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Quality ratio

The quality ratio reflects how closely your data aligns with its ideal state. It is calculated per rule and represents the proportion of valid entries compared to the total evaluated rows.

Rather than just counting issues, the quality ratio provides a normalized percentage — enabling easier comparison across small and large tables, columns, and rulesets.


How the quality ratio is calculated

The quality ratio is computed at multiple levels:


Rule level

Formula:
(Total rows for this rule – Issue rows) / Total rows for this rule

Notes:

  • "Total rows" excludes rows filtered out by rule conditions

  • Rows with excluded NULLs are not counted in the denominator

  • Multi-column rules: The quality ratio is calculated only for the first selected column

  • Table-based rules: These are considered as being based on their own column. When calculating an average quality score for the table, keep in mind that all three table-based rules have either 0 or 1 issue but are still evaluated against the total row count


Column level

Average of all rule-level quality ratios for this column


Ruleset level

Average of all column-level quality ratios for the ruleset


Tenant / Dashboard level

Average of all ruleset-level ratios the user has access to


Example calculation

If a table has 1,000 rows and 50 rows violate a rule:
→ Quality Ratio = (1000 – 50) / 1000 = 95%

If 250 valid rows are later added:
→ Quality Ratio = (1250 – 50) / 1250 = 96%


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(1) Quality scores

Each ruleset receives a score based on the quality ratio. These boundaries can be configured per ruleset. The default thresholds are:

Grade

Threshold

A

> 99% valid entries

B

> 95%

C

> 90%

D

> 85%

E

≤ 85%


(2) Quality trend charts

Displayed across the platform — on:

  • Rule level

  • Ruleset level

  • Tenant level

In each chart, you can toggle between:

  • Issue counts

  • Quality ratio (%)

Visualize how quality improves or declines over time.


Use cases

  • Benchmark data quality across business units

  • Track improvement over time

  • Identify underperforming areas needing attention

  • Share quality scores with stakeholders via BI dashboards


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Quality ratio | DQC