Normalization is a process used in database design to organize data in a way that reduces redundancy and improves data integrity. There are several levels, or “normal forms,” of normalization, each building on the previous one. The most common levels include the First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), and Boyce-Codd Normal Form (BCNF). Each level has specific requirements that must be fulfilled to classify a database schema into that form.
The First Normal Form (1NF) requires that all the values in a table are atomic, meaning that each column must contain indivisible values. Additionally, each entry in a column must be of the same type, and every table should have a primary key that uniquely identifies each record. For example, if you had a 'Students' table with a 'Courses' column, which lists multiple courses for each student, you would need to split that column into separate entries so that each course is listed in its row, ensuring that the table adheres to 1NF.
Advancing to the Second Normal Form (2NF), the table must already be in 1NF, and all non-key attributes should be fully functionally dependent on the primary key. This means that if any non-key attribute depends on only part of a composite primary key, you need to separate those into another table. For instance, if you have a 'Course Registrations' table with 'StudentID' and 'CourseID' as a composite key and a 'CourseName' column, you would move 'CourseName' into a separate 'Courses' table to avoid partial dependency, thus achieving 2NF. The Third Normal Form (3NF) mandates that all attributes must be directly dependent on the primary key, not on other non-key attributes. If you encounter a scenario where one non-key attribute is dependent on another non-key attribute, you must also separate that into its table to ensure compliance with 3NF. After achieving 3NF, databases can advance to Boyce-Codd Normal Form (BCNF) if they meet a stricter criterion where every determinant must be a candidate key. Normalization ensures data accuracy and streamlines database structures, ultimately making it easier to maintain and query.