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Data quality

Data quality describes how accurate, complete, consistent and timely your data is.

Written by Reflective Data experts · updated Oct 5, 2026

Poor data quality quietly undermines decisions: duplicate events, missing values, broken joins and stale tables. Automated tests catch many of these problems before they reach a dashboard.

Quality is a continuous process, built into pipelines and models rather than checked once.

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