<![CDATA[Modern hospital information systems operate within fragmented and heterogeneous OLTP environments designed for transaction recording rather than strategic analytical workloads. This study designs and implements a temporal healthcare Data Warehouse for OLAP analytics supporting historical data consistency and multidimensional performance monitoring aligned with Indonesian Ministry of Health (Kemenkes RI) standards. The Kimball bottom-up methodology was applied to integrate two heterogeneous OLTP sources into a Galaxy Schema comprising two fact tables and seventeen dimension tables. The ETL pipeline was implemented using SSIS with a complete SCD Type 2 workflow preserving full patient dimension history across ward transfers and physician reassignments. The OLAP layer was constructed using SSAS Tabular with VertiPaq in-memory engine and DAX-based measures, visualized through a Power BI Executive Information System dashboard. Empirical validation using 52,321 discharged patient records over a one-year observation period demonstrated an average OLAP Speedup Ratio of 30.27× over equivalent relational SQL queries across ten benchmark runs, ranging from 2.98× (Slice) to 79.18× (Dice), with all response times below 40 ms and 100% computational accuracy across all six Kemenkes RI KPIs. The novelty lies in integrating a complete SCD Type 2 temporal model within a Galaxy Schema healthcare data warehouse, empirically validated against live heterogeneous hospital data and nationally aligned KPI standards.]]>
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