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Performance measure analysis and data pipeline integration for enhanced dashboard visualisation
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Resumo(s)
The growing demand for data analytics underscores the importance of advanced computational tools and data visualisation techniques, while Business Intelligence (BI) systems play a pivotal role in collecting, integrating, and analysing diverse data sources to enhance decision-making processes and organisational performance in the evolving landscape of technological advancements. This Master’s Final Work details an internship at VISPIRON SYSTEMS GmbH, contributing to the "BI@systems" project by establishing data pipelines and automated processes for performance measures. The project focused on two key performance measures: Green Projects and Liquidity.
For Green Projects, a standardised methodology was developed, including a comprehensive definition and the creation of a "Green Calculator" to accurately determine the environmental impact of projects. This process ensured more reliable performance measurements and better alignment with sustainability goals. For Liquidity, challenges in data integration were addressed by merging multiple data sources, enhancing the accuracy of liquidity contribution measurements.
The implementation of these measures on a BI dashboard provided management with a comprehensive overview of the company's performance, despite initial limitations due to manual data input and delays in infrastructure setup. The project's outcomes demonstrated significant progress in automating data processes, improving data quality, and enhancing the decision-making framework within the organisation.
Descrição
Mestrado Bolonha em Data Analytics for Business
Palavras-chave
Business Intelligence Performance measures Data pipelines Green Projects
Contexto Educativo
Citação
Tronsberg, Anna (2024). “Performance measure analysis and data pipeline integration for enhanced dashboard visualisation”. Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestão
Editora
Instituto Superior de Economia e Gestão