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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. Database normalization is the process of representing a database in terms of relations in standard normal forms, where first normal is a minimal requirement.
A table (called the referencing table) can refer to a column (or a group of columns) in another table (the referenced table) by using a foreign key. The referenced column(s) in the referenced table must be under a unique constraint, such as a primary key. Also, self-references are possible (not fully implemented in MS SQL Server though [5]).
"Don't repeat yourself" (DRY), also known as "duplication is evil", is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.
PostgreSQL (/ ˌ p oʊ s t ɡ r ɛ s k j u ˈ ɛ l / POHST-gres-kew-EL) [11] [12] also known as Postgres, is a free and open-source relational database management system (RDBMS) emphasizing extensibility and SQL compliance. PostgreSQL features transactions with atomicity, consistency, isolation, durability properties, automatically updatable ...
A database relation (e.g. a database table) is said to meet third normal form standards if all the attributes (e.g. database columns) are functionally dependent on solely a key, except the case of functional dependency whose right hand side is a prime attribute (an attribute which is strictly included into some key).
In SQL, the unique keys have a UNIQUE constraint assigned to them in order to prevent duplicates (a duplicate entry is not valid in a unique column). Alternate keys may be used like the primary key when doing a single-table select or when filtering in a where clause, but are not typically used to join multiple tables.
In coding theory, the repetition code is one of the most basic linear error-correcting codes. In order to transmit a message over a noisy channel that may corrupt the transmission in a few places, the idea of the repetition code is to just repeat the message several times. The hope is that the channel corrupts only a minority of these repetitions.
The conclusion made by the researchers was that repeating a statement makes it more likely to appear factual. [ 1 ] [ 2 ] In 1989, Hal R. Arkes, Catherine Hackett, and Larry Boehm replicated the original study, with similar results showing that exposure to false information changes the perceived truthfulness and plausibility of that information.