Cloud Migration Strategies for Enterprise Data Platforms: Architectural Patterns and Implementation Roadmaps

With the world data volume growing above 180 zettabytes in 2025, and with generative AI becoming a standard business ability, the oldest on-premise data warehouses have become economically and technically unsustainable. This practitioner guide is a high-level guide derived based on the experiences learned throughout hundreds of successful migrations of petabytes that have been carried out in the period between 2023 and 2025. It analyses the entire range of business motivation and business challenges, introduces the five most prevalent migration approaches (rehost, replatform, refactor, hybrid/ multi-cloud, and blended), discusses the transformative move in the prevalent ETL-ELT pattern and in the traditional data lake-modern Lakehouse and Data Mesh patterns, and provides a roadmap to move to, and implement in phases. Particular focus is given to integrating zero-trust security, regulatory compliance (GDPR, HIPAA, data-sovereignty laws), performance engineering, and FinOps practices into the initial level of development. The outcome is a repeatable structure that allows businesses not only to save costs but to develop cloud-native analytics engines to drive real-time decision making, AI-first innovation and sustainable competitive advantage in an ever more data- and intelligence-oriented world.