Membangun Taxonomy Riset Big Data Analytics dan Business Intelligence: Systematic Literature Review dalam Konteks Manajemen Informatika - Tribuana, Dhimas; Dewi Haryanti Agustan, Andi; Hidayat; Halimah, Endang; Dianah, Koas; Isiswanty (Plexi Digital Indonesia, 2025)
Digital transformation has propelled the role of Business Intelligence (BI) from a mere reporting system to a strategic data-driven platform. This study aims to map the state of the art of BI through a Systematic Literature Review (SLR) guided by the PRISMA 2020 framework. A total of 50 scholarly articles published between 2010 and 2025 were systematically analyzed, sourced from both open-access databases and standard repositories (Scopus, Web of Science, Google Scholar, Semantic Scholar, and DOAJ). The analysis produced a taxonomy dividing the literature into five main domains: BI Foundations, Big Data Analytics, Data Governance & Quality, Real-Time & Stream Processing, and BI-AI Integration. The findings indicate that BI research evolves progressively, beginning with conceptual foundations, expanding toward advanced analytic capabilities, reinforcing data governance, accelerating real-time processing, and culminating in integration with Artificial Intelligence (AI) and Generative AI (GenAI). The study offers theoretical implications by providing a comprehensive conceptual framework for BI research, practical implications by guiding organizations in adopting BI-AI technologies effectively, and policy implications by emphasizing the need for adaptive regulation in data governance and AI ethics. Limitations include the restricted publication period and reliance on academic literature. Future research is recommended to incorporate grey literature and empirical case studies to enhance practical relevance.