Architecting Intelligent Decentralized Data Systems to Enable Analytics with Entropy-Aware Governance, Quantum Readiness and LLM-Driven Federation

Enterprises pursuing AI-driven transformation face a critical tradeoff: centralized consistency vs. decentralized scalability. The "Data Platform Unification Paradox" captures this dilemma. Building on our prior NLPI 2025 paper, this extended version integrates technical depth, mathematical models, and concrete architectures, especially for integrating Data Mesh with Quantum Databases and LLM Agents. A federated architecture is proposed using graph-theoretic models and entropy-based data valuation. We introduce a formal structure to evaluate platform complexity and propose intelligent agent-based governance models to operationalize data sharing across domains. This work aims to move beyond conceptual frameworks by proposing actionable blueprints for next-generation, intelligent data ecosystems.