A carregar...
Publicação
Business Intelligence systems in academia: A Practical Application in Universidade Católica Portuguesa
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 3.22 MB | Adobe PDF |
Orientador(es)
Resumo(s)
Digital transformation, analytics, instinct information are buzzwords that sum up the contemporary age we live in, where there is an exponential need for information that is readily accessible, correct, and available. Universities worldwide feel this pressure of a data-driven approach that requires the power of a centralized analytical platform that Business Intelligence (BI) solutions provide, in order to adjust their current market offer based on the insights provided.
In this project report it was discussed an implementation of a BI prototype in an academic institution, more specifically at Universidade Católica Portuguesa (UCP). The main goal was to migrate the current approach of using transactional databases to an analytical solution. This allowed the University (1) to better understand key performance indicators that affect main competitive areas, such as students (enrolments, graduates), and (2) to apply these insights to their strategic business goals.
To achieve such endeavours, this BI project at UCP followed an adapted Business Intelligence Roadmap methodology. The input data came from transactional databases and Excel files. Microsoft BI solutions were the main source of technology to deal with the ETL pipeline and report development.
In terms of results, this project allowed UCP to take another step towards a data-driven decision-making mindset, with a system that can help in the identified business needs, but also with implications that can be further explored outside of UCP boundaries, by providing a practical end-to-end use case, that can support other Universities environments and projects.
Descrição
Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
Palavras-chave
Analytics University Data Warehouse Business Intelligence Dimensional Modelling Data-Driven Decision Making