What are the best practices for classifying data based on sensitivity level?

1 What is data classification?

Data classification is the process of assigning labels or categories to data based on predefined criteria, such as the type, source, content, purpose, or owner of the data. Data classification helps to identify the value, risk, and regulatory requirements of the data, and to apply appropriate policies and controls for data security, privacy, quality, and lifecycle management. Data classification can be done manually or automatically, depending on the volume, complexity, and diversity of the data.

2 Why is data classification important?

Data classification is important for several reasons. First, it helps to protect the confidentiality, integrity, and availability of the data, by ensuring that only authorized users can access, modify, or delete the data according to their roles and responsibilities. Second, it helps to comply with the legal, ethical, and contractual obligations of the data, by ensuring that the data is handled, stored, and disposed of in accordance with the relevant laws, regulations, standards, and agreements. Third, it helps to optimize the performance, efficiency, and cost of the data, by ensuring that the data is stored, backed up, archived, and deleted in the most appropriate way, based on its value and usage.

4 How to implement data classification and access control?

Once you have defined your data sensitivity levels and criteria, you need to implement them in a consistent and effective manner. This requires inventorying and mapping your data sources, locations, and flows to understand what you have, where it is, and how it is used. Additionally, you should label and tag your data according to sensitivity levels using metadata, encryption, or other methods. Furthermore, data access policies and rules must be defined and enforced based on the roles and permissions of the users, the data sensitivity levels, and the data usage scenarios. It is also important to monitor and audit your data access activities and incidents to detect any anomalies, breaches, or violations. Lastly, you should review and update your data classification and access control processes regularly to reflect any changes in the data, the business, or the regulations.

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?