Data Quality Agent

DQA is designed to reduce the time spent by GIS technicians in the validation and correction of their work. This interactive tool informs the technician of data anomalies the instant they are created. By doing so, the data anomalies can be corrected by the technician, as soon as they are detected by DQA: it is like an expert always helping you to reach accurate data. It comes with predefined data validation rules and you can write your own to match your business rules. When writing a business rule, if you know how to fix an error, the engine enables you to do so without interrupting the user.

What is DQA?

DQA is a .NET™ based Fusion™ plug-in that dynamically identifies data anomalies, and suggests potential resolution scenarios. The validation rules and anomaly resolution algorithms can be customized to fit the utility’s needs.

Why DQA?

The Data Quality Agent is designed to reduce the time spent by GIS technicians in the validation and correction of their work. This interactive tool informs the technician of data anomalies the instant they are created. By doing so, the data anomalies can be corrected by the technician, as soon as they are detected by DQA.

Fusion environment with DQA data anomaly messages and graphic identification display.

What does it do?

In general, data error detection is performed as a batch process, executed only when the GIS data update work is completed. The data anomalies report is then reviewed by a GIS technician that finds the problematic objects and performs the proper corrective action. This cycle might need to be repeated multiple times, as new errors could be introduced accidentally by the technician as he applied other changes.
DQA constantly validates the data affected by a data manipulation performed by a GIS technician. If an abnormal condition is created by the result of a data update, DQA informs the technician of the abnormal result and recommends a resolution solution.

DQA comes with the following validation rules, but is not limited to them:

• Attribute validation (mandatory, range value, length...)
• Features Relationship
• Features connectivity
• Matching phase with connected entities