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Publication
Data Engineering Roadmap for Implementing Business Intelligence in Higher Education
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Advisor(s)
Abstract(s)
This article addresses the implementation of
Business Intelligence (BI) systems in Higher Education
Institutions (HEIs), focusing on developing an appropriate data
architecture that meets the specificities and requirements of this
sector. With the rapid advance of information technologies,
HEIs face the growing challenge of managing a considerable
volume of data, making it essential to implement BI systems that
support informed and efficient decision-making. Using the
Design Science Research methodology, this study proposes a BI
architecture model that aligns technologies with HEIs' academic
and administrative needs and facilitates their integration and
ongoing maintenance. The model is designed to be flexible and
scalable, allowing adaptations as institutional needs evolve. The
article describes the architecture development process, from
initial planning to implementation, and discusses how this
framework can significantly improve data management and the
quality of decision-making processes in educational institutions.
The research offers practical and theoretical insights for
academics and managers seeking to optimize the use of BI in
educational contexts.
Description
Keywords
Business intelligence Higher education Data engineering Decision-making
Citation
Sequeira, Romeu; Reis, Arsénio; Branco, Frederico; Alves, Paulo (2024). Data Engineering Roadmap for Implementing Business Intelligence in Higher Education. In 9th International Conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2024, the 10th International Conference on Connected Smart Cities, CSC 2024 and the 16th International Conference on e-Health, EH 2024, Part of the 18th Multi Conference on Computer Science and Information Systems 2024, MCCSIS 2024. p. 1-6. ISBN 979-8-3503-8754-4
Publisher
IEEE