Difference between conceptual and logical data models
The basic distinction between a conceptual and a logical data model is that a conceptual data model depicts entities and their relationships, whereas a logical data model includes attributes, primary and foreign keys, as well as entities and relationships.
In general, data modeling is the process of developing a data model using the data that is currently available. A data model is a representation of data objects and their relationships. Overall, this procedure aids in the visual representation of data and the extraction of business insights. There are several different forms of data models, including conceptual and logical data models.
What is a Conceptual Data Model, and how does it work?
Entities and relationships are represented in a conceptual data model. A relationship is an affiliation or a dependency between two entities, whereas an entity is a real-world thing. It doesn’t say anything about the qualities or the primary key. Overall, the conceptual data model represents the most important items as well as their relationships. To put it another way, it does not give information in the same way as logical or physical data models do.
What does a logical data model imply?
A logical data model is more detailed than a conceptual data model in describing the data. However, it is not used to generate a real database. There are no entities, relationships, or attributes missing. The features or properties of an entity are described by these attributes. A primary key and a foreign key are also included in a logical data model. It is also possible to perform normalization. The normalization level is usually the third normal form.
There is yet another data model, the physical data model, in addition to the conceptual and logical models. It aids in the implementation of the database itself. It is more sophisticated than the logical data model because it includes information such as table names, column names, and data types for columns.
What’s the Difference Between a Conceptual and a Logical Data Model?
A conceptual data model helps identify the highest-level connections between the various elements, whereas a logical data model defines the data in as much detail as possible, independent of how it will be technically stored in the system. This clarifies the primary distinction between a conceptual and a logical data model.
The primary purpose of a developing data model is to ensure that the functional team’s data items are appropriately represented. We should start with a conceptual data model and add more specifics as more information becomes available, refining it from a conceptual to a logical model. Data modeling is the process of identifying the information that must be stored in a database.
In addition, when it comes to data modeling, there are three main models to consider. Conceptual and logical data modeling are two of them. The basic distinction between a conceptual and a logical data model is that a conceptual data model shows entities and their relationships, but a logical data model includes attributes, primary and foreign keys in addition to entities and connections.