Completeness Checks

Completeness checks verify that required data is present and not missing (NULL). These are critical for ensuring data integrity and preventing downstream processing issues.

Follow these best practices for completeness checks:

  • Prioritize critical business columns such as financial values and timestamps

  • Consider appropriate thresholds based on business requirements (not all columns need to be 100% complete)

  • Use count-based checks for smaller tables and percentage-based checks for larger tables

  • Combine with freshness checks for time-based columns to ensure both presence and recency

Available Metrics

  • Missing Count: Total number of NULL or empty values

  • Missing Percentage: Proportion of missing values relative to total records

Configuration Examples

Check Description

Configuration Steps

Example Check

Ensure all products have prices

  1. Select price column.

  2. Choose Missing Count check.

  3. Select = operator.

  4. Set threshold to 0.

missing_count(price) = 0

Validate low percentage of missing email addresses

  1. Select email column.

  2. Choose Missing Percentage check.

  3. Select <= operator.

  4. Set threshold to 5.

missing_percent(email) <= 5