Preserve referential integrity with consistent mapping in an entire data ecosystem to match data across tables, databases and systems.
Referential integrity is a concept in database management that ensures consistency and accuracy between tables in a relational database. Referential integrity would ensure that every value that corresponds to “Person 1” of “Table 1” corresponds to the correct value of “person 1“ in “Table 2” and any other linked table.
Enforcing referential integrity is crucial for maintaining the reliability of test data in a relational database as part of non-production environments. It prevents data inconsistencies and ensures that relationships between tables are meaningful and reliable for proper testing and software development.
Consistent mapping ensures that referential integrity across tables, databases and systems is preserved as part of de-identification.
For any column that has the First Name mocker applied with the Consistent Mapping feature enabled, the first name values of “Karen” will be consistently mapped to the same Synthetic Mock Value, which is “Olivia” in the example.
For any column that has the SSN mocker applied with the Consistent Mapping feature enabled, the SSN values of “755-59-6947” will be consistently mapped to the same Synthetic Mock Value, which is in “478-29-1089” in the example.
Consistent mapping works across tables
Consistent mapping works across databases
Consistent mapping works across systems
Test data in a relational database environment should preserve referential integrity to be usable. Maintaining referential integrity in non-production environments, such as those used for testing and software development, is important for several reasons:
Users can apply consistent mapping in the Syntho Engine over workspaces, at workspace level and on column level for each mocker. This enables the application of domain-specific consistent mapping, providing users with flexibility and the ability to generate accurate test data with preserved referential integrity.