In data management and database analysis, a data domain refers to all the unique values which a data element may contain. The rule for determining the domain boundary may be as simple as a data type with an enumerated list of values.
For example, a database table that has information about people, with one record per person, might have a "gender" column. This gender column might be declared as a string data type, and allowed to have one of two known code values: "M" for male, "F" for female—and NULL for records where gender is unknown or not applicable (or arguably "U" for unknown as a sentinel value). The data domain for the gender column is: "M", "F".
In a normalized data model, the reference domain is typically specified in a reference table. Following the previous example, a Gender reference table would have exactly two records, one per allowed value—excluding NULL. Reference tables are formally related to other tables in a database by the use of foreign keys.
Less simple domain boundary rules, if database-enforced, may be implemented through a check constraint or, in more complex cases, in a database trigger. For example, a column requiring positive numeric values may have a check constraint declaring that the values must be greater than zero.
This definition combines the concepts of domain as an area over which control is exercised and the mathematical idea of a set of values of an independent variable for which a function is defined. See: domain (mathematics).
Famous quotes containing the words domain and/or data:
“In the domain of art there is no light without heat.”
—Victor Hugo (1802–1885)
“To write it, it took three months; to conceive it three minutes; to collect the data in it—all my life.”
—F. Scott Fitzgerald (1896–1940)