Normalization

Normalization is simply breaking down tables to achieve efficiency in retrieving and maintaining data. The most common reason is to avoid redundancy which means less storage is required. Normalization also helps in avoiding data anomalies.

Data anomalies can add to problems with large consumption of storage space, slow execution times, etc. There are 3 types of data anomalies

update anomaly Failing to update all the occurrences of a certain attribute because of the repeating values problem.
insertion anomaly You are prevented from inserting certain data because you are missing other pieces of information.
deletion anomaly you could end up losing data because you are trying to remove some duplicate attributes from a customers data

There are 5 levels of simplification (forms)

1NF

There are no duplicate rows in the table
Each cell is singled-valued (no repeating groups or arrays)
Entries in a column are the same kind

2NF
 Is that it is already in 1NF and it has no partial dependencies
3NF
 is that it is already in 2NF and every non-key attribute is fully and directly dependent on the primary key (eliminate the columns that aren't dependent on the key.
BCNF
 if every determinant is a primary key.
4NF
 if it is in BCNF and contains no nontrivial multi valued dependencies
5NF
 is defined as a relation that has no join dependency