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The third normal form (3NF) is a normal form used in database normalization. 3NF was originally defined by E. F. Codd in 1971. [2] Codd's definition states that a table is in 3NF if and only if both of the following conditions hold: The relation R (table) is in second normal form (2NF).
Database normalization is the process of structuring a relational database accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .
Boyce–Codd normal form (BCNF or 3.5NF) is a normal form used in database normalization. It is a slightly stricter version of the third normal form (3NF). By using BCNF, a database will remove all redundancies based on functional dependencies .
There is no B → A relationship. B → C direct dependency relationship exists. Then the functional dependency A → C is a transitive dependency (which follows the axiom of transitivity). In database normalization, one of the important features of third normal form is that it excludes certain types of transitive dependencies.
Generally, the third normal form is considered to be a "good" standard for a relational database. [citation needed] Normalization aims to free the database from update, insertion and deletion anomalies. It also ensures that when a new value is introduced into the relation, it has minimal effect on the database, and thus minimal effect on the ...
For example, all the relations are in third normal form and any relations with join dependencies and multi-valued dependencies are handled appropriately. Examples of denormalization techniques include: "Storing" the count of the "many" elements in a one-to-many relationship as an attribute of the "one" relation
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Elementary key normal form (EKNF) is a subtle enhancement on third normal form, thus EKNF tables are in 3NF by definition. This happens when there is more than one unique compound key and they overlap. Such cases can cause redundant information in the overlapping column(s).