This ebook explains why modern organizations must rethink traditional data governance models in the age of AI, regulatory pressure, and data sprawl. It outlines the strengths and limitations of centralized, decentralized, and federated governance approaches, showing how each impacts trust, scalability, and accountability. The guide highlights how fragmented governance leads to inconsistent definitions, compliance risk, and stalled innovation, especially when powering AI systems. It introduces a hybrid governance model that combines centralized standards with federated execution, aligning people, processes, and technology. Core governance processes such as promotion, adoption, specialization, and generalization are explored as mechanisms for sustaining trust. The ebook positions unified, hy

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