Background: There is growing recognition in the education sector of the critical role empirical data plays in aiding strategic decision-making and supporting personalised learning. The call for increased and more nuanced data-driven decision-making has been primarily addressed by the institutional use of student learning dashboards and learner profiles in higher education; their application and evaluation in K-12 settings remain underexplored. Existing approaches often lack robust empirical evidence, and there is limited research addressing their use in real-world classroom environments. Objectives and Methods: This study aims to bridge the knowledge gap by systematically reviewing both academic and non-peer-reviewed literature on decision-making systems in schools. The review focused on understanding the types of data used, the implementation status of dashboards and learner profiles, and the practical applications in K-2 education. The analysis included 19 academic papers as well as 10 pieces of non-peer-reviewed literature to examine the landscape of decision-making systems. Results: The analysis revealed that while academic literature highlights the underuse of diverse data types and a scarcity of real-world evaluations, non-peer-reviewed literature showcases promising holistic decision-making approaches employed by schools and government bodies globally. However, these practical applications often lack empirical validation. Conclusions: This study provides a novel contribution by exploring how researchers can move beyond stand-alone studies focusing on academic performance to gauge the success of different decision-making systems. The study also recommends that practitioners invest in more research-backed systems to create better teaching and learning practices and enhance personalised learning. By highlighting the current gaps and offering forward-looking recommendations, our study clarifies the present landscape and serves as a foundation for future research to improve student learning outcomes.