vieses
paradoxos
análise de dados