Logical Data Model Design

The logical data model design defines the structure of data and what relationship exists among those data. The following are the major components of the logical design:

1. Data Models: Data modeling is a visual modeling technique used to get a high-level overview of our database. Data models help us understand the needs and requirements of our database by defining the design of our database through diagrammatic representation. Ex: model, Network model, Relational Model, object-oriented data model.

2. Entity: Entities are objects in the real world, which can have certain properties & these properties are referred to as attributes of that particular entity. There are 2 types of entities: Strong and weak entity, weak entity do not have a key attribute to identify them, their existence solely depends on one 1-specific strong entity & also have full participation in a relationship whereas strong entity does have a key attribute to uniquely identify them.

Weak entity example: Loan -> Loan will be given to a customer (which is optional) & the load will be identified by the customer_id to whom the lone is granted.

3. Relationships: How data is logically related to each other defines the relationship of that data with other entities. In simple words, the association of one entity with another is defined here.

A relationship can be further categorized into – unary, binary, and ternary relationships.

• Unary: In this, the associating entity & the associated entity both are the same. Ex: Employee Manages themselves, and students are also given the post of monitor hence here the student themselves is a monitor.
• Binary: This is a very common relationship that you will come across while designing a database.
  Ex: Student is enrolled in courses, Employee is managed by different managers, One student can be taught by many professors.
• Ternary: In this, we have 3 entities involved in a single relationship. Ex: an employee works on a project for a client. Note that, here we have 3 entities: Employee, Project & Client.

4. Attributes: Attributes are nothing but properties of a specific entity that define its behavior. For example, an employee can have unique_id, name, age, date of birth (DOB), salary, department, Manager, project id, etc.

5. Normalization: After all the entities are put in place and the relationship among data is defined, we need to look for loopholes or possible ambiguities that may arise as a result of CRUD operations. To prevent various Anomalies such as INSERTION, UPDATION, and DELETION Anomalies.

Data Normalization is a basic procedure defined for databases to eliminate such anomalies & prevent redundancy.

An Example of Logical Design

Database Design can be defined as a set of procedures or collection of tasks involving various steps taken to implement a database. Following are some critical points to keep in mind to achieve a good database design:

1. Data consistency and integrity must be maintained.
2. Low Redundancy
3. Faster searching through indices
4. Security measures should be taken by enforcing various integrity constraints.
5. Data should be stored in fragmented bits of information in the most atomic format possible.

However, depending on specific requirements above criteria might change. But these are the most common things that ensure a good database design.