Analysis of Features in Big Data Projects: A Systematic Literature Review

• Autores: Ojeda, Mariel Liliana, Vegega, Cinthia, Pollo Cattaneo, María F.
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Universidad de Lima
• Repositorio: Revistas - Universidad de Lima
• Lenguaje: español
• OAI Identifier: oai:revistas.ulima.edu.pe:article/7457
• Enlace del recurso: https://revistas.ulima.edu.pe/index.php/Interfases/article/view/7457
• Nivel de acceso: acceso abierto
• Materia: methodology; big data technology; enterprise data management; metodología; tecnología big data; gestión de datos empresariales

In the implementation of big data projects, several problems are identified that may be due to different factors, such as the low quality of the data used with anomalies that may affect the accuracy of the results or the lack of clarity in the business objectives. This situation can lead to errors in the decision making process, delays in deliveries and even the cancellation of the project. In this context, the present work arises from the need to compile previous research in order to know the importance of the application of a working methodology in big data projects. The objective is to identify the approaches of the most used methodologies and to analyze the characteristics of each one, as well as the common or transversal characteristics that allow the combination, or adaptation, of different methodologies in the same project. The generation of large volumes of data from different sources and formats ncreases the challenge of verifying quality, as they may present anomalies that affect the accuracy of the results obtained.