What Are The Different Levels Of Data Classification?

The process, by which data is analyzed and organized into relevant categories, is called data classification. Its purpose is to protect the data efficiently. The data classification process has immense importance in risk management, data security, and compliance. The process increases the speed of search by canceling multiple duplications and reducing the storage of data.

The data classification process makes data easily tractable and reduces backup costs. The process needs compliance with data privacy regulations.

Levels Of Data Classification

An organisation has four levels of classification for data. The classification is dependent on the sensitivity of data a company holds. The different levels of Data Classification are in the following.

1. Public

The first data classification level includes public data that is easily accessible to the general public. Public data needs no additional controls and security protocols. A company can use, reuse and share public data on its website. The promotional content of a company’s product and services or job descriptions are examples of pubic data.

2. Internal

Internal data, a data classification level, allows sharing of data with only the company’s personnel or employees. The data is not sensitive, but it can’t be shared with the general public. Business plans, company memos, and employee handbooks are examples of internal data.

3. Confidential

Confidential data is sensitive and so has strict access control within the company. The data can be shared with a particular team only. Its access needs specific authorization. Pricing policies, cardholder data, and social security numbers are confidential information.

4. Restricted

Restricted data is more sensitive than confidential data. So, anybody within the company can’t access this type of data. Even access to restricted data without authorization is considered a criminal charge. Non Disclosure Agreement protects this data and reduces legal risk. Credit card information and financial information are examples of restricted data.


Data classification levels reduce the risk of sensitive data being compromised. Its enforcement within a company is essential.