Federated Data Lakehouse Architecture for Multi-Cloud Governance, AI and Analytics

Abstract

Enterprise data architecture requirements have enhanced the pace at which scalable enterprise data architecture is being unified in a manner that is secure, intelligent, and entailed across diverse cloud environments. The federated data lakehouse architecture is a paradigm that integrates the flexibility of data lakes with the structure and management capabilities of data warehouses, while being designed for use across multi-cloud platforms. This review explains how federated lakehouses can facilitate data governance, enable distributed collaboration with AI, and support real-time analytics, while also addressing challenges related to data residency, compliance, and interoperability. The paper provides a comprehensive view of architectural components within cloud computing, data engineering, and artificial intelligence through the convergence of these domains using a federated perspective, coordinated operations, and the advantages inherent in this model. Drawing on recent literature, the article reveals the transformational potential of federated lakehouses in re-engineering enterprise information systems to align with the emerging era of decentralization and intelligent automation.