How do you classify your data?

1 What is data classification?

Data classification is the process of organizing data into categories based on its level of sensitivity, confidentiality, and regulatory compliance. Data classification helps you identify what data you have, where it is stored, who can access it, and how it should be handled. Data classification also enables you to apply appropriate security measures, such as encryption, access control, backup, and retention policies, to protect your data from unauthorized use, disclosure, or loss.

2 Why is data classification important?

Data classification is important for several reasons. First, it helps you comply with legal and regulatory requirements, such as GDPR, HIPAA, PCI DSS, and others, that mandate how certain types of data should be treated. Second, it helps you reduce the risk of data breaches, data leakage, and data loss, by ensuring that only authorized users can access and modify sensitive data. Third, it helps you optimize your data storage, management, and usage, by allowing you to prioritize the most valuable and critical data and allocate resources accordingly.

3 How to classify your data?

Data classification is not a one-size-fits-all approach, as different organizations may have different criteria and standards for their data. A common practice is to use a four-tier model that categorizes data into four levels: public, internal, confidential, and restricted. Each level has a different degree of sensitivity and impact, thus requiring a different level of security and protection. Public data can be shared without any negative consequences; examples include marketing materials, press releases, product information, and public reports. Internal data should only be disclosed to external parties with authorization; examples include employee records, policies, procedures, and financial data. Confidential data contains sensitive information that could harm the organization or its stakeholders if exposed; examples include customer data, trade secrets, intellectual property, and contracts. Restricted data contains highly sensitive information that could cause severe damage or legal liability if compromised; examples include personal data, health data, credit card data, and classified data.

4 How to implement data classification?

Implementing data classification requires a systematic and consistent process. Firstly, you must define your data classification policy, which outlines the objectives, scope, roles, responsibilities, and procedures for data classification in your organization. It should also define the criteria and standards for each data category, as well as the security measures and controls for each level. Secondly, you must inventory your data by identifying and locating all the structured and unstructured data you have across all systems, devices, and platforms. Tools such as data discovery, data mapping, and data cataloging can assist with this step. Thirdly, assign roles and responsibilities to individuals or groups who are accountable for the creation, maintenance, and security of each data set. Data owners should have the authority and knowledge to classify their data and enforce the data classification policy. Fourthly, label your data with tags that indicate its category, sensitivity, and security requirements. Tools such as metadata management, data labeling, and data encryption can help with this step. Lastly, audit and monitor your data by reviewing its accuracy and effectiveness of your data classification as well as detecting any changes or incidents that may affect it. Data quality, data governance, and data security tools can assist with this step.

5 What are the benefits of data classification?

Data classification can bring many advantages to your organization, such as improving your information security posture, increasing operational efficiency, and enhancing business performance. By classifying your data according to its importance, risk, and impact, you can reduce the exposure and vulnerability of your data, streamline data storage and management, and leverage your data for decision making. However, data classification is not a one-time project; it requires continuous improvement and adaptation to ensure that your data remains secure, compliant, and valuable.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?