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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 .
In statistics and applications of statistics, normalization can have a range of meanings. [1] In the simplest cases, normalization of ratings means adjusting values measured on different scales to a notionally common scale, often prior to averaging.
Feature standardization makes the values of each feature in the data have zero-mean (when subtracting the mean in the numerator) and unit-variance. This method is widely used for normalization in many machine learning algorithms (e.g., support vector machines , logistic regression , and artificial neural networks ).
If such a data model is represented as relations, a repeating group would be an attribute where the value is itself a relation. First normal form eliminates nested relations by turning them into separate "top-level" relations associated with the parent row through foreign keys rather than through direct containment.
The sixth normal form is currently as of 2009 being used in some data warehouses where the benefits outweigh the drawbacks, [9] for example using anchor modeling.Although using 6NF leads to an explosion of tables, modern databases can prune the tables from select queries (using a process called 'table elimination' - so that a query can be solved without even reading some of the tables that the ...
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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:
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