How to create a conceptual data model

A conceptual data model is a structured business view of the data required to support business processes, record business events, and track related performance measures.

The main elements of the conceptual model are:

Entity: is a person, organization, object, or concept about which information is stored.

Information about entities is captured as attributes: characteristics or traits that describes an entity.

Relationship: a dependency or an association between two entities.

Relationships are further qualified by identifying their cardinality: the number of instances of one entity related to instances of another entity.

This article describes how a business analyst may approach creating a conceptual data model while defining business use cases.

Here is an example of a conceptual model representing the domain of ski resorts:

This model captures five entities and the relationships between them: SkiResort, Summit, Lift, LIftTicket, and ResortStatistics.

Watch the video below to see how this model was created using information from a free Kaggle data set:

Conceptual data modelling is a useful analysis technique that allows to:

  • Name key business entities
  • Capture relationships between business entities
  • Enforce consistent terminology
  • Identify concepts that exist independent of technology implementations
  • Support business knowledge

For business analysts and architects, it is an excellent tool to have in your toolbox to create a shared understanding of data and business requirements.

Please share your thoughts!

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