Background. The use of big data in higher education planning is a strategic issue in the era of digital transformation, demanding data-driven decision-making. Purpose. Aims. This research aims to analyze the characteristics and sources of big data, its use in national education planning, the challenges it faces, and the strategies for its strengthening. Method. The research uses a qualitative, descriptive-exploratory design, employing interviews with resource persons from the National Development Planning Agency and documentation studies. Results. The results of the study show that big data in higher education has complex characteristics, is large and diverse, and is dynamic. Its use has been employed in mapping human resource needs and policy formulation, but it remains descriptive. The main challenges faced are data fragmentation, limited system integration, human resource capacity, and data governance. Conclusion. The ideal model emphasizes cross-sectoral integration based on analytics technology. Therefore, it is necessary to strengthen digital infrastructure, human resource capacity, data integration policies, and data-based culture to support more effective and sustainable higher education planning.
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