Data Warehouse projects in organizations as a basis for obtaining in-formation are having a great development today. The maturity of generation methodologies has reached significant acceptance. This allows us to focus on addressing the study of the lack of adaptability to the high dynamics of the changes in requirements of this type of projects. Data Science and Natural Language Processing allow us to integrate areas of knowledge and provide tools to solve this problem. A methodological model is proposed to partially automate the stages of generation of Data Warehouse instances based on requirements.
Información general
Fecha de exposición:octubre 2021
Fecha de publicación:2021
Idioma del documento:Inglés
Evento:VII Simposio Argentino de Ciencia de Datos y GRANdes DAtos (AGRANDA 2021) - JAIIO 50 (Modalidad virtual)
Institución de origen:Sociedad Argentina de Informática e Investigación Operativa
Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)