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What Is Data Integrity and Why Is It Important?

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Over the years, data integrity has been a pressing issue, with online data theft cases making headlines. Data theft has caused many businesses and individuals to lose valuable assets.

Data integrity is a modern practice that makes you less vulnerable to cyberattacks. Since anyone can be a victim of a security breach, neglecting it is an act of carelessness.

This article will discuss different types of data integrity, the importance of data integrity, and how to ensure data integrity in a database.

What Is Data Integrity?

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Data integrity is a collection of critical measures to ensure allocated data in a system is safe, secure, and unaltered. Emergencies do come up. Hence, data integrity determines how accurate data is, even after resolving the issue.

Most popular companies you see today have where they store data. Some of these companies deploy specialists to secure their data, and others work with massive data centers. Keeping information safe is mandatory and critical for online regulatory compliance. This practice is a must and applies to everyone in general.

Data integrity also has to do with complying with online rules and regulations, especially a significant one like the General Data Protection Regulation (GDPR). If you’re building an online startup, embracing its tactics is necessary. Online theft prevails in the absence of data integrity, and its consequences are destructive.

Data leaks have caused harm to more businesses than you can imagine, and it forces companies to close up. However, before you delve into online enterprising, you must first understand what data integrity entails and why it’s significant.

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Why Is Data Integrity Important?

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You can’t overemphasize the importance of data integrity. When data integrity is at its peak, cyber attackers find it difficult to penetrate a system. All attempts fail and result in nothing.

Data integrity is mainly altered when there’s a fatal hit, emergency, or breach.

GDPR compliance involves a set of regulatory standards set by a high reputation organization to reduce cases of data leaks. It requires that any online business processing data in any form must abide by the rules bestowed to avoid penalties and subtle consequences.

Before you can fully secure data, you must also look into the safety of this data and how they’re processed. A slight misinterpretation or mix-up may lead to huge inevitable circumstances.

The importance of data security extends to businesses; it also applies to individuals. To protect sensitive information from leaking, you need to assess internal handling. Validating data and keeping an eye on the system for error checks reduces the chances of miscategorizing or altering data. No matter how long you store or access sensitive information, a secure database with complete integrity will continue to offer protection against malicious intent.

Types of Data Integrity

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Imagine working in a company with several departments alongside other employees. Say, these employees work in two different sectors such as health and finance. Does that require you to store their information twice? No, you don’t.

Data integrity maintains that no data must be duplicated inappropriately. The selection, deletion, and allocation of sensitive data contribute to its accuracy.

Here are four primary types of data integrity.

1. Domain Integrity

Assume you have a storage unit titled “Workers Wages,” and you wish to input the salaries of all employees in it. Domain integrity ensures only acceptable values gain entry. It consists of several acceptable values inputted in one column and filters unwanted entries.

Domain integrity utilizes characters, text, date, and much more. For example, if you’re making an entry for a column, it should also be in the domain of the data type.


2. Entity Integrity

Entity integrity helps differentiate two or more similar data types likely to confuse retrieval. It enables you to select data from a table by ensuring that each row in a table is unique.

Entity integrity is implemented using unique primary keys. For instance, two of your workers bear the name Anderson, and you want to locate one of them. Differentiating these two data fields with a primary key allows you to input what data you intend to retrieve quickly.

3. Referential Integrity

Referential data integrity is primarily applicable when maintaining a database. It involves using foreign keys to change a database without affecting its integrity.

Referential data integrity states that foreign keys referring to primary keys in the second table must have a null value in the first storage or be present in the second storage, with specific rules regarding what the foreign key can change. Restricting the access and editorial ability of a foreign key protects the data integrity of the primary data.

4. User-Defined Integrity

All three data integrity types mentioned above are efficient—but not enough to resist data interruption. This is where user-defined integrity comes in, defining specific and applicable rules that every entity, domain, and key must follow.

How to Ensure Data Integrity in a Database

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When it comes to ensuring data integrity, some guidelines can’t be left out, such as those involved with GDPR compliance and the FDA draft on data integrity. However, things have switched up. Before collecting data, you must ensure the highest degree of data integrity.

Below are some tips to help protect your data.

1. Cleaning and Maintenance

A system doesn’t remain stagnant. Data is processed continually, and employees interact with the system regularly, so it evolves. With these constant changes to data storage, you need to erase system errors frequently, ensuring the data collected remains unaltered and secure.

User authentication is an effective technique for cleaning and maintaining your data. It ensures that only verified users access your data.

2. Data Entry Training and Responsibility

Ensuring the highest level of data integrity is the new normal. However, you’ll have to handle a few malicious attempts, no matter how hard it is to resist them. It’s a code of conduct to equip employees with the knowledge and tactics needed to secure and make data efficient.

Techniques like penetration testing are helpful in data entry and responsibility. By launching deliberate attacks on your system, you are in a better position to identify the loopholes that attackers would exploit.

3. Data Validation

To err is human. Manually inputting data into a system is a common practice, yet it isn’t completely efficient.

Data validation requires you, as an admin, to control data values of information stored by an employee. By doing this, you can easily prevent the system from accidental modifications. Best of all, your data analytics improves.

Data exposure has led to the downfall of many businesses and triggered many others to embrace data integrity. Cleaning your system continuously and validating your data are just a few of the many measures to follow.

Using a single data source code is optional yet effective. It promotes data accuracy and makes tasks more manageable. Automation also works fine.

Have your employees undergo all necessary training and enlighten them on the effects of data exposure.


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