This handbook explains why data observability, visibility into data health at any time—is essential for trust, quality, and decision-making. It outlines the four pillars (metrics, metadata, lineage, logs), options to build/buy/borrow tools, evaluation criteria, and common implementation mistakes. Case studies show faster issue detection, improved trust, and scalable analytics. Strong observability reduces downtime, prevents costly errors, and maximizes ROI by ensuring accurate, timely, and reliable data for all stakeholders.

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