Data modelling is the process of creating a visual representation of a system’s data and the relationships between different data elements. This helps in organizing and structuring the data so it can be efficiently managed and utilized.
Data modelling ensures that data is logically structured and organized, making it easier to store, retrieve, and manipulate in a database.
Workflow of Data Modeling
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Conceptual Model:
- Focuses on high-level business requirements.
- Defines important data entities and their relationships.
- Tools: ER Diagrams, ER Studio, DbSchema.
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Logical Model:
- Details the attributes of each data entity.
- Specifies relationships without depending on a specific database management system.
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Physical Model:
- Implements the logical model in a specific database system.
- Includes table structures, columns, data types, and constraints.
Types of Modeling
- Relational: Organizes data into tables.
- Object-Oriented: Focuses on objects and their state changes, e.g., robots in a car factory.
- Entity: Uses ER Diagrams to represent data entities and relationships.
- Network: An extension of hierarchical models.
- Hierarchical: Organizes data in a tree-like structure.
Example: Online Bookstore
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Conceptual Model:
- Entities: Customer, Order, Book
- Relationships: Customers place Orders, Orders include Books
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Logical Model:
- Customer: CustomerID, Name, Email
- Order: OrderID, OrderDate, CustomerID
- Book: BookID, Title, Author
- Order-Book Relationship: OrderID, BookID
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Physical Model (for a SQL database):