Modernization of a Health Surveillance Data Platform : A Retrospective on Legacy-to-Cloud Migration

Modernizing mission-critical public health data platforms requires more than infrastructure migration; it demands preservation of complex business semantics, regulatory compliance, and analytical integrity across heterogeneous cloud ecosystems. This paper presents a governance-driven, two-release cloud modernization framework for migrating a legacy disease surveillance platform from SQL Server to a cloud-native architecture integrating Salesforce, Snowflake, Informatica IDMC, and Tableau. The proposed approach combines metadata-driven data integration, reverse-engineered business-rule preservation, phased migration execution, reusable transformation pipelines, automated reconciliation, and cloud-native orchestration to minimize migration risk while improving scalability and data quality. The first release establishes foundational data profiling, schema transformation, and baseline validation, whereas the second release extends enterprise-scale migration through incremental loading, optimized orchestration, cross-platform reconciliation, and performance tuning for operational and analytical consistency. Results demonstrate significant improvements in reconciliation coverage, defect resolution efficiency, migration scalability, and enterprise data governance despite a threefold increase in migrated assets. The framework provides a repeatable reference architecture for cloud modernization of regulated healthcare and government information systems and offers practical guidance for future enterprise data platform transformations requiring operational resilience, analytical trustworthiness, and long-term maintainability.