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Types of Data Models

Data modeling is the process of creating data and storing them in the database. It offers both conceptual and visual representation of the data, which presents a comprehensive foundation for the various information related to a business. It shows associations and rules between various data objects and contains information, policies, compliances, securities, semantics, and many other equally important factors that are significant for an organization. There are three types or levels in data models; conceptual data model, logical data model, and physical data model.

Conceptual Data Model

Conceptual data modeling defines what the model contains. It establishes entities, their attributes, and the relationship between two entities. The data presented in the conceptual model of data is general rather than specific, and this leads to its reputation of being abstract. The intention behind the conceptual data model is to organize and design business concepts and rules. As mentioned already, at this level, data is generic rather than specific, therefore, it does not contain metadata or descriptions of various entities and their attributes.

Conceptual data has three elements:

  1. Entity
  2. Attributes
  3. Relationship

Entity refers to physical objects or real-world things such as a customer and a product. Attributes refer to the features or characteristics of the entities, for example, the name and number of the customer, and the name and price of the product. The relationship is the association between two entities such as the association of sale between product and customer. Therefore, the given example is the basics of a conceptual data model. They are created by business stakeholders and data architects to organize and scope the basic design of the business.

Logical Data Model

The logical data model is the next level of organizing and designing data. It expands the conceptual data model by including more attributes such as time, month, product id, store description, and much more in the logical data model. They also contain key and non-key attributes and introduce the relationship between primary key and foreign key among entities and their attributes. As mentioned already, the logical data has more details than the conceptual data because it tends to include more attributes and many other important relationships, that is why it needs database management software.

Physical Data Model

A physical data model is the next level of data modeling. It expands upon the logical data model by adding more information to the data, also known as metadata or meta descriptions of the business and entities. It requires database management software as well and it is technical because it changes the data to rows and columns. Because of its technical understanding, it is not user-friendly and requires an expert to manage it. A conceptual data model can be easily enhanced, logical data can also be enhanced but a physical data model is difficult and takes more effort to enhance.

Data models are the conceptual and visual representation of business data. It is a laborious process and consumes a lot of time initially but in the longer run, it keeps an organization’s data management and IT infrastructure effective and healthy.

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