Federated Computing A Data-Driven Business Infrastructure

Abstract

As organizations increasingly rely on distributed data assets, they require secure, scalable, and efficient infrastructures that ensure privacy, compliance, and business control. Federated Computing (FC) addresses this need as a conceptual infrastructure framework built on four key pillars: a) distributed data assets for data sovereignty, b) federated services for privacy-preserving analytics, c) standardized APIs for system interoperability, and d) distributed ledger technology for data security and collaboration. FC is modular and adaptable, allowing organizations to choose the proper modules and components that ensure seamless integration with existing platforms and regulatory requirements. The paper introduces FC's conceptual foundation, explores its deployment models, and demonstrates how it enables organizations to unlock value from distributed data assets to drive innovation, collaboration, and value creation, including both internal data utilization and external data monetization. The broader applicability of FC is pivotal for utilizing distributed data assets among external organizations and staff within an organization.

Keywords: Data Collaboration, Federated AI, Privacy-Preserving Computation, Data Valuation, Data Sovereignty