In the rapidly evolving digital economy, global enterprises require immediate access to actionable insights to remain competitive and responsive. Real-time data integration has become the cornerstone of Operational Business Intelligence (OBI), enabling organizations to monitor, analyze, and act upon business events as they occur. Unlike traditional business intelligence systems that rely on batch processing, OBI demands architectures capable of handling high-velocity data from diverse, distributed sources with minimal latency. This paper explores the doctrinal foundations and technological frameworks of real-time data integration architectures that support OBI in global enterprises. It discusses architectural models such as federated systems, event-driven frameworks, and data mesh approaches that ensure scalability, compliance, and interoperability across international boundaries. The paper also examines the convergence of cloud computing, AI, and edge technologies with real-time data processing, highlighting their collective impact on enterprise agility. Legal and ethical considerations—including data privacy, governance, and algorithmic transparency—are integrated into the analysis to provide a comprehensive view of implementing real-time systems responsibly. The research concludes by proposing a unified, scalable, and legally compliant framework tailored to the needs of globally distributed enterprises aiming for real-time operational intelligence.