This white paper highlights three best practices for delivering high-quality analytical and operational public sector data. It emphasizes the costly impact of poor data quality, citing that organizations can lose $15 million annually due to bad data and that public sector employees spend about 50% of their time addressing data issues. Additionally, 47% of citizens lack trust in the government's ability to protect their personal data. The paper suggests adopting an automated approach to data testing to mitigate these problems, thus enhancing decision-making, improving compliance, and restoring trust in public sector services.

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