What does "extending the business data model" (Fachdatenmodell erweitern) involve, and why is adding the fields not enough?

The IAM's business data model gets the new information objects or attributes (for example licence and class under person), and a maintenance process is defined that keeps them correct; without the process the new fields quickly go stale.

The business data model (Fachdatenmodell) is the IAM's description of the things it knows about and how they relate: a person has a first name and a last name and owns one or more accounts, and so on. A qualitative extension adds to it. In the fleet example, person gains two attributes: driving licence and vehicle class.

Defining the model change properly means answering more than "which column":

• Meaning and format: what exactly is a "class"? Which value list (B, C1, D...)? Can a person have several?
• Relation: does it hang off the person (one per human) or the account (per system access)?
• Maintenance (Pflege): who enters and updates the value, from which source, how often? A licence can be withdrawn tomorrow; a value that was right at entry is not right forever.
• Lifecycle: when is it deleted again (for example when the person leaves)?

The maintenance process is drawn explicitly next to the model change because a data model only describes slots. Data quality comes from the process that fills them.

Go deeper:

• Conceptual schema (Wikipedia) — the business-level model of entities, attributes and relationships that the IAM extends.
• Data quality (Wikipedia) — accuracy, timeliness and completeness as properties that need ongoing maintenance.