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

 

Đã lưu trong:
Chi tiết về thư mục
Tác giả: Zárate-Sánchez, Roberto
Định dạng: artículo original
Trạng thái:Versión publicada
Ngày xuất bản:2024
Miêu tả: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.
Quốc gia:Portal de Revistas UNED
Tổ chức giáo dục:Universidad Estatal a Distancia
Repositorio:Portal de Revistas UNED
OAI Identifier:oai:revistas.uned.ac.cr:article/5150
Truy cập trực tuyến:https://revistas.uned.ac.cr/index.php/index/article/view/5150
Từ khóa:Big data
falacias
sesgos
paradojas
análisis de datos
fallacies
biases
paradoxes
data analysis
sophismes
biais
analyse de données
falácias
vieses
paradoxos
análise de dados