Database schema design is a critical aspect of creating a robust and efficient database system. It involves defining the structure of a database, including the tables, fields, relationships, and constraints. A well-designed schema ensures data integrity, reduces redundancy, and improves query performance.

1. Entities and Attributes:

   • Entities: Objects or things in the real world that have distinct existence (e.g., Customers, Orders).
   • Attributes: Properties or details of entities (e.g., Customer Name, Order Date).

2. Relationships:

   • One-to-One (1:1): Each entity in the relationship will have exactly one related entity.
   • One-to-Many (1:N): One entity can be related to multiple entities.
   • Many-to-Many (M:N): Multiple entities can be related to multiple entities.

3. Normalization:

   • Process of organizing data to reduce redundancy and improve data integrity.
   • Common normal forms: 1NF, 2NF, 3NF, BCNF.

4. Primary Keys:

   • Unique identifier for a record in a table.
   • Ensures each record is unique and can be referenced.

5. Foreign Keys:

   • A field (or collection of fields) in one table that uniquely identifies a row of another table.
   • Establishes a link between the data in two tables.

1. Requirement Analysis:

   • Understand the data requirements and business rules.
   • Identify the entities and relationships.

2. Conceptual Design:

   • Create an Entity-Relationship Diagram (ERD) to visually represent the entities and relationships.

3. Logical Design:

   • Convert the ERD into a logical schema.
   • Define tables, columns, primary keys, and foreign keys.

4. Normalization:

   • Apply normalization rules to ensure the schema is free of redundancy and anomalies.

5. Physical Design:

   • Optimize the schema for performance.
   • Consider indexing, partitioning, and other physical storage considerations.

• Entities: Customers, Orders, Products.
• Relationships:
  • A customer can place multiple orders (1:N).
  • An order can contain multiple products (M:N).

1. Customers Table:

   CREATE TABLE Customers (
       CustomerID INT PRIMARY KEY,
       Name VARCHAR(100),
       Email VARCHAR(100)
   );
   

2. Orders Table:

   CREATE TABLE Orders (
       OrderID INT PRIMARY KEY,
       OrderDate DATE,
       CustomerID INT,
       FOREIGN KEY (CustomerID) REFERENCES Customers(CustomerID)
   );
   

3. Products Table:

   CREATE TABLE Products (
       ProductID INT PRIMARY KEY,
       ProductName VARCHAR(100),
       Price DECIMAL(10, 2)
   );
   

4. OrderDetails Table:

   CREATE TABLE OrderDetails (
       OrderID INT,
       ProductID INT,
       Quantity INT,
       PRIMARY KEY (OrderID, ProductID),
       FOREIGN KEY (OrderID) REFERENCES Orders(OrderID),
       FOREIGN KEY (ProductID) REFERENCES Products(ProductID)
   );
   

• Ensure tables are in 3NF:
  • 1NF: Each table has a primary key, and each column contains atomic values.
  • 2NF: All non-key attributes are fully functional dependent on the primary key.
  • 3NF: No transitive dependencies.

• Indexing: Create indexes on frequently queried columns to improve performance.

  CREATE INDEX idx_customer_email ON Customers(Email);
  CREATE INDEX idx_order_date ON Orders(OrderDate);
  

• Partitioning: Consider partitioning large tables to improve query performance and manageability.

Requirements:

• Entities: Books, Members, Loans.
• Relationships:
  • A member can borrow multiple books (1:N).
  • A book can be borrowed by multiple members over time (M:N).

Tasks:

1. Identify the entities and their attributes.
2. Create an ERD.
3. Define the tables and their relationships.
4. Normalize the schema to 3NF.
5. Write SQL statements to create the tables.

1. Entities and Attributes:

   • Books: BookID, Title, Author, ISBN.
   • Members: MemberID, Name, Email.
   • Loans: LoanID, BookID, MemberID, LoanDate, ReturnDate.

2. ERD:

   Books (BookID, Title, Author, ISBN)
   Members (MemberID, Name, Email)
   Loans (LoanID, BookID, MemberID, LoanDate, ReturnDate)
   

3. Tables:

   CREATE TABLE Books (
       BookID INT PRIMARY KEY,
       Title VARCHAR(100),
       Author VARCHAR(100),
       ISBN VARCHAR(20)
   );
   
   CREATE TABLE Members (
       MemberID INT PRIMARY KEY,
       Name VARCHAR(100),
       Email VARCHAR(100)
   );
   
   CREATE TABLE Loans (
       LoanID INT PRIMARY KEY,
       BookID INT,
       MemberID INT,
       LoanDate DATE,
       ReturnDate DATE,
       FOREIGN KEY (BookID) REFERENCES Books(BookID),
       FOREIGN KEY (MemberID) REFERENCES Members(MemberID)
   );
   

4. Normalization:

   • Ensure all tables are in 3NF.

5. Indexing:

   CREATE INDEX idx_member_email ON Members(Email);
   CREATE INDEX idx_loan_date ON Loans(LoanDate);
   

Database schema design is a foundational skill for data architects. It involves understanding the data requirements, defining entities and relationships, and applying normalization principles to ensure data integrity and performance. By following a structured approach, you can create efficient and scalable database schemas that meet the needs of your organization.