What are the levels of data normalization?

The levels of data normalization are First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), Boyce-Codd Normal Form (BCNF), Fourth Normal Form (4NF), and Fifth Normal Form (5NF).

Data normalization is a process in database design that organises data to minimise redundancy and dependency. This process involves dividing a database into two or more tables and defining relationships between the tables. The main aim of normalization is to add, delete, and modify data without causing data anomalies.

The First Normal Form (1NF) sets the fundamental rules for an organised database: eliminate duplicative columns from the same table, create separate tables for each group of related data and identify each set of related data with a primary key.

The Second Normal Form (2NF) further addresses the concept of removing duplicative data: meet all the rules of the first normal form and remove subsets of data that apply to multiple rows of a table and place them in separate tables. Create relationships between these new tables and their predecessors through the use of foreign keys.

The Third Normal Form (3NF) goes one large step further: meet all the rules of the second normal form and remove columns that are not dependent upon the primary key.

The Boyce-Codd Normal Form (BCNF) is a slightly stronger version of the 3NF. A table is in BCNF if, and only if, for every one of its non-trivial functional dependencies X → Y, X is a superkey.

The Fourth Normal Form (4NF) has one additional requirement: meet all the rules of the third normal form and a relation is in 4NF if it has no multi-valued dependencies.

Finally, the Fifth Normal Form (5NF), also known as Project-Join Normal Form (PJNF), deals with cases where information can be reconstructed from smaller pieces of information that can be maintained with less redundancy. A table is in 5NF if and only if every join dependency in it is implied by the candidate keys.

Each level of normalization addresses a specific potential issue that could arise in a relational database. It's important to note that a higher level of normalization does not always mean a better database design. Depending on the specific requirements, a less normalized database may be more efficient.