Normalization is a process in database design that reduces data redundancy and eliminates undesirable characteristics like Insertion, Update and Deletion Anomalies. Normalization rules are divided into several normal forms; the first three of which are the most widely used.

The table you provided is currently in an unnormalized form (0NF) because it contains repeating groups (Book and DueDate).

Let's normalize this table step by step:

1. First Normal Form (1NF):
- Each table cell should contain a single value.
- Each record needs to be unique.

To achieve this, we can break down the table into two tables:

Table 1: MemberLoan
LoanID | MemberName | MemberID
--- | --- | ---
9001 | Sarah Adams | 101
9002 | Mark Taylor | 102
9003 | Jessica Lee | 103

Table 2: LoanDetails
LoanID | Book | DueDate
--- | --- | ---
9001 | Introduction to SQL | 2024-08-10
9001 | Python Programming | 2024-08-15
9002 | Data Structures | 2024-09-05
9002 | Algorithms | 2024-09-10
9002 | SQL Fundamentals | 2024-09-15

2. Second Normal Form (2NF):
- It should be in 1NF.
- All non-key attributes should be fully functional dependent on the primary key.

Our tables are already in 2NF because all non-key attributes (MemberName in the MemberLoan table and Book, DueDate in the LoanDetails table) are dependent on the primary key (LoanID).

3. Third Normal Form (3NF):
- It should be in 2NF.
- There should be no transitive functional dependency.

To achieve this, we can further break down the MemberLoan table into two tables to remove the transitive functional dependency (MemberName is dependent on MemberID):

Table 1: Member
MemberID | MemberName
--- | ---
101 | Sarah Adams
102 | Mark Taylor
103 | Jessica Lee

Table 2: Loan
LoanID | MemberID
--- | ---
9001 | 101
9002 | 102
9003 | 103

Table 3: LoanDetails remains the same.

Now, all tables are in Third Normal Form (3NF).

Question

Normalization is a process in database design that reduces data redundancy and eliminates undesirable characteristics like Insertion, Update and Deletion Anomalies. Normalization rules are divided into several normal forms; the first three of which are the most widely used.

The table you provided is currently in an unnormalized form (0NF) because it contains repeating groups (Book and DueDate).

Let's normalize this table step by step:

1. First Normal Form (1NF):
   - Each table cell should contain a single value.
   - Each record needs to be unique.

To achieve this, we can break down the table into two tables:

Table 1: MemberLoan
LoanID | MemberName | MemberID
--- | --- | ---
9001 | Sarah Adams | 101
9002 | Mark Taylor | 102
9003 | Jessica Lee | 103

Table 2: LoanDetails
LoanID | Book | DueDate
--- | --- | ---
9001 | Introduction to SQL | 2024-08-10
9001 | Python Programming | 2024-08-15
9002 | Data Structures | 2024-09-05
9002 | Algorithms | 2024-09-10
9002 | SQL Fundamentals | 2024-09-15

2. Second Normal Form (2NF):
   - It should be in 1NF.
   - All non-key attributes should be fully functional dependent on the primary key.

Our tables are already in 2NF because all non-key attributes (MemberName in the MemberLoan table and Book, DueDate in the LoanDetails table) are dependent on the primary key (LoanID).

3. Third Normal Form (3NF):
   - It should be in 2NF.
   - There should be no transitive functional dependency.

To achieve this, we can further break down the MemberLoan table into two tables to remove the transitive functional dependency (MemberName is dependent on MemberID):

Table 1: Member
MemberID | MemberName
--- | ---
101 | Sarah Adams
102 | Mark Taylor
103 | Jessica Lee

Table 2: Loan
LoanID | MemberID
--- | ---
9001 | 101
9002 | 102
9003 | 103

Table 3: LoanDetails remains the same.

Now, all tables are in Third Normal Form (3NF).

Knowee AI · Accepted Answer