Exploring Logical Challenges in Data Visualization and Analysis in Big data Architectures: A Focus on Fallacies, Biases, and Paradoxes
Guardado en:
| Autor: | |
|---|---|
| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2024 |
| Descripción: | 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 |
| Institución: | Universidad Estatal a Distancia |
| Repositorio: | Portal de Revistas UNED |
| Lenguaje: | Español |
| OAI Identifier: | oai:revistas.investiga.uned.ac.cr:article/5150 |
| Acceso en línea: | https://revistas.uned.ac.cr/index.php/rna/article/view/5150 |
| Palabra clave: | Big data falacias sesgos paradojas análisis de datos fallacies biases paradoxes data analysis sophismes biais analyse de données falácias vieses paradoxos análise de dados |