Relational Data Modeling vs. Conceptual Modeling

Relational data modeling and conceptual modeling are two different approaches to designing a database.
Relational data modeling is a method of designing a database based on the relational model, which organizes data into tables and defines relationships between the tables. The focus of relational data modeling is on the specific technical details of how the data will be stored and accessed, including the selection of data types, keys, and constraints. Conceptual modeling, on the other hand, is a higher-level approach to database design that focuses on the overall structure and relationships of the data, rather than the technical details of how it will be stored and accessed. The goal of conceptual modeling is to create a clear and concise representation of the data and its relationships, which can be used to guide the development of the database. While relational data modeling is concerned with the specific technical details of the database design, conceptual modeling is focused on the overall structure and relationships of the data. Conceptual modeling is often used as a first step in the database design process, as it allows stakeholders to agree on the overall structure and relationships of the data before moving on to more detailed design work. Overall, the main difference between relational data modeling and conceptual modeling is the level of detail and focus. Relational data modeling is a more detailed and technical approach, while conceptual modeling is a higher-level approach focused on the overall structure and relationships of the data.

Relational data modeling is a collection of processes and a set of techniques that records the inventory, shape, size, contents, and rules of data elements used in the scope of a business process to build a complete representation of that scope.
Despite the name, a database is not just a collection of data. Rather it is a collection of facts, or in other words true propositions .
I will continue to represent entities using both styles, so if you prefer graphics to relational notation you will have a visual reference to make the explanations more understandable. Learning how to read relational notation is essential to data modeling. Doing so will allow you to study beyond this course and take advantage of resources that use relational notation to present their material.

Conceptual modeling is a very important phase in designing a successful database application. Generally, the term database application refers to a particular database and the associated programs that implement the database queries and updates. For example, a BANK database application that keeps track of customer accounts would include programs that implement database updates corresponding to customer deposits and withdrawals. These programs provide user-friendly graphical user interfaces (GUIs) utilizing forms and menus for the end users of the application. Hence, a major part of the database application will require the design, implementation, and testing of these application programs. Traditionally, the design and testing of application programs has been considered to be part of software engineering rather than database design. In many software design tools, the database design methodologies and software engineering methodologies are intertwined since these activities are strongly related. In this module, we follow the traditional approach of concentrating on the database structures and constraints during conceptual database design. We present the modeling concepts of the Entity-Relationship (ER) model, which is a popular high-level conceptual data model. This model and its variations are frequently used for the conceptual design of database applications, and many database design tools employ its concepts. We describe the basic data-structuring concepts and constraints of the ER model and discuss their use in the design of conceptual schemas for database applications. We also present the diagrammatic notation associated with the ER model, known as ER diagrams.