The European Union established the General Data Protection Regulation (GDPR) in 2018 to protect the privacy and personal data of EU citizens. GDPR applies to any organization that collects, processes, or stores the personal data of EU citizens, regardless of the organization’s location.
One of the key requirements of GDPR is that personal data must be accurate, up-to-date, and relevant. This means that organizations must ensure that their customer data is accurate and complete and that it is kept up-to-date over time. Failure to comply with GDPR can result in hefty fines, damage to reputation, and lost customers. Therefore, data cleansing is essential to ensure GDPR compliance.
What is Data Cleansing?
Data cleansing is the process of detecting and correcting or removing inaccurate, incomplete, or irrelevant data from a database. It involves identifying and correcting errors, inconsistencies, and duplications in the data to ensure that it is accurate, complete, and up-to-date. Data cleansing is also referred to as data scrubbing or data cleaning.
The Importance of Data Cleansing for GDPR Compliance
GDPR requires organizations to ensure that personal data is accurate, up-to-date, and relevant. This means that organizations must take steps to ensure that their customer data is accurate and complete, and that it is kept up-to-date over time. Failure to comply with GDPR can result in hefty fines, damage to reputation, and lost customers. Therefore, data cleansing is essential to ensure GDPR compliance.
Here are some ways in which data cleansing can help organizations ensure GDPR compliance:
- Identifying and Correcting Inaccurate Data
Data cleansing can help organizations identify and correct inaccurate data in their databases. It can be done by various techniques one of which is the various software services.You can follow this link for a data matching tool which is a user-friendly solution designed to clean, match, and deduplicate data. This can include misspelled names, incorrect addresses, and other errors that can lead to data breaches or non-compliance with GDPR. By correcting inaccurate data, organizations can ensure that their customer data is accurate and up-to-date, reducing the risk of data breaches and penalties.
- Eliminating Duplications
Data cleansing can also help organizations eliminate duplications in their customer databases. Duplications can lead to confusion and inconsistencies in customer data, making it difficult to ensure GDPR compliance. By removing duplications, organizations can ensure that each customer’s data is accurate and complete, and that there are no inconsistencies or errors in the data.
- Removing Irrelevant Data
GDPR requires organizations to ensure that personal data is relevant to the purposes for which it is being processed. This means that organizations must ensure that they only collect and process data necessary for the purposes for which it is being used. Data cleansing can help organizations identify and remove irrelevant data from their customer databases, ensuring that they only collect and process data necessary for their business operations.
- Keeping Data Up-to-Date
GDPR requires organizations to ensure that personal data is up-to-date. This means that organizations must take steps to ensure that their customer data is kept up-to-date over time. Data cleansing can help organizations identify and update outdated data in their customer databases, ensuring that their data is accurate and up-to-date.
- Enhancing Data Quality
Data cleansing can also help organizations enhance the quality of their customer data. By ensuring that data is accurate, complete, and up-to-date, organizations can improve the quality of their customer data, reducing the risk of data breaches and ensuring GDPR compliance.
Real-World Examples of the Importance of Data Cleansing for GDPR Compliance
In 2018, British Airways suffered a data breach that affected approximately 500,000 customers. The attackers gained access to the customers’ personal and financial information, including their names, addresses, email addresses, credit card numbers, and expiry dates.
The breach was caused by a vulnerability in British Airways’ website, which allowed the attackers to steal sensitive information from the payment page. The vulnerability was caused by outdated code that was not properly maintained or updated.
One of the factors that contributed to the breach was the lack of proper data cleansing practices. British Airways failed to identify and remove outdated and redundant data, which made it easier for the attackers to exploit the vulnerability and gain access to sensitive information.
Data cleansing could have prevented the breach by identifying and removing outdated code and data, reducing the attack surface and making it harder for attackers to exploit vulnerabilities.
In addition, data cleansing could have helped British Airways comply with the General Data Protection Regulation (GDPR), which requires organizations to ensure the accuracy and completeness of personal data and take appropriate measures to protect it from unauthorized access.
The Equifax Breach
Another example of a data breach that could have been avoided through proper data cleansing is the Equifax breach in 2017. Equifax, a consumer credit reporting agency, suffered a data breach that affected 143 million individuals. The breach was caused by a vulnerability in an open-source software framework that Equifax used, which was left unpatched for months.
The breach resulted in the exposure of sensitive personal information, including Social Security numbers, birth dates, addresses, and credit card numbers. Equifax faced numerous lawsuits and regulatory fines, and its reputation was severely damaged.
One of the factors that contributed to the breach was the lack of proper data cleansing practices. Equifax failed to detect and remove outdated and redundant data, which made it easier for the attackers to exploit the vulnerability and gain access to sensitive information.
In conclusion, data cleansing is a critical component of a comprehensive data protection strategy. It helps organizations to identify and remove outdated, redundant, and inaccurate data, reducing the risk of data breaches and regulatory non-compliance. By implementing proper data cleansing practices, organizations can protect their customers’ personal data, maintain their reputation, and avoid costly fines and legal action.
