Research aims: This study presents a systematic literature review of empirical research on Big Data Analytics (BDA) in the public sector. The purpose is to examine how BDA has been applied, the research settings, dominant themes, and the lessons learned across the literature.Design/Methodology/Approach: Using a review method adapted from Hoque (2014), the study analyzed 64 articles published between 2015 and 2023 sourced from the Scopus database. Articles were selected based on relevance, journal quality, accessibility, and methodological rigor.Research findings: The review identified six key thematic areas in public sector BDA research: accountability, energy efficiency, sustainability, innovation, analytics, and governance. The dominant theories found include Big Data Theory, Stakeholder Theory, and Agency Theory, while archival and survey methods were the most commonly employed research approaches. The United Kingdom, United States, and international multi-country studies contributed the most publications.Theoretical contribution/ Originality: The novelty of this study lies in its exclusive focus on the public sector, its integrative thematic analysis using co-word mapping, and its implications for academic theory building, practical implementation, and policy formulation in public administration.Practitioner/Policy implication: This study can be used these insights to develop effective BDA strategies, enhance performance, and foster trust in public institutions through more responsive and evidence-based decision-making.Research limitation/Implication: Future research is expected to further study and research: (1) The Impact of Big Data on the Public Sector using journals or other references outside the Scopus database; (2) Future research can use keywords that are different from this research, (3) and can also access more journals to be reviewed.