Correct Answer: A,B
Database Consistency Checks (DCCs) are designed to verify that the data in the physical database tables aligns perfectly with the metadata definitions in the Guidewire application.
The first critical scenario is whenexternal SQL scriptsare used (Option A). Guidewire's application layer usually handles all data validation and referential integrity. When a developer or DBA runs a SQL script directly against the database, they bypass these application-level checks. Running DCCs after such an operation is mandatory to ensure that the script didn't accidentally introduce null values into non-nullable columns or break foreign key constraints.
The second scenario involvesdata imports and subtype creation(Option B). When a new subtype is created with a "required" column, and data is imported-even through the UI or staging tables-there is a risk that existing records or improperly mapped import files might result in missing data for that required field. DCCs will identify these "logical" inconsistencies where the database contains a null value for a field that the application metadata now defines as mandatory.
Options C and D involve metadata changes (UI and Typelists) that do not typically risk corrupting existing table data in a way that DCCs are designed to catch. Option E is less critical because the column is "not required," so a null value is considered consistent with the data model.