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The capacity of nations to collect, govern, analyse and act upon data has become a defining determinant of public value, competitiveness and resilience. This paper synthesises the state of the art in national analytics capacity, the interlocking set of infrastructures, human capital, institutional and governance arrangements that allow a country to convert data into decisions at scale, and charts a forward-looking research agenda. We situate the discussion in the momentum generated by the United Nations “data revolution” agenda and the World Bank’s framing of data as a resource for development, and we organise recent advances into four themes: data infrastructure and platforms; skills and human capital; institutions and governance; and public sector use cases. Across these themes we observe genuine progress, the maturation of open government data ecosystems, the professionalisation of data science roles, the diffusion of cloud and interoperability standards, and a growing evidence base on analytics capabilities and value realisation. To make the synthesis actionable we describe a five-level national analytics maturity model spanning six capability dimensions, offering a common vocabulary for assessment and target-setting. We then examine persistent open challenges, including fragmented data infrastructures, acute skills shortages, weak data governance, uneven data literacy, and the equity and trust risks that accompany data-intensive government. Finally, we propose concrete future opportunities and research directions: capability-maturity measurement, human-capital pipelines, federated and privacy-preserving infrastructure, institutional design for stewardship, and impact evaluation of analytics investments. The paper is intended as a compact orientation for researchers, policymakers and practitioners building analytics capacity at national scale.
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Uchechi Mary-Linda Unamma (2026) studied this question.
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