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Codd introduced the concept of normalization and what is now known as the first normal form (1NF) in 1970. [4] Codd went on to define the second normal form (2NF) and third normal form (3NF) in 1971, [5] and Codd and Raymond F. Boyce defined the Boyce–Codd normal form (BCNF) in 1974. [6]
Second normal form (2NF), in database normalization, is a normal form. A relation is in the second normal form if it fulfills the following two requirements: A relation is in the second normal form if it fulfills the following two requirements:
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).
First normal form (1NF) is a property of a relation in a relational database. A relation is in first normal form if and only if no attribute domain has relations as elements. [ 1 ] Or more informally, that no table column can have tables as values.
Only S 1, S 2, S 3 and S 4 are candidate keys (that is, minimal superkeys for that relation) because e.g. S 1 ⊂ S 5, so S 5 cannot be a candidate key. Given that 2NF prohibits partial functional dependencies of non-prime attributes (i.e., an attribute that does not occur in any candidate key ) and that 3NF prohibits transitive functional ...
Some modeling disciplines, such as the dimensional modeling approach to data warehouse design, explicitly recommend non-normalized designs, i.e. designs that in large part do not adhere to 3NF. Normalization consists of normal forms that are 1NF, 2NF, 3NF, Boyce-Codd NF (3.5NF), 4NF, 5NF and 6NF. Document databases take a different approach.
In Boolean algebra, a formula is in conjunctive normal form (CNF) or clausal normal form if it is a conjunction of one or more clauses, where a clause is a disjunction of literals; otherwise put, it is a product of sums or an AND of ORs.
These three rules are a sound and complete axiomatization of functional dependencies. This axiomatization is sometimes described as finite because the number of inference rules is finite, [ 5 ] with the caveat that the axiom and rules of inference are all schemata , meaning that the X , Y and Z range over all ground terms (attribute sets).
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