The digital transformation wave has fundamentally altered how enterprises manage, process, and derive value from their data assets. Legacy data warehouse systems, while reliable workhorses for decades, increasingly struggle to meet the demands of modern analytics workloads, real-time processing requirements, and the exponential growth of data volumes. This paper examines comprehensive strategies for migrating enterprise data warehouses from traditional on-premises architectures to cloud-native solutions. We analyze the technical, organizational, and operational considerations that influence migration success, presenting a framework that balances immediate business continuity needs with long-term strategic objectives. Through analysis of real-world implementations and emerging architectural patterns, we offer evidence-based recommendations for enterprises at various stages of cloud adoption. Our findings suggest that successful migrations require not merely technological shifts but fundamental rethinking of data governance models, skills development pathways, and organizational processes to fully capitalize on the elasticity, cost efficiency, and innovation potential of cloud-native data platforms.