Not all data is equal. Some information, such as client records or financial details, requires far stricter protection than everyday business correspondence. Data classification is the process of organising information into categories based on its sensitivity and importance.
By correctly classifying data, businesses can apply the right level of security to each category, reduce risk, and demonstrate compliance with both GDPR and Cyber Essentials requirements.
Why Data Classification Matters
Protecting sensitive information – ensures confidential data is only accessible to those who need it.
Compliance – GDPR requires organisations to know what personal data they hold, why they hold it, and how it is protected.
Efficient security – Not all data needs the same level of protection. Classifying information avoids unnecessary costs while still keeping sensitive data safe.
Incident response – In the event of a breach, classification helps determine what data has been compromised and how serious the impact is.
Typical Data Categories
While each company can define its own data definitions and categories, below are some of the more common.
Public Data – Information intended for open use, such as website content or published marketing material. Minimal protection required.
Internal Data – Everyday business information not meant for public release, e.g., staff contact lists or meeting notes. Protected by standard access controls.
Confidential Data – Sensitive business information, such as HR files, internal financial reports, or client contracts. Access should be restricted to authorised personnel only.
Restricted Data – Highly sensitive data, including personal client information, medical records, or payment details. This category requires the strongest protections, such as encryption, multi-factor authentication, and strict access controls.
Under GDPR legislation, companies must:
Identify personal data they process.
Justify why they hold it and ensure it is used lawfully.
Protect it proportionately based on risk.
Data classification makes this possible by clearly separating personal data from non-personal data and ensuring sensitive categories receive the highest safeguards.
For Example: If your business holds both client names (personal data) and product stock lists (non-personal data), GDPR requires greater protection for the former. Without classification, it’s easy to apply the wrong level of security or overlook data protection obligations altogether.
Conclusion
Data classification is the foundation of any effective data protection strategy. By categorising information and applying the right level of security, organisations can:
Reduce the risk of unauthorised access
Protect sensitive personal data
Comply with GDPR obligations
Meet Cyber Essentials security standards
In short, classification ensures your business doesn’t treat all data the same but protects the most valuable information with the care it deserves.