Ensuring Regulatory Compliance in Cloud-based Big Data Systems: A Framework for Global Operations Adhering to GDPR and CCPA

Abstract

Cloud-based big data systems increasingly serve as critical infrastructure for organizations that collect, process, and store vast amounts of sensitive information. As global regulations evolve, specifically in jurisdictions that uphold stringent compliance standards such as the General Data Protection Regulation and the California Consumer Privacy Act, the complexity of ensuring end-to-end data protection has escalated. This paper introduces a framework designed to address challenges that arise when organizations operate across multiple legislative environments, emphasizing core elements of governance and technological enforcement to safeguard personal data. The framework interweaves encryption, identity and access management, and distributed storage solutions, striving to streamline data provenance and transfer monitoring for comprehensive adherence to these regulations. By examining the interplay between data flows, regulatory obligations, and risk mitigation, it illuminates systematic strategies that can be integrated throughout the entire data lifecycle, from ingestion to archival. The subsequent sections present an in-depth discussion of underlying cloud architectures, advanced mathematical models for compliance risk evaluation, and robust methods for real-time privacy preservation in large-scale analytics. The overarching goal is to facilitate a structured approach that addresses the nuanced constraints of multinational operations, ensuring both efficiency and regulatory alignment across disparate jurisdictions while maintaining the agility demanded by modern cloud infrastructures.