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It’s important to make a distinction between the concept model and the data model
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The IIBA BABOK guide defines a data model as follows:
A data model describes the entities, classes or data objects relevant to a domain, the attributes that are used to describe them, and the relationships among them to provide a common set of semantics for analysis and implementation.
The concept model helps the expression of natural-language statements and supplies them with semantic meaning. They don’t deal with data in terms of unifying, simplifying or codifying it. The vocabulary of concept models is tailored to suit complex and knowledge-intensive domains, so it’s much richer.
In most cases, concept models are represented graphically just like data models. The typical representation of a concept model is a relationship diagram, while data models use entity relationship diagrams or ERDs. However, they are devoid of distractions to business stakeholders which may make them less understandable to someone outside of the knowledge domain. So, concept models are more business-friendly of the two. Data models commonly require knowledge of notions and some IT background.
While concept models revolve around concepts, data models are centred around things, entities, and classes. It’s often easy to create a data model based on a concept model. The reverse, or deriving concept model from the data model, is, more or less, impossible.
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