This study aims to analyze a government big data governance model for improving the effectiveness of integrated public services. The research focuses on inter-agency data integration, system interoperability, data security, and the use of public data in integrated service delivery. This study employs a qualitative method with an exploratory-descriptive approach and conceptual governance model development. Data were collected from secondary and documentary sources, including recent peer-reviewed journal articles, policy documents, institutional reports, digital government guidelines, regulatory materials, and scholarly works related to big data governance, data-driven government, interoperability, data security, and public-service innovation. The data were analyzed using thematic analysis by classifying findings into inter-agency data integration, system interoperability, data quality, data security, institutional coordination, collaborative governance, public-service effectiveness, and accountability. The findings show that integrated public services require more than digital applications or one-stop service portals. Effective integration depends on shared data standards, interoperable systems, secure data exchange, reliable data quality, and coordinated institutional responsibility. The study contributes by proposing a cross-sector government big data governance model consisting of institutional coordination, data integration, system interoperability, data quality assurance, data security, and collaborative service use. This model emphasizes that big data must be governed as a strategic public asset to improve service speed, accuracy, accessibility, transparency, and accountability.