Being a valuable asset of any organization, data can make huge impacts on how businesses are running: boost revenue, make future predictions and improve business decisions, enhance customer experiences, or increase employees’ efficiency. But when data is inconsistent, unreliable, and inaccurate, business decisions will be bad and ineffective. The success of a company depends on the data quality, where data integrity is the core part. Data integrity refers to consistent, completed, accurate, and precise data in a data warehouse which contributes to the overall business wellbeing. Many business executives mistrust in their data and analytics, and this data, in turn, affects corporate reputation. In terms of security and regulatory compliance, data integrity is the key factor. That means maintaining the consistency of data throughout its lifecycle ensures data protection and reliability. Minimizing data integrity risks will help to achieve data security. Let’s take a closer look at these terms.
Data Integrity vs. Data Security
These two concepts are related to each other; however, they differ. When we are talking about data security, it means ensuring cyber attacks prevention and that only authorized users can get access to the database to modify data. Data integrity on the other hand, is concerned with keeping the data pure, correct, and uncorrupted. Data integrity includes data security to restrict unauthorized users from modifying data.
Data Integrity Risks
In order to ensure data integrity, one has to consider how devastating risks can be.
- Human errors. Without following an appropriate protocol, employees can enter incorrect data, duplicate or delete it, which leads to compromised data integrity.
- Transfer errors. When transferring from one database to another, some transfer errors can occur. Data integration platforms allow data to be transferred seamlessly, correctly, and streamlined.
- Non-compliance with regulations.It is vital for organizations to satisfy the demands of GDPR, as non-compliance can lead to significant penalties, and repeated violations can ruin your business.
- Compromised hardware. Crashes on the devices or servers lead to errors due to which data rendering is incompleted, and access to data can be limited or denied.
- Bugs and viruses.Due to cyber attacks, data can be modified, stolen, or deleted, which makes data integrity jeopardized.
How to Ensure Data Integrity
Since data integrity risks can backfire on data-driven processes, it is of high priority to think over strategic planning for the elimination of threats. So in order to achieve data integrity, it is essential to adhere to standards and take the following measures:
1. Clean data
Before you do any type of data processing, it is vital to implement data cleansing on a regular basis. Cleaned and up-to-dated data leads to good data quality, which can also be obtained through data integration from different systems.
2. Implement audit trails.
Audit trails help check the actions made in the database, timestamps of access throughout the entire lifecycle. Audit trails are one of the most effective measures for minimizing data integrity risks and assuring that data records have not been altered or deleted.
3. Limit access to data.
It is important to define access restrictions. Permit access only to authorized users. Ensure that accounts are not shared, and access to a specific data is granted only for those who really need it. Keep sensitive physical records locked and secured. The limited and restricted access policy can prevent losses and corruption, as well as social hacking.
4. Validate data.
Make sure the data is correct and meaningful when gathered and used. There should be a data validation system with predefined rules defining the process of data saving. Accuracy and consistency of data depend on removing duplicates from the database.
5. Back up data.
In terms of security and prevention of data loss, a well-performing data back-up and recovery strategy is the key aspect for successful data integrity. There are different back-up locations where you can store files (cloud-based, within the same data center, or off-site).
6. Reduce transfer errors.
To ensure the complete data transfer, you need to care about the security measures. With this purpose, there are hash values that can be attached to the data, and afterwards, checked by the receiver who can see if it is completed.
7. Use error-detection software.
Since manual inspections are not accurate, error detection software is proven to be efficient in identifying errors and preventing them in the future.
Dangerous and bad data can have devastating consequences on any business. Without data integrity in mind, business executives might suffer from significant costs and risks that can affect their revenue and overall business performance. To ensure data integrity in business processes, organizations have to adhere to standards and keep abreast of threats. Data quality and data security are crucial aspects of data integrity. That’s why it’s so vital for businesses to care about data accuracy, completeness, and consistency throughout each stage of the lifecycle.