SQL Normalization: FAQs to Master Database Design and Normal Forms

1.What is Normalization and why is it essential in databases?
Normalization is a systematic process in the database design that minimizes data redundancy and enhances data integrity by organizing data into multiple related tables. It makes sure that data dependencies are logical, eliminating duplicate storage. The end goal is to improve data storage and retrieval efficiency.
For example, consider a table storing employee and department details. Without normalization, all department information must be repeated for every employee in the same department. Normalization breaks this data into two tables: one for employees and another for departments. The department information is stored only once, and a relationship is established using a foreign key.
Normalization prevents anomalies such as:
•Insert Anomaly: Adding a new department without an employee is impossible.
•Update Anomaly: Upgrading department information necessitates an update in several rows.
•Delete Anomaly: Erasing an employee could delete important department data.

2.Which of the following are the various normal forms used in database normalization?
Database normalization is divided into a number of stages, known as normal forms that target different types of redundancy and dependency problems:
1.First Normal Form (1NF): Guarantees that all columns are atomic-that contain indivisible values-and removes repeating groups.
2.2NF : Guarantees that every non-key attribute depends on the entire primary key, thus addressing partial dependency.
3.3NF : Eliminates transitive dependencies where non-key attributes depend on other non-key attributes.
4.Boyce-Codd Normal Form (BCNF): Guarantees that every determinant or a column that determines another column is a candidate key.
5.Higer forms like 4NF and 5NF deal with multi-valued dependencies and join dependencies respectively. Each normal form increments the previous one, step by step towards redundancy reduction and data integrity enhancing.

3.What is First Normal Form (1NF) Is its definition?
A relation or table is said to be in First Normal Form (1NF), that is:
1. All column holds atomic values (no lists of multicolumns).
2.A table has a distinct identified primary key.
Use below structure for a sample representation of a student table:
| StudentID | Name | Subjects |
|-----------|-------|------------------|
| 1 | Alice | Math, Physics |
| 2 | Bob | Chemistry, Math |
The column Subjects is in violation of 1NF because it holds multiple values. To normalize it, split the data into rows:
| StudentID | Name | Subject |
|-----------|-------|------------------|
| 1 | Alice | Math |
| 1 | Alice | Physics |
| 2 | Bob | Chemistry |
| 2 | Bob | Math |
This will guarantee atomicity and simplify the query and make it more efficient.

4.What is partial dependency and how does Second Normal Form (2NF) eliminate it?
Partial dependency is a situation where a non-key attribute depends on only a part of a composite primary key rather than the whole key. This violates the principle of full functional dependency.
Suppose a table has the following attributes: StudentID, CourseID, and Instructor:
| StudentID | CourseID | Instructor |
|-----------|----------|------------|
| 1 | 101 | Dr. Smith |
| 2 | 102 | Dr. Brown |
In this case, Instructor is dependent only on CourseID, not the entire composite key (StudentID, CourseID).
To overcome this, the table is split into two
1.Students-Courses Table: Contains StudentID and CourseID.
2.Courses-Instructor Table: Has CourseID and Instructor.
This removes partial dependencies and hence is in 2NF.

5.What is a transitive dependency and how does Third Normal Form (3NF) address it?
A transitive dependency occurs when a non-key attribute depends on another non-key attribute that, in turn, depends on the primary key.
For instance, in an Employees table:
| EmployeeID | Department | Manager |
|------------|------------|----------|
| 1 | HR | Alice |
| 2 | IT | Bob |
Here, Manager depends on Department, which depends on EmployeeID. This is a transitive dependency.
To achieve 3NF, break the table into two:
1. Employees Table: It has EmployeeID and Department.
2. Departments Table: It has Department and Manager.
This removes transitive dependencies and provides better data structuring.

Guide to SQL normalization, explaining normal forms and their role in efficient database design

6.What is Boyce-Codd Normal Form (BCNF) and why is it more strict than 3NF?
BCNF is a more strict form of 3NF where every determinant is a candidate key.
BCNF solves the problems that 3NF may not solve in specific scenarios.
For instance, consider this table:
| CourseID | Instructor | Room |
|----------|------------|----------|
| 101 | Dr. Smith | Room A |
| 102 | Dr. Brown | Room B |
In this case, Instructor depends on Room, but Instructor is not a candidate key.
For normalization to BCNF, take two different tables:
1. Courses-Instructors Table: It has CourseID and Instructor.
2. Instructors-Rooms Table: It has Instructor and Room.
BCNF guarantees that every determinant is a key.

7.How does normalization help in the reduction of database anomalies?
Normalization solves the three main types of anomalies:
1.Insert Anomaly: Prevents inability to insert data because some information is missing.
2.Update Anomaly: Ensures consistency of updates for related data.
3.Delete Anomaly: Prevents unintentional loss of data while deleting records.
For instance, storing employee and department details in one table can cause all department data to be lost if the last employee of a department is deleted. Normalization separates this data into related tables, preserving department details.

8.How does normalization improve query performance and maintainability?
By reducing redundancy and organizing data logically, normalization simplifies queries and ensures data integrity.
For example,
retrieving department details no longer requires scanning duplicate data.
However, overnormalization can lead to a higher number of joins which may deteriorate query performance by a small amount. This trade-off can be controlled by index or denormalizing certain read-heavy applications.

9.What is the problem with normalization?
Normalization does improve consistency and reduces data redundancy, but it has following problems:
•More complexity for designing and maintaining multiple tables related to each other
•Read operations are relatively slower because of multiple joins that have to be performed.
•Denormalization could be necessary in read-heavy environments for performance.
Balancing normalization and denormalization depends on the requirements of an application.

10.How do you balance normalization and denormalization in database design?
Balancing normalization and denormalization depends on understanding trade-offs. For instance, normalization reduces redundancy while denormalization makes performance better since it puts together related tables.
Consider an e-commerce database:
•Normalize product and order details to preserve data integrity.
•Denormalize frequently accessed data like product names and prices in reports to reduce query complexity.
Use indexing, caching, and database optimization techniques in addition to normalization to yield optimum performance.

Previous Topic==> Dynamic SQL FAQ. || Other Topic==> Banking Account Management Case Study in SQL

Top SQL Interview Questions Employee Salary Management FAQ!. Top 25 PL/SQL Interview Questions

Joins With Group by Having Equi Join Joins with Subqueries Self Join Outer Join