The Root Causes of Data Quality Issues

Poor data quality often stems from five fundamental causes: input errors, infrastructure failures, incorrect transformations, invalid assumptions, and ontological misalignment. Understanding these root causes can help businesses improve their data quality management by focusing on what is knowable and controllable. By adopting a systematic approach and learning from other communities, the number and severity of data quality issues can be reduced.

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