Editing Data integrity (section)

== Databases ==
Data integrity contains guidelines for [[data retention]], specifying or guaranteeing the length of time data can be retained in a particular database (typically a [[relational database]]). To achieve data integrity, these rules are consistently and routinely applied to all data entering the system, and any relaxation of enforcement could cause errors in the data. Implementing checks on the data as close as possible to the source of input (such as human data entry), causes less erroneous data to enter the system. Strict enforcement of data integrity rules results in lower error rates, and time saved troubleshooting and tracing erroneous data and the errors it causes to algorithms.

Data integrity also includes rules defining the relations a piece of data can have to other pieces of data, such as a ''Customer'' record being allowed to link to purchased ''Products'', but not to unrelated data such as ''Corporate Assets''. Data integrity often includes checks and correction for invalid data, based on a fixed [[database schema|schema]] or a predefined set of rules. An example being textual data entered where a date-time value is required. Rules for data derivation are also applicable, specifying how a data value is derived based on algorithm, contributors and conditions. It also specifies the conditions on how the data value could be re-derived.

=== Types of integrity constraints ===
Data integrity is normally enforced in a [[database system]] by a series of integrity constraints or rules. Three types of integrity constraints are an inherent part of the [[Relational model|relational data model]]: entity integrity, referential integrity and domain integrity.

* ''[[Entity integrity]]'' concerns the concept of a [[primary key]]. Entity integrity is an integrity rule which states that every table must have a primary key and that the column or columns chosen to be the primary key should be unique and not null.
* ''[[Referential integrity]]'' concerns the concept of a [[foreign key]]. The referential integrity rule states that any foreign-key value can only be in one of two states. The usual state of affairs is that the foreign-key value refers to a primary key value of some table in the database. Occasionally, and this will depend on the rules of the data owner, a foreign-key value can be [[Null (SQL)|null]]. In this case, we are explicitly saying that either there is no relationship between the objects represented in the database or that this relationship is unknown.
* ''Domain integrity'' specifies that all columns in a relational database must be declared upon a defined domain. The primary unit of data in the relational data model is the data item. Such data items are said to be non-decomposable or atomic. A domain is a set of values of the same type. Domains are therefore pools of values from which actual values appearing in the columns of a table are drawn.
* ''User-defined integrity'' refers to a set of rules specified by a user, which do not belong to the entity, domain and referential integrity categories.

If a database supports these features, it is the responsibility of the database to ensure data integrity as well as the [[consistency model]] for the data storage and retrieval. If a database does not support these features, it is the responsibility of the applications to ensure data integrity while the database supports the [[consistency model]] for the data storage and retrieval.

Having a single, well-controlled, and well-defined data-integrity system increases:

* stability (one centralized system performs all data integrity operations)
* performance (all data integrity operations are performed in the same tier as the consistency model)
* re-usability (all applications benefit from a single centralized data integrity system)
* maintainability (one centralized system for all data integrity administration).

Modern [[database]]s support these features (see [[Comparison of relational database management systems]]), and it has become the de facto responsibility of the database to ensure data integrity. Companies, and indeed many database systems, offer products and services to migrate legacy systems to modern databases.

=== Examples ===
An example of a data-integrity mechanism is the parent-and-child relationship of related records. If a parent record owns one or more related child records all of the referential integrity processes are handled by the database itself, which automatically ensures the accuracy and integrity of the data so that no child record can exist without a parent (also called being orphaned) and that no parent loses their child records. It also ensures that no parent record can be deleted while the parent record owns any child records. All of this is handled at the database level and does not require coding integrity checks into each application.