ERBuilder Data Modeler provides three methods to validate a data model

August 08th, 2020,

During the process of designing a data model, it is very important to deliver a valid and consistent final model. This validation must pass at least by these two methods, syntactic validation and validation by the test data.

Validating a model syntactically means checking each entity if it is correct and complies with database modeling standards. The second method is to validate the data model by manipulating real test data. This last validation method sometimes requires the use of a tool other than the one used for modeling. In other case, some tool does the modeling and the generation of the test data but is it safe to populate a database with thousands of data, which can later turn out to be unsatisfactory? It can be a waste of time and effort.

The ideal is to test your model in an environment such as a sandbox with virtual test data without physically populate the database.

ERBuilder is a GUI data-modeling tool; a reference for easy data modeling provides three ways to check for potential mistakes and ambiguities in the created model. The first method of validation is the use of the model checker utility to detect syntax errors. The second method consist to validate a data model by manipulating and querying virtual test data in a database sandbox. These virtual data are not persistent in a database; these data are stored only in memory. Finally, the third way to validate a model is by generating web user interface for CRUD applications based on your model.