Poor data quality, redundant information, and lost data can have a significant financial and operational impact on organizations, potentially consuming 15% to 25% of operating budgets. Data errors created during research, experimentation, or reporting can spread throughout processes, becoming more difficult and costly to correct over time. In scientific research, unresolved errors can undermine credibility, while in business they can damage customer trust and brand reputation. Negative perceptions can lead customers to leave, especially as company reputation increasingly influences purchasing decisions. Small mistakes, if ignored, can escalate into larger issues that affect product quality, compliance, decision-making, and organizational performance. By implementing strong data management

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