Power BI Visual Data Quality Free v1.1.0.0

Data Health Panel (Power BI Visual)

A clear signal for the health of the data behind the report.

A Power BI custom visual that evaluates whether data can be trusted by showing a weighted 0-100 health score, four quality KPI tiles, and a plain-English diagnostic issue list.

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Features

Weighted Data Health Score

Computes a 0-100 score from completeness, freshness, uniqueness, and validity using intent-driven Power BI field buckets.

Completeness Checks

Measures the average percent of non-blank values across fields selected for completeness.

Freshness Evaluation

Compares the latest selected date against fresh and stale hour thresholds.

Uniqueness Detection

Calculates distinct-value rates and flags duplicate identifier values, with row limits for distinct-count performance.

Category Validity Review

Checks category fields for blanks, low-frequency categories, and high fragmentation.

Plain-English Issue List

Ranks diagnostic messages by severity and links issues to the related quality dimension.

Included Capabilities

Free

  • Weighted Data Health Score
  • Completeness Checks
  • Freshness Evaluation
  • Uniqueness Detection

Advanced

  • Show or hide the health score, KPI tiles, and issue list
  • Adjust base font size for report layouts
  • Configure fresh hours, stale hours, blank thresholds, low-frequency thresholds, fragmentation thresholds, and row limits
  • Override good, warning, and bad score colors

Field buckets

Score formula: 0.4 * Completeness + 0.25 * Freshness + 0.2 * Uniqueness + 0.15 * Validity

Purpose-built inputs for quality checks.

Fields to Check Completeness

Up to 20 fields

Fields where blanks or nulls reduce the completeness score.

Fields to Check Uniqueness

Up to 20 fields

Identifier fields where repeated values reduce the uniqueness score.

Field to Check Freshness

1 date field

A date field used to evaluate how old the dataset is.

Fields to Validate Categories

Up to 20 fields

Category fields checked for blanks, low-frequency values, and fragmentation.

Use cases

Data Analysts BI Developers IT Operations Data Governance

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