What is Data Integrity?

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Managed Vulnerability Reduction
June 19, 2020

What is Data Integrity?

When speaking of data, most often refer to data protection and data security, but another important aspect of data is called data integrity. Data integrity is defined as the consistency, accuracy, and overall reliability of data. All kinds of organizations use data in order to make decisions regarding their business deals or products; however, even if data is not constantly acted upon, it is vital that data integrity is maintained. If the data is not accurate, not only is the collection and use of it rendered ineffective, but the organization can also fail to meet any necessary regulatory standards.

Maintaining Data Integrity

Violating data integrity can have negative consequences for an organization, thereby making it highly important to set in place processes and frameworks that ensure data remains reliable. When data is accurate, those analyzing it know that errors have been minimized as much as possible. As data is collected (especially if another party or customer enters it), organizations must ensure the data is verified. In some situations, you may end up with duplicate sets of data; remove any unnecessary duplications from the place the data is stored (database, cloud, etc.) Furthermore, data should remain legible during its entire lifetime, such that the data presents information exactly as it was collected originally.

Data should also be accessible to the appropriate, authorized user. While this goes in tandem with data security, data should be secure, but that does not mean it shouldn’t be accessible. Moreover, if organizations deal with customers, they should also be tracing each touchpoint.

The Different Types of Data Integrity

While the aforementioned relate to data integrity as a whole, this field also has specific types of data integrity. Specifically, within logical integrity, a database can maintain entity, referential, domain, and user-defined integrity. Entity integrity refers to having primary keys so that elements are not null, and data is not repeated. With referential integrity, a foreign key refers to a primary key and ensures that data is consistent when in a relationship. Domain integrity is to ensure data within a domain contains the accurate values. Finally, user-defined integrity is beneficial for those who want to set their own restraints on data in order to meet their organization-specific needs.

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