Logical data model

A logical data model also referred to as "LDM" in computer science is a representation of an organization's data, organized in terms of a particular data management technology. When ANSI first laid out the idea of a "logical schema" (in 1975 [1] ), the choices were "hierarchical" and "network". Relational had just been recognized as a data organization theory but no technology existed. Currently, the choices are "relational", "object-oriented", and "XML". Relational data is described in terms of tables and columns. Object-oriented data is described in terms of classes, attributes, and associations. XML is described in terms of "tags".

Logical data models, properly designed, should be based on the structures identified in the conceptual data model, since this describes the semantics of the business, which the logical model should also reflect. Even so, since the logical data model anticipates implementation on a finite-capacity computer, some will modify the structure to achieve certain efficiencies.

In certain organizations, there is a tendency to use the term 'Logical Data Model' to mean the 'Domain Model' or as an alternative to the domain model. While the two concepts are closely related, and having overlapping goals, domain model is more focused on capturing the concepts in problem domain than structure of the data which is associated with that domain.

What is a Logical Data Model

* Graphical representation of the business requirements
* Contains the things of importance in an organisation and how they relate to one another
* Contains business textual definitions and examples
* Validated and approved by a business representative
* Basis of physical database design

This is sometimes incorrectly called a "physical data model", which is not what the ANSI people had in mind. The physical design of a database involves deep use of particular database management technology. For example, a table/column design could be implemented on a collection of computers, located in different parts of the world. That is the domain of the physical model.

Difference of Logical & Physical Data Model

People often get confused with the fact that logical and physical data models are very different in their objectives, goals and content. Following are some key differences.

Why Build Logical Data Model

* Helps common understanding of business data elements and requirements
* Provides foundation for designing a database
* Facilitates avoidance of data redundancy and thus prevent data & business transaction inconsistency
* Facilitates data re-use and sharing
* Decreases development and maintenance time and cost
* Confirms a logical process model and helps impact analysis.

Logical Modeling Benefits

* Clarifies functional specifications and avoids assumption
* Confirms business requirements
* Facilitates business process improvement
* Focuses on requirements independent of technology
* Decreases system development time and cost
* Becomes a template for the enterprise
* Facilitates data re-use and sharing
* Faster ROI
* Gathers metadata
* Foster seamless communication between applications
* Focuses communication for data analysis and project team members
* Establishes a consistent naming scheme

References

# American National Standards Institute. 1975. “ANSI/X3/SPARC Study Group on Data Base Management Systems; Interim Report”. FDT(Bulletin of ACM SIGMOD) 7:2.