Data Engineering Tools
Data Quality Score Calculator
Enter data quality dimension percentages to compute a composite data quality score with dimension-level grading.
No data is transmitted — everything runs locallyTool
Example — Representative default scenario — completeness 98 · accuracy 95 · timeliness 92.
Composite DQ score
97.6%
equal-weighted average
Weakest dimension
Timeliness
94.0% — focus here first
Rating
Good
Gap to 99%
1.4pp
improvement needed
About this tool
Data Quality Score Calculator
The Data Quality Score Calculator computes a composite score from completeness, validity, uniqueness, and timeliness dimensions with dbt test mapping.
• Calculate overall data quality score for a data quality report
• Identify which DQ dimension needs the most improvement
• Track data quality trend over sprints for a data engineering dashboard
• Set data quality SLOs from baseline measurements
Affiliate disclosure
Uptime, incident, and on-call management. Better Stack provides status pages, incident management, and on-call scheduling for engineering teams.
View data quality with Better Stack
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FAQ
What does this tool tell you?
The Data Quality Score Calculator computes a composite score from completeness, validity, uniqueness, and timeliness dimensions with dbt test mapping.
What affects the result most?
Data quality dimensions: completeness, validity, consistency, timeliness, uniqueness, accuracy. Completeness: non-null % for required fields — null_count / total_rows. Validity: values within expected domain — invalid_type_count / total_rows.
How should I use the result?
The calculation is deterministic — the same inputs always produce the same output — so the most useful workflow is to vary one input at a time and see which factor moves the result most. That tells you where to focus your attention before committing to a decision.