Metrics

The purpose of Qualdo is to help you locate, track & eliminate all data quality issues. Qualdo Metrics measure and track data quality performance.

Qualdo has two types of metrics.
  • Default Metrics

  • Custom Metrics

Default Metrics

Data Quality Metrics - To monitor Data Quality of each Dataset.

Data Quality Metrics

Default Data Quality Metrics are enabled for each Dataset to monitor Data Quality. Enabled metrics are computed for each new Dataset version on a Qualdo managed interval which is configured for each metric, based primarily on dependencies. Metrics for new Dataset versions are queued for computation as soon as possible.

  1. Data Completeness

    Measures the completeness of the data. Qualdo uses a default definition to identify how much Null/Empty/Invalid data and rows present. The definition of completeness can be customized.

  2. Data Timeliness

    Measures the recency for the Datasets. Recency is measured in days once the Dataset is configured and is recency reset for each new Dataset version.

  3. Data Conformity

    Identifies whether the data conforms to certain standards. For example, a date attribute has to be in one of the standard formats (“dd/mm/yyyy”, “yyyy/mm/dd”, etc.) Other examples are gender, SSN, email. The definition of conformities can be customized.

  4. Data Accuracy

    Identifies numeric data outliers/anomalies in the Dataset.

  5. Data Consistency

    For two environments, such as staging and production, identify two Datasets that should be consistent. This metric measures overall consistency between the two selected Datasets. Data consistency is not enabled automatically, but the user may enable the metric as needed.

  6. Data Drift

    Measure the drifts between different versions of the Dataset. Identifies the variation in the distribution and statistical properties of the attributes between different versions of the Dataset.

  7. Data Uniqueness

    Identifies the unique values in the Dataset.

Custom Metrics

Custom Metrics may be written, deployed, enabled and disabled. A Custom Metric may be additional, or may be used in place of a Default Metric. To learn more about how to create Custom Metrics refer to tutorial on creating Custom Metrics.