Data Classification: How to get it right

Not all business data is created equal. Some information is more valuable—and more sensitive—than others. This is where data classification becomes important. It helps separate the low risk information from the highly sensitive and confidential.

What is Data Classification?

Data classification is the process of categorising business information based on its level of sensitivity and the impact to the organisation should that data be disclosed, altered, or destroyed without authorisation. It’s about understanding what data you have, where it resides, and how sensitive or critical it is to your operations.

Why is Data Classification Important?

  1. Risk Management: By identifying your most sensitive data, you can focus your security efforts and resources where they matter most.
  2. Compliance: Many regulations (like GDPR, CCPA or PCI-DSS) require organisations to know what types of data they handle and protect it accordingly.
  3. Data Handling: Classification helps employees understand how to properly handle different types of information.
  4. Access Control: It informs decisions about who should have access to what data.
  5. Data Retention: Classification aids in determining how long data should be retained and when it should be destroyed.

Common Data Classification Levels

While classification schemes can vary, I would suggest that you keep the classification scheme simple. A typical model we use might include:

  1. Public: Information that can be freely shared
  2. Restricted: Information that is usually retained within the business and may be restricted to specific departments. Some restricted information such a client proposals may be shared with outside companies.
  3. Confidential: Sensitive information that could harm the organisation if disclosed. This information will normally be restricted to specific individuals or processes. Staff information (for example, payroll and HR records) would sit in this category.

Steps to Implement Data Classification

  1. Identify Your Data: Complete a data audit to understand the different types of data your organisation handles.
  2. Develop a Classification Scheme: Create categories that align with your organisation’s needs and risk profile.
  3. Classify the Data: Assign each piece of data to a category. This can be done manually or with automated tools.
  4. Label the Data: Ensure data is clearly marked with its classification level.
  5. Implement Security Controls: Apply appropriate security measures based on the classification level.
  6. Train Employees: Educate staff on the classification system and their responsibilities.
  7. Review and Update: Regularly review your classification scheme and reclassify data as needed.

Challenges in Data Classification

Data classification isn’t without its challenges. It can be time-consuming, especially for organisations with vast amounts of data. There’s also the risk of over-classification, which can hinder productivity, or under-classification, which can leave sensitive data vulnerable.

Despite these challenges, the benefits of data classification far outweigh the difficulties. It provides a foundation for effective information security, helping organisations protect what matters most while enabling the free flow of less sensitive information.

In conclusion, by understanding the value and sensitivity of your data, you can make informed decisions about how to protect it, ensuring that your most critical assets receive the highest levels of security.

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