The logical data model is characterized by its abstraction and focus on business requirements rather than technical implementation details. It serves as a blueprint before designing a physical database. Here are its key features:
Core Features of a Logical Data Model
The logical data model outlines the structure of data and their relationships, focusing on what data is needed rather than how it will be stored. This abstraction allows stakeholders to understand the data needs without the clutter of database specifics.
Independence from Specific Database and Data Storage Structures
- Logical data models are not tied to any particular database management system (DBMS) or storage mechanism. This flexibility enables users to change the underlying database technology without affecting the logical model.
- The model focuses on representing the information requirements of the business and not the technical specifics of any database system.
- For instance, the logical model defines that a "Customer" entity has attributes like "Name", "Address", and "Email", without specifying if the data will be stored in a SQL table, a NoSQL document, or some other storage system.
Specification of Entities and Attributes
- The logical model identifies specific entities (like Customer, Order, Product) and their corresponding attributes (like CustomerID, OrderDate, ProductName).
- These entities and attributes represent the core data elements used by the business processes.
- For example, in an e-commerce application, "Order" would be an entity with attributes such as "OrderID", "OrderDate", "CustomerID", and "TotalPrice".
Definition of Business Rules and Relationships
- A crucial part of the logical data model is to capture business rules that govern the data.
- Examples of rules include: a customer can have multiple orders, an order can belong to only one customer.
- It also defines relationships between entities.
- These relationships specify how entities are connected, such as one-to-many, many-to-many, and one-to-one.
- These relationships reflect real-world business connections, ensuring data integrity and enabling better decision-making.
- For instance, a logical model specifies that "Customers" are related to "Orders" with a one-to-many relationship, meaning one customer can have multiple orders, but each order belongs to only one customer.
Practical Insights
| Feature | Description | Example |
|---|---|---|
| Database Independence | Design is not tied to a specific system. | Can be implemented using different databases (e.g., MySQL, MongoDB) without changes in design. |
| Specific Entities & Attributes | Clearly defines the data required for an application. | Includes Customer, Order and attributes such as CustomerID, OrderDate, and Product Name. |
| Business Rules & Relationships | Outlines how entities relate to each other based on business processes. | A customer can have multiple orders (one-to-many relation). |
Conclusion
The logical data model, with its focus on business needs, forms a strong foundation for the subsequent physical database design. This model is essential for aligning data storage with business objectives, and its features ensure that data is well-defined, organized, and reflects the real-world rules and relationships of the business environment.
