A Systematic Mapping of Data Visualization in Business Intelligence

• Published in: Springer Proceedings in Mathematics and Statistics
• Main Author: Rahman N.A.; Mahmud M.; Zahari N.S.; Zukarnain Z.A.; Putra Y.H.
• Format: Conference paper
• Language: English
• Published: Springer 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209595790&doi=10.1007%2f978-981-97-3450-4_24&partnerID=40&md5=2e895f47bfe94bc8928eb0d18655fe29

Business intelligence technology enables users to apply dynamic reporting for various bodies of knowledge since multiple data sources can be integrated to produce reliable and efficient decision making. These sources allow an organization to visualize insights more easily and be user-friendly without allocating much time to interpret the data. This paper performs a systematic mapping of the role of data visualization for business reporting. The systematic mapping protocol starts with defining research questions, identifying inclusion and exclusion criteria, executing the search strategy, performing quality assessment and data extraction method, and finally, synthesis of the extracted data. The systematic mapping results produce the potential of data visualization and business intelligence as data-driven tools for business reporting. The systematic mapping yields extensive analysis of the frequency of publications according to keywords, existing business intelligence tools, and trends of data visualization according to each body of knowledge in the selected online journal database. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.