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Denormalization is a strategy used on a previously-normalized database to increase performance. In computing, denormalization is the process of trying to improve the read performance of a database, at the expense of losing some write performance, by adding redundant copies of data or by grouping data.
In computing, the star schema or star model is the simplest style of data mart schema and is the approach most widely used to develop data warehouses and dimensional data marts. [1] The star schema consists of one or more fact tables referencing any number of dimension tables .
Snowflake schema used by example query. The example schema shown to the right is a snowflaked version of the star schema example provided in the star schema article. The following example query is the snowflake schema equivalent of the star schema example code which returns the total number of television units sold by brand and by country for 1997.
Example of a star schema; the central table is the fact table. In data warehousing, a fact table consists of the measurements, metrics or facts of a business process. It is located at the center of a star schema or a snowflake schema surrounded by dimension tables. Where multiple fact tables are used, these are arranged as a fact constellation ...
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 ...
A relational schema R is in Boyce–Codd normal form if and only if for every one of its functional dependencies X → Y, at least one of the following conditions hold: [5] X → Y is a trivial functional dependency (Y ⊆ X), X is a superkey for schema R. [5]
Fourth normal form (4NF) is a normal form used in database normalization.Introduced by Ronald Fagin in 1977, 4NF is the next level of normalization after Boyce–Codd normal form (BCNF).
The reverse star schema is a schema optimized for fast retrieval of large quantities of descriptive data. The design was derived from a warehouse star schema , [ 1 ] and its adaptation for descriptive data required that certain key characteristics of the classic star schema be "reversed".