Uso del procesamiento de lenguaje natural para derivar un modelo conceptual de Data Warehouses a partir del lenguaje del dominio

Overview & Synopsis

A Warehouse Data (data warehouse) is a storage system designed to collect, organize and analyze large volumes of data from various sources. It is used in business analysis and decision making, since it allows to consult historical information efficiently. A Warehouse Data helps companies manage, analyze and visualize data efficiently, improving decision -making based on reliable and consolidated information. One of the models to design a Data Warehouse is the multidimensional model, which allows to structure the data efficiently for analysis and reports. This model facilitates the navigation and exploration of information from different perspectives, optimizing performance in analytical consultations. Although it constitutes a valuable starting point, it is not always easy to obtain an orderly and consistent requirements specification, which integrally describes all the functionality of the model. This article proposes a tool that allows the derivation of the multidimensional model using various natural language processing techniques from the Glossary of the LEL domain.