Field Validation in Grooper
"Field validation" refers to the various ways Grooper can warn users a Data Field or Data Column cell value may be inaccurate (e.g. invalid). Invalid fields are set to an error state, making it more obvious for reviewers something is wrong. The Data Viewer may also be configured such that the Review task cannot be completed until the error is resolved.
Ways to validate data in Grooper
There are several ways data in a Data Model is validated in Grooper:
- The Data Field/Data Column's Value Type configuration validates data based on what type of information is expected (e.g. decimal values, datetime values, string values, or other types of values)
- "Required" fields are considered invalid if no value is collected.
- Is Valid expressions
- Calculated Value expressions (when using "Validate" mode or "SetIfEmpty" mode and a value is present)
- Database Lookups
- Data Rules
Value Types
Required Fields
Is Valid expressions
Calculated Value expressions
Database Lookups
|
⚠ |
BE AWARE: Setting "Is Valid" expressions on a lookup field can be problematic. Set "Is Valid" expressions on target fields (or other fields in the Data Model) instead. Grooper's validation logic has an order of operations that can make it seem like "Is Valid" expressions on lookup fields do not work. This is not really the case. Instead, the lookup's validation is taking priority. Lookup validation presumes an error should be thrown if the lookup misses. In more nuanced scenarios, the results of the lookup need to be used to validate something based on some condition. "Is Valid" expressions are useful for validating data using conditional logic. However, they should not be configured on lookup fields.
|