Cross-Platform Data Management: Patterns and Best Practices (Published)
Cross-platform data management has emerged as a critical discipline for organizations navigating today’s complex technology ecosystems. This article examines how enterprises can effectively manage data across heterogeneous environments spanning legacy systems, cloud platforms, and edge computing nodes. It explores the fundamental challenges of data silos, inconsistent governance, performance bottlenecks, and technical debt that organizations face when operating in multi-platform landscapes. The article presents key architectural patterns including data federation, virtualization, microservices, and event-driven integration that enable cohesive data management. It details essential technologies for implementation success, from integration platforms and API management to containerization and data cataloging tools. The discussion extends to best practices for implementation and governance frameworks that ensure consistency across platforms while accommodating the unique characteristics of diverse environments. Through practical insights and implementation strategies, the article offers a roadmap for organizations seeking to build resilient, scalable data ecosystems that span multiple platforms.
Keywords: data integration, federation, governance automation, hybrid architecture, microservices