Completeness
Average percent of non-blank values across fields selected for completeness.
Documentation
A Power BI custom visual that evaluates whether data can be trusted by showing a weighted health score, four quality KPIs, and a plain-English diagnostic issue list.
Quality score
Health Score =
0.4 * CompletenessScore +
0.25 * FreshnessScore +
0.2 * UniquenessScore +
0.15 * ValidityScore Dimensions
Average percent of non-blank values across fields selected for completeness.
Latest selected freshness date compared with the current date. Fresh scores 100, warning scores 70, and stale scores 30.
Average distinct-value rate across fields selected for uniqueness.
Category checks for blanks, low-frequency categories, and high fragmentation.
Field roles
Assign fields where blanks or nulls should reduce the completeness score. Example: Country and Status.
Assign identifiers where repeated values should reduce the uniqueness score. Example: CaseID.
Assign one date field used to evaluate how old the dataset is. Example: CreatedDate.
Assign category fields where blank, low-frequency, or fragmented categories should reduce validity. Example: Status or Country.
Formatting controls
Test in Power BI Desktop
AppSource notes
The current MVP does not use external API calls, data export, local storage, eval, or unsafe dynamic script execution.