![]() Other examples of internally defined metadata include:Īs you grasp these dimensions of data integrity - the lenses through which it can be measured, managed, and threatened - you can use them to guide your approach to establishing data integrity. User-defined integrity refers to rules established by the user that fall outside of domain, entity, or referential integrity.įor example, to strengthen data integrity and safeguard data, an authorized user might add a specific business rule related to GDPR compliance. Ready for another analogy? Think about how a passport is linked to your SSN but gives you verifiable identity to a foreign country with a different societal numbering scheme. It requires a foreign key (a column that links data between tables) to have a corresponding primary key or it must be null.įor example, a common referential integrity constraint requires a customer ID in the Order table must match a valid customer ID in the Customer table. ![]() Referential integrity ensures uniform usage and proper storage of data. In the same way a Social Security Number (SSN) can connect a citizen to a whole host of networks and services, entity integrity connects and preserves distinct identity. And they’d certainly avoid using “home telephone” as a primary key as it would produce null values related to the customers who don’t have a landline. So an auto insurer will designate “policy number” as a primary key in their customer table to avoid duplicative results. It protects against data duplication and incomplete data, among other headaches.įor example, a customer’s name isn’t necessarily unique. ![]() ![]() This could also protect formats, such as a dollar value or significant figure the number of options selected and other structural, input-focused considerations.Ĭonsider this the aspect of data integrity that “protects its domain” or shields its input environment from inaccurate, misplaced, or invalid metadata.Įntity integrity prevents duplicate records and null values by enforcing a unique primary key to identify and retrieve individual records. Because of domain-level data integrity, the user will get an error until they enter the allowed values of the ZIP code field, a five- or nine-digit integer. Since the ZIP code table in the backend database only accepts integers, the value Jones will not be accepted. The most exciting benefits of data integrity include:ĭomain integrity ensures that all data in a field contains valid values.įor example, consider a user who tries to enter their last name into the ZIP code field of an online form. Unless your data is high-quality and trustworthy, there’s little value in it. Gaps in an organizations’ data integrity can lead to poor decision-making that can impact the bottom line. As a result, it’s fueling data democratization and other data management initiatives (i.e., metadata management, marketing taxonomy, and more) to ensure users have easy access to data to perform their job responsibilities. Why is Data Integrity Important? What are its Benefits?ĭata-driven organizations recognize data as an essential asset that can have a significant impact on their bottom line. In other words, data integrity represents structural soundness - maintaining accuracy and completeness in both value and form - everywhere that data lives and flows. Data with integrity is accurate, reliable, optimally stored, and standardized despite modification, transfer, or deletion. Data integrity ensures the value, usability, accuracy, and consistency of an organization’s data from its creation or acquisition through its analysis and observation, and on to its archival or destruction.
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