Risk analysis of using big data in computer sciences

Today, as technologies mature and people are encouraged to contribute data to organizations’ databases, more transactions are being captured than ever before. Meanwhile, improvements in data storage technologies have made the cost of evaluating, selecting, and destroying legacy data considerably greater than simply letting it accumulate. On the one hand, the excess of stored data has considerably increased the opportunities to interrelate and analyze them, while the moderate enthusiasm generated by data warehousing and data mining in the 1990s has been replaced by a rampant euphoria about big data and data analytics. But, is this as wonderful as seems? This paper presents a risk analysis of Big Data and Big Data Analytics based on a review of quality factors.

• Autores: Silva, Jesus; Pineda Lezama, Omar Bonerge; Romero Marin, Ligia Cielo; Solano, Darwin; Silva Fernández, Claudia Susana
• Tipo de recurso: Article of journal
• Fecha de publicación: 2019
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/5989
• Acceso en línea: https://hdl.handle.net/11323/5989; https://repositorio.cuc.edu.co/
• Palabra clave: Data management; Data quality; Decision making; Data analysis; Gestión de datos; Calidad de datos; Toma de decisiones; Análisis de datos
• Rights: openAccess
• License: CC0 1.0 Universal