<![CDATA[The implementation of the National Assessment (AN) produces complex educational data volumes, covering the results of the Minimum Competency Assessment (AKM), Character Surveys, and Learning Environment Surveys. The management of transactional and scattered data often hinders the comprehensive education quality evaluation process. This study aims to design and implement a Data Warehouse using the Snowflake Schema method to analyze the influence of socio-economic status and school profiles on student literacy and numeracy achievements. Kimball's Nine-Step Methodology approach is used in data architecture design. Test results show that the Snowflake scheme is effective in handling regional and school dimension hierarchies by reducing storage redundancy. OLAP (Online Analytical Processing) analysis reveals significant gaps in literacy and numeracy scores based on school accreditation levels and student economic backgrounds, where school quality is proven to be a moderating variable in improving student achievements from low economic groups.]]>
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