Artifact: Logical Data Model
Logical Data Model represents the organization business-domain concepts in a set of diagram and logical schema. The choice of representation will depend of the design approach and the target audience. It could be relational (Table - columns, association), object oriented (class - attribute association) or XML (tags) defined.
Domains: Rule AnalysisRule Governance
Data modeling is the act of exploring data-oriented structures.  Like other modeling artifacts data models can be used for a variety of purposes, from high-level conceptual models to physical data models.
Main Description

A logical data model or LDM is a graphical representation of some of the business requirements and especially the concepts manipulated by the business member. LDM is independent of the technology of implementation, and is mostly used as a communication vehicle for the business analyst and to prepare the implementation of data models.  

From the point of view of an object-oriented developer data modeling is conceptually similar to class modeling. With data modeling you identify entity types whereas with class modeling you identify classes.  Data attributes are assigned to entity type just as you would assign attributes and operations to classes. Traditional data modeling is different from class modeling because it focuses solely on data – class models allow you to explore both the behavior and data aspects of your domain, with a data model you can only explore data issues.

We use UML simple class diagram to represent a Logical Data Model but by applying Agile's principle of multiple models, it is possible to use other diagrams.

Logical Data Models are used to explore the domain concepts, and their relationships, of the problem domain.  This could be done for the scope of a single project or for the entire enterprise.  LDMs depict the logical entity types, typically referred to simply as entity types, the data attributes describing those entities, and the relationships between the entities.


Defining a logical data model prepare for future reuse, and help to build common definition of terms. This is one of major building block for enterprise data model.