How to Ensure GDPR Compliance Using Data Governance

The General Data Protection Regulation (GDPR) is one of the most significant pieces of legislation impacting data protection and privacy in the European Union (EU). It came into effect on May 25, 2018, and established strict guidelines on how personal data should be collected, processed, stored, and shared. For organizations that handle personal data, GDPR compliance is not just a legal obligation, but also an essential part of maintaining trust with customers, partners, and stakeholders. 

To ensure compliance with GDPR and promote responsible data management, organizations must embed data governance best practices into their operations. Data governance involves creating policies, standards, and procedures for handling data assets, ensuring that data is accurate, accessible, secure, and used appropriately. Below, we will explore key data governance best practices under the GDPR law. 

1. Identify and Classify the Data

Begin by identifying and mapping all personal data within the organization. This includes understanding where the data comes from and how it’s processed, stored, and shared. Next, categorize the data based on sensitivity and its purpose to ensure proper handling and protection. 

2. Minimize the Data

Only collect data that is necessary for the specific purpose for which it is being processed. Avoid collecting excessive data that isn’t required. Then, ensure that personal data is only used for the purposes it was collected and not repurposed without the individual’s consent.  

3. Establish Access Control and Security

Implement role-based access controls (RBAC) so that only authorized personnel can access personal data. Organizations should also encrypt sensitive personal data at rest (such as on a hard drive) and in transit (such as online or through email) to protect it from unauthorized access. Where possible, companies should anonymize or pseudonymize data to reduce the risk of exposure in case of a data breach.  

4. Build Privacy in From the Beginning

Ensure that privacy is built into business processes, systems, and operations from the outset. Implement default privacy settings that maximize data protection, such as default data sharing settings set to the most restrictive level.  

5. Manage Data Subject Rights

Establish procedures to handle data subject rights – such as the right to access, correct, erase, or restrict processing of their data – within the timeframes mandated by GDPR. Provide clear instructions to data subjects on how to exercise their rights, ensuring ease of access and transparency. 

6. Enforce Data Retention and Deletion Policies

Create and enforce clear data retention policies that specify how long personal data will be retained. Personal data should only be kept as long as necessary to fulfill the purpose for which it was collected. Additionally, implement a process for securely deleting data that is no longer needed, in accordance with retention policies. This includes ensuring that data is securely erased from all systems, backups, and storage devices. 

7. Manage Vendors and Third Parties

Ensure that any third parties who process personal data on behalf of the organization (data processors) comply with GDPR by signing Data Processing Agreements (DPAs). These agreements should clearly outline roles, responsibilities, and data protection obligations. Regularly assess and audit third-party vendors to ensure they are maintaining the required level of data protection. 

8. Develop a Data Breach Response Plan

Develop and maintain a robust data breach response plan that complies with GDPR’s 72-hour breach notification requirement. The plan should include immediate actions, internal notifications, and notifications to affected individuals and relevant authorities. Investigate any potential breaches thoroughly and document the findings. This includes tracking the impact and the corrective actions taken to mitigate the issue.  

9. Document All Data Processing Activities

Maintain comprehensive records of data processing activities. Document what data is processed, why it’s processed, the legal basis for processing, and how long the data will be retained. Ensure that the organization’s data governance practices are well-documented to demonstrate compliance with GDPR during audits. This includes maintaining policies, training records, consent logs, and data processing agreements.

10. Conduct Data Protection Impact Assessments (DPIAs)

For high-risk data processing activities, such as large-scale processing of sensitive data, conduct Data Protection Impact Assessments (DPIAs) to identify and mitigate potential risks to the data subject’s privacy. Implement measures to mitigate identified risks, such as pseudonymization, encryption, or restricting access to the data. 

11. Provide GDPR Training

Provide ongoing GDPR training for employees to ensure they understand their roles and responsibilities in protecting personal data. This should include the principles of data privacy, data subject rights, and the handling of sensitive data. Foster a culture of privacy within the organization by continuously raising awareness about GDPR compliance and data protection best practices.

12. Appoint a Data Protection Officer (DPO)

If required, appoint a Data Protection Officer (DPO) to oversee the organization’s data protection activities. The DPO will be responsible for ensuring GDPR compliance and acting as a point of contact for data subjects and regulatory authorities. The DPO should operate independently and have the authority to raise privacy concerns directly to top management. 

13. Ensure Compliance With Data Transfers Outside the EU

If personal data is transferred outside the EU, ensure compliance with GDPR’s requirements for international data transfers. This may involve using Standard Contractual Clauses (SCCs), Binding Corporate Rules (BCRs), or ensuring that the destination country has an adequate level of data protection. 

14. Audit Processes and Continue to Improve

Regularly audit data governance processes to ensure compliance with GDPR. These audits should assess data processing activities, security measures, access controls, and handling of data subject rights. Continuously monitor and update data governance practices to address new risks, changes in business processes, or updates to data protection laws. 

By implementing these best practices, organizations can create a robust data governance framework that ensures compliance with GDPR, mitigates risks, and fosters trust with customers and stakeholders. 

GDPR Compliance is Crucial to Data Governance Practices

GDPR compliance is integral to modern data governance practices, and implementing these best practices can help organizations safeguard personal data, foster trust, and avoid costly penalties. By creating a solid data governance framework, embedding data protection principles into every aspect of the organization, and maintaining ongoing compliance efforts, the organization will not only meet legal obligations but also gain a competitive advantage. 

Get Data Governance Assistance From Actian

Actian has an all-in-one data intelligence platform that provides advanced governance solutions. It can help organizations ensure compliance with regulations like GDPR, manage data assets, and effectively leverage information for better decision making. Try a tour of the platform today to get a better idea of how Actian can help businesses thrive amidst regulatory restrictions and increasing amounts of data to manage. 

About Actian Corporation

Actian makes data easy. Our data platform simplifies how people connect, manage, and analyze data across cloud, hybrid, and on-premises environments. With decades of experience in data management and analytics, Actian delivers high-performance solutions that empower businesses to make data-driven decisions. Actian is recognized by leading analysts and has received industry awards for performance and innovation. Our teams share proven use cases at conferences (e.g., Strata Data) and contribute to open-source projects. On the Actian blog, we cover topics ranging from real-time data ingestion, data analytics, data governance, data management, data quality, data intelligence to AI-driven analytics.