Data Quality

Data Quality

Detecting data quality issues is done through comprehensive Data Quality Checks (aka. DQC). DataHub provides over 30 different types of pre-defined D.Q.C. including presence check, format validation, date control, comparison between sources, time-series outliers detection, tolerance check, change detection etc. Additional business and logical controls can be set up to trigger exceptions when breached. 

Key Benefits


For faster delivery, changes can be made in a matter of minutes using graphical tools directly within the app, and with no updates or restarting necessary. 


Any changes are made in real-time. This ensures that users are always working with the correct version of data, business rules, screens and even the same data model.


For unique client specifications and for a rapid integration of new applications, use graphic mapping to create an API REST or any other export in the specified format, without needing to upgrade.

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