Because we have entered a world where data is your company’s most valuable asset: the quality, security, and health of your data are essential. To guarantee this, you need to ensure its integrity at all times. Would you like to understand the fundamental rules of Data Integrity to set your company on the path to serene and reliable exploitation of data? Follow this guide!
While the notion of integrity is often mentioned when talking about security and data being compromised, it should not be confused with Data Integrity, which is a discipline on its own in the complex and demanding world of data exploitation.
The exact definition of Data Integrity is maintaining and ensuring the accuracy and consistency of data throughout its life cycle.
Ensuring Data Integrity means ensuring that the information stored in a database remains complete, accurate, and reliable. And this, regardless of how long it is stored, how often it is accessed, or how it is processed.
The different types of Data Integrity
The concept of Data Integrity is complex because it takes multiple forms and meanings. Beyond an overall approach to Data Integrity, it is important to understand that there are different types of Data Integrity. These different types are not in opposition to each other, but rather complement and combine each other to ensure the quality and security of your data assets.
Guaranteeing Data Integrity, in all its dimensions, is not only a matter of compliance but also of optimal use of the available information. There are two main types of Data Integrity: physical integrity on the one hand, and logical integrity on the other.
Protecting the physical integrity of data means avoiding exposing it to human error and hardware failure (such as storage server malfunctions, for example).
It also means making sure that the data cannot be distorted by system programmers, for example. In the same way, the physical integrity of the data is called into question when a power failure or a fire affects a database.
Finally, the physical integrity is also compromised when a hacker manages to access the data.
Ensuring the logical integrity of your data means making sure that the data remains unchanged under all circumstances. While logical integrity is, like physical integrity, intended to protect data from human manipulation and error, it is exercised in a different way and on four distinct axes:
Entity integrity is the principle of associating primary keys with the data collected. These unique values identify all of your data elements. It is an effective guarantee against duplicates, for example, because each piece of data is only listed once.
The principle of referential integrity describes the series of processes that ensure that data is stored and used in a uniform and consistent manner. Repository mode is your best assurance that only the appropriate and authorized data changes, additions, or deletions are made. Referential integrity allows you to define rules to eradicate duplicate entries or to verify the accuracy of the data entered in real-time.
Domain integrity refers to the set of processes that ensure the accuracy of data attached to a domain. A domain is characterized by a set of values that are considered acceptable and that a column can contain. It can include different rules to define either the format or type of the data or the amount of information that can be entered.
User-defined integrity involves rules created by the user to meet their needs related to their own usage. By adding a number of specific business rules to Data Integrity measures, it is possible to complement the management of entity integrity, referential integrity, and domain integrity.
Why is it important to ensure data integrity?
Data integrity is important for two key reasons.
The first concerns data compliance. As the GDPR sets strict rules and provides for severe penalties, ensuring Data Integrity at all times is a major issue.
The second is related to the use of your data. When integrity is preserved, you have the certainty that the information available is reliable and of quality, and, above all, in line with reality!
The differences between Data Integrity and Data Security
Data Security is a discipline that brings together all the measures that are deployed to prevent data corruption. It is based on the use of systems, processes, and procedures that restrict unauthorized access to your data.
Data Integrity, on the other hand, addresses all the techniques and solutions that ensure the preservation of the integrity and accuracy of the information throughout its life cycle.
In other words, Data Security is one of the components that contribute to Data Integrity.