Modifying Validation Rules

Before you run the Validate Data diagnostic in Data Quality Analysis, you can create or modify Validation rule sets using the Rule Set Editor. The rule sets enable you to analyze where your exposure data is missing key information and whether it contains any invalid combinations of attributes.

Completeness Rules:

Enable you to check key exposure data for missing values or for particular user-specified values that might have a significant impact on modeled losses.

Reasonability Rules:

Enable you to compare key attributes to each other so that you can see instances where seemingly mismatched data is included in the exposure data. An example of mismatched exposure data could be where a location was entered with a Commercial Parking occupancy AND with a Wood Frame or Mobile Home construction. Large numbers of locations that violate these types of reasonability rules indicate that the data may not be correct, which could affect the accuracy of the loss estimates, depending on the perils being analyzed.

During the analysis, the system flags any locations that violate the selected rules and displays them as analysis results.