When a data modeler works with the client, his title may be a logical data modeler or a physical data modeler or combination of both. A logical data modeler designs the data model to suit business requirements, creates and maintains the lookup data, compares the versions of data model, maintains change log, generate reports from data model and whereas a physical data modeler has to know about the source and target databases properties.
A physical data modeler should know the technical-know-how to create data models from existing databases and to tune the data models with referential integrity, alternate keys, indexes and how to match indexes to SQL code. It would be good if the physical data modeler knows about replication, clustering and so on.
The differences between a logical data model and physical data model is shown below.
Logical vs Physical Data Modeling
| Logical Data Model | Physical Data Model |
| Represents business information and defines business rules | Represents the physical implementation of the model in a database. |
| Entity | Table |
| Attribute | Column |
| Primary Key | Primary Key Constraint |
| Alternate Key | Unique Constraint or Unique Index |
| Inversion Key Entry | Non Unique Index |
| Rule | Check Constraint, Default Value |
| Relationship | Foreign Key |
| Definition | Comment |
Relational Data Modeling