This eBook presents a structured, five-stage framework for building trusted, high-quality data across the enterprise. It begins with documenting and defining data through catalogs, glossaries, classification, and lineage; then moves to profiling, monitoring, and AI-driven observability. It outlines methods to improve data via transformation, matching, remediation workflows, and master data practices. The framework adds prevention through real-time validation and “data quality firewall” controls, and concludes with governance, stewardship, ownership, and policy enforcement to ensure long-term trust, scalability, and regulatory compliance.

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