Trust Centric Data Architecture Enabling Secure and Scalable Enterprise Digital Transformation in Modern Distributed Environments

Enterprises undergoing digital transformation increasingly depend on distributed data ecosystems that demand strong assurances of security, integrity, and governance. This study explores how trust centric data architecture can serve as a foundational enabler for secure and scalable transformation in such environments. The research focuses on the challenge of embedding trust across complex data flows while maintaining performance and adaptability. The objective is to propose a structured architectural framework that integrates trust mechanisms throughout the data lifecycle. A mixed method approach is employed, combining qualitative examination of enterprise architecture practices with quantitative assessment of security performance, governance efficiency, and system scalability. The findings indicate that incorporating trust driven architectural principles enhances data reliability, strengthens security posture, and supports consistent governance across distributed systems. The study introduces an innovative framework that systematically aligns trust components with architectural layers, enabling transparency and control without compromising scalability. From a strategic perspective, the research provides actionable insights for organizations seeking to operationalize trusted data environments, while academically it advances the conceptual understanding of trust as an architectural construct. The study concludes that trust centric data architecture is essential for achieving resilient and secure digital transformation, offering significant value for both industry implementation and ongoing scholarly development in enterprise data systems.