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
Low-code
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.
Real-time
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.
Ease-of-use
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.
Solution coverage
