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This assignment is based on the database environment proposed in the Week One Individual Assignment. Perform a logical design on the proposed database environment without going through the full normalization process. Include the identification of all entities and attributes associated with the environment.
Use a 2-page memo to document your logical design including the process you went through. Discuss the process you went through to select the appropriate data types, primary and foreign keys, and other constraints that are necessary to maintain the integrity of the database. Create a detailed ERD using the data specifications from the logical design. Use Microsoft® Visio® or another tool to create this diagram. One alternative is to create a free account to access LucidChart, a Visio compatible tool.
Paper For Above instruction
Performing a logical database design is a critical step in developing a robust and efficient information system. Based on the proposed environment from the Week One assignment, the first step involved identifying the key entities that represent core objects within the system. These entities form the foundation of the database schema, and their attributes further describe each entity's characteristics.
The primary entities identified in the environment include Customers, Orders, Products, and Employees. Each of these entities possesses specific attributes essential for the operation and reporting within the system. For Customers, attributes include CustomerID, Name, Address, Phone, and Email. Orders include OrderID, OrderDate, CustomerID, and EmployeeID—serving as a link between customers and employees managing the orders. Products encompass ProductID, Name, Description, Price, and StockQuantity. Employees, who manage the orders and customer interactions, include EmployeeID, Name, Position, and Department.
In designing the logical schema, careful consideration was given to the selection of appropriate data types. For instance, numeric identifiers such as CustomerID, OrderID, ProductID, and EmployeeID are best represented by integer data types, ensuring quick indexing and retrieval. Attributes like Name, Address, and Description are textual, thus designated as VARCHAR with suitable length constraints to balance storage efficiency and data completeness. Date-related data, such as OrderDate, are best stored using date or datetime data types, facilitating date calculations and reporting.
Keys play a pivotal role in maintaining database integrity. The primary keys—CustomerID, OrderID, ProductID, and EmployeeID—uniquely identify each record within their respective entities. Foreign keys establish relationships between entities; for example, CustomerID in Orders references the primary key in Customers, while EmployeeID links to Employees. These foreign key constraints enforce referential integrity, preventing orphaned records or inconsistent data.
Besides keys, other constraints such as NOT NULL ensure essential fields are populated, while UNIQUE constraints prevent duplicate records where necessary (e.g., Email or Product Name if required for business rules). Implementing check constraints further ensures data validity, such as verifying that Price or StockQuantity are non-negative numbers.
The ERD visually represents these entities and relationships, showcasing primary keys, foreign keys, and attributes. Using tools like Microsoft Visio or LucidChart, I created an ERD where entities are depicted as rectangles, with primary keys underlined. Relationships are visualized with connecting lines, annotated to show the nature of the relationship (one-to-many, many-to-many). For example, one Customer can place many Orders, but each Order is placed by one Customer, representing a one-to-many relationship.
This logical design serves as a blueprint for subsequent physical implementation. It ensures data consistency, supports efficient query execution, and maintains referential integrity across the database. The process involved thoughtful analysis of the system’s requirements, appropriate data type selection, and careful structuring of relationships to support the organization's operational needs.
References
- Codd, E. F. (1970). A relational model for large shared data banks. Communications of the ACM, 13(6), 377-387.