A Framework for Self-Service Business Intelligence

Rosa Matias, Maria Piedade

2024

Abstract

Building an effective Business Intelligence solution involves several key steps. Recently, low-code software tools have allowed casual users - those with domain-specific knowledge of a case study - to develop custom solutions independently of IT teams. This is the era of Self-Service Business Intelligence. However, some drawbacks have been identified due to casual users' lack of Business Intelligence expertise. In response, a framework is proposed, introducing the role of casual power users and specifying the Business Intelligence knowledge they should possess. Additionally, the framework aims to integrate Business Intelligence methodologies more cohesively with data visualization and data storytelling development cycles. As a proof of concept, the framework was applied to develop a solution for monitoring class attendance at a higher education institution. In this case study, a casual power user is able to identify, early in the semester, which classes require adjustments to improve resource management and pedagogical outcomes. The contextualization provided by the framework enabled that user to successfully uncover critical insights.

Paper Citation

in Harvard Style

Matias R. and Piedade M. (2024). A Framework for Self-Service Business Intelligence. In Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR; ISBN 978-989-758-716-0, SciTePress, pages 408-415. DOI: 10.5220/0013015700003838

in Bibtex Style

@conference{kdir24,
author={Rosa Matias and Maria Piedade},
title={A Framework for Self-Service Business Intelligence},
booktitle={Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR},
year={2024},
pages={408-415},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013015700003838},
isbn={978-989-758-716-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR
TI - A Framework for Self-Service Business Intelligence
SN - 978-989-758-716-0
AU - Matias R.
AU - Piedade M.
PY - 2024
SP - 408
EP - 415
DO - 10.5220/0013015700003838
PB - SciTePress