<![CDATA[Digital monitoring is increasingly central to modern information systems, enabling continuous observation of assets, processes, and services through real-time data collection. Although advances in analytics and machine learning support data-driven decisions, monitoring, analytics, and decision-making are still often developed in isolation, limiting effective integration. This study maps digital monitoring research, classifies monitoring characteristics, and identifies gaps in linking monitoring with decision-making. Using a PRISMA-based Systematic Literature Review of Scopus-indexed journal articles published between 2020 and 2025, 97 studies were selected and analysed through thematic synthesis. The review shows that digital monitoring spans nine major domains, with infrastructure, environmental, and manufacturing applications most dominant. The study’s main contribution is a multidimensional taxonomy that classifies monitoring approaches by monitoring object, mode, analytics type, application domain, and information system orientation. This taxonomy also positions digital monitoring within the evolution of information systems toward decision intelligence. Findings indicate that current research remains largely technical, relying mainly on descriptive and predictive analytics, while integration with decision intelligence is still limited. A notable gap appears in digital service contexts, especially proactive user-experience monitoring in Internet Service Providers (ISP).]]>
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