In the Webster dictionary, the word "integrity" is defined as "firm adherence to a code, a set of moral values, honesty and incorruptibility".

In general computer science, Data Integrity is the aspect of wholeness of completeness of data during such operations such as transfer, storage and retrieval. It also refers to the preservation of data as it undergoes several processes of manipulation. Of course, Data Integrity also refers to its faithfulness of its source whenever it travels.

Whenever a database developer or database designer lays out the database design, one of the important things considered is the structure of the data. This will ensure Data Integrity but allowing any data user to encode the right data only according to the defined structural specifications.

For instance, if a product to be entered for the Product_ID entity has a value of 25 in the "Products" table, the database will never allow any other product to have the same value within the same table.

In another related instance, if there is a column named Product_Rating within the "Products" table that is intended to accept only values which range from 1 to 10, the database will never accept any other values which are not within the range of 1 to 10.

Another specification in the database which ensures Data Integrity Value is the definition of data types. A data type is an attribute which gives a specification to the type of data that can be allowed for storage in a database table column, parameter or variable.

For example, some of the data types include Boolean, character, integer, binary, strings and many more. It is often a feature in some database implementation that users can define or create their own data types basing on the data types supplied by the database system. Data types can be used in enforcing Data Integrity Value by making the input data conform to the type specified for the object.

Table column nullability specifies whether the database column value is either unknown or undefined. It does not mean that the column has blank, zero or zero length character string. A null value in a column means that no data has been entered into it.

Another way to ensure Data Integrity Value in a database is to have default definitions. It means that each table column should contain a value even if the value is null. In some situations, it possible that when a row is inserted into a table, the value for a column is not known or the value does not yet exist.

Data Integrity Value can also be maintained beyond the database design. This can be achieved by the ethical use of data in a database or Data Warehouse. Some of the ethics of data usage which can help ensure Data Integrity Value include:

• Not using information to support activities of other individuals or groups which seek to gain profit in a negative way. This can be done by not disclosing information without proper authorization.

• Not engaging in any form of database voyeurism

• Not circumventing the nature or level of data access which are granted to others

• Not sharing one’s username and password to others who would potentially use the database data for purpose other than the intended.

By maintaining Data Integrity Values, the organization may gain tremendous benefits such as getting an accurate picture of the progress of their operations as well as getting trends and patterns that the organization can use to make critical decisions which can bring about progress.