Affiliation:
1. Department of Computer Science, School of Computing, College of Science, Engineering and Technology (CSET), Science Campus, University of South Africa (Unisa), Johannesburg 1709, South Africa
2. Digital Transformation and Innovation, Graduate School of Business Leadership (SBL), Midrand Campus, University of South Africa (Unisa), Midrand 1686, South Africa
Abstract
Business intelligence (BI) refers to technologies, tools, and practices for collecting, integrating, analyzing, and presenting large volumes of information to enable improved decision-making. A modern BI architecture typically consists of a data warehouse made up of one or more data marts that consolidate data from several operational databases. BI further incorporates a combination of analytics, data management, and reporting tools, together with associated methodologies for managing and analyzing data. An important goal of BI initiatives is to improve business decision-making for organizations to increase revenue, improve operational efficiency, and gain a competitive advantage. In this article, we analyze qualitatively various prominent business intelligence (BI) frameworks in the literature and develop a comprehensive BI framework from these. Through the technique of qualitative propositions, we identify the properties, respective advantages, and possible disadvantages of the said BI frameworks to develop a comprehensive framework aimed mainly at data management, incorporating the advantages and eliminating the disadvantages of the individual frameworks. The BI landscape is vast, so as a limitation, we note that the new framework is conceptual; hence, no implementation or any quantitative measurement is performed at this stage. That said, our work exhibits originality since it combines numerous BI frameworks into a comprehensive framework, thereby contributing to conceptual BI framework development. As part of future work, the new framework will be formally specified, followed by a practical phase, namely, conducting case studies in the industry to assist companies in their BI applications.
Funder
University of South Africa
Reference40 articles.
1. Management Support with Structured and Unstructured Data—An Integrated Business Intelligence Framework;Kemper;Inf. Syst. Manag.,2008
2. An evaluation of how big-data and data warehouses improve business intelligence decision making;Martins;Trends Innov. Inf. Syst. Technol.,2020
3. Alsmadi, I. (2017). Design Solutions for User-Centric Information Systems, IGI Global.
4. Ackermann, J.G., and van der Poll, J.A. (2020, January 16–18). Reasoning Heuristics for the Theorem-Proving Platform Rodin/Event-B. Proceedings of the 2020 International Conference on Computational Science and Computational Intelligence (CSCI’20), Las Vegas, NV, USA.
5. Saunders, M.N.K., Lewis, P., and Thornhill, A. (2022). Research Methods for Business Students, Pearson. [8th ed.].
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