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Publicação
Sistema de Apoio à Decisão para Ciências ULisboa
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| 2.75 MB | Adobe PDF |
Orientador(es)
Resumo(s)
The growing organizational complexity and the multiplicity of information sources make it essential to establish mechanisms that ensure the availability of reliable and relevant data to support decision-making. In this context, Decision Support Systems (DSS) play a crucial role by integrating data from different information systems and presenting it in a structured and accessible manner. The present work aimed to develop a DSS platform for the Faculty of Sciences of the University of Lisbon (CIÊNCIAS ULisboa), enabling the collection, integration, and analysis of institutional data on human resources and teaching service distribution, as well as the dissemination of interactive reports to support the management of CIÊNCIAS ULisboa. To achieve this goal, a dimensional data model was designed, followed by the implementation of an automated ETL (Extract, Transform, Load) system to consolidate information from the institutional systems Census, Gremius, and Fénix. The data were extracted through API (Application Programming Interface) calls, processed to ensure their consistency, and loaded into a central repository. Subsequently, Power BI was used to structure the data models and develop interactive reports, allowing for flexible exploration and personalized consultation of information. The evaluation of the platform involved institutional decision-makers from CIÊNCIAS ULisboa, who confirmed the usefulness and adequacy of the interactive reports in addressing the initially defined business questions, particularly in analyzing trends and monitoring performance indicators. The developed solution contributes to information management at CIÊNCIAS ULisboa by providing an automated and user-friendly system. In addition to meeting current needs, it also establishes a foundation for future developments, such as the integration of new data sources or the application of more advanced analytical techniques.
Descrição
Trabalho de Projeto de Mestrado, Ciência de Dados, 2025, Universidade de Lisboa, Faculdade de Ciências
Palavras-chave
Decision Support Systems Dimensional Modeling ETL Business Intelligence Data Visualization