<![CDATA[Digital transformation has created new opportunities for reformulating educational policy through the utilization of big data, educational analytics, and social analysis. The availability of data concerning learner characteristics, learning outcomes, family socioeconomic conditions, the distribution of educators, school infrastructure, and access to technology enables policymakers to gain a more comprehensive understanding of educational issues. However, the use of data in educational policy cannot rely solely on computational capabilities and statistical modeling. Quantitative data must be integrated with social analysis to uncover structural inequalities, power relations, cultural diversity, regional characteristics, and the experiences of groups vulnerable to educational exclusion. This article aims to analyze the conceptual relationship between big data and social analysis, and to formulate a framework for educational policy reform that is evidence-based, equitable, participatory, and accountable. The study employs a qualitative approach, utilizing an integrative literature review covering educational analytics, data governance, digital transformation, social justice, and educational policy. The analysis involves thematic categorization, conceptual synthesis, and the formulation of policy implications. The findings highlight five key requirements: cross-sectoral data integration, social interpretation of educational indicators, the strengthening of policymakers' analytical capacity, the protection of personal data, and policy evaluation focused on promoting equity. This article proposes a "Data and Social Analysis Synergy" framework that links data collection, the diagnosis of inequalities, policy formulation, implementation, and evaluation in a continuous cycle. Within this framework, technology serves as an instrument to support decision-making, while ethical considerations, social justice, and public accountability remain the foundational pillars of educational policy.]]>
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