What is Data Classification? Essential 6 Topics To Understand


Data Classification is the process of organizing data as per relevant categories so that it can be used more effectively. Data classification is the process of analyzing structured or unstructured data and organizing it into categories based on file type, contents, and other metadata. It helps management, compliance and data security. It eliminates duplication of data, reduces the storage requirement and increases the processing speed. It makes the data easier to locate and retrieve.

  1. Purpose of Data Classification
  2. Types of Data Classification
  3. Data Classification Process
  4. Example of Data Classification
  5. Methods of Data Classification
  6. Data Classification Best Practices

1. Purpose of Data Classification

The data classification process helps to identify sensitive files and secure crucial data. It helps to track regulated data and optimizes the search capabilities. It identifies the trend inside the data and identifies the duplicate data. It facilitates proper security responses based on the type of data being transmitted or copied. It helps the organization identify and separate the more crucial data from the less crucial one.

2. Types of Data Classification

There are three main types of data classification, which are content-based, context-based, and user-based. Content-based data classification interprets the files looking for sensitive information. Context-based focuses on the location, application etc. User-based relies on user knowledge and discretion. Data Classification can also be useful and automated. User depends on the manual and end-user selection. The advantage is that it helps to identify sensitive data. Automated classification employs a file parser with a string analysis system to find data in the file. It is better than user-based classification.

3. Data Classification Process

The data classification process first involves defining the objectives to identify what compliance regulation applies to your organization. Secondly, we need to categorize the data into different kinds of data at different levels. Next, we have to create workflows based on selected classification tools. Then, we have to define the categories and classification criteria. In the fifth step, we need to define the outcome and usage of the data. Lastly, monitoring and managing of data are important.

4. Example of Data Classification

An example of data classification can be dividing the data into public, private and restricted. The public is the least sensitive data; private is more sensitive and restricted being the most sensitive data. Data classification is also used in customer data, credit card, employee records, supplier contracts.

5. Methods of Data Classification

Equal intervals, manual interval, quantile and natural breaks are some of the methods of data classification.

  • The Equal Interval Classification

Under this method, each class consists of equal data interval. To determine the data interval, divide the total data by the number of classes. 

  • Manual Interval Classification

It allows you to define your own class, add breaks, and set class ranges appropriate for the data. 

  • Quantile Classification

Under this, each class has an equal number of features. It is suitable for linearly distributed data. There are no empty classes or classes with less or a few values.

  • Natural Breaks Classification 

This method classifies the data based on natural groupings inherent in the data. The features are divided into classes whose boundaries are set where there is a difference in the data. 

6. Data Classification Best Practices

  • To identify the rules and regulations which apply to your organization and plan accordingly.
  • Processing large volumes of data accurately and efficiently.
  • Helps you start with a realistic approach.
  • Adjust the rules and validating the results.
  • Determine the project objective and pre-requisites.
  • Figure out solutions and implement the right policy.


Data Classification is a crucial component of information security and compliance program. It serves as a foundation for system security solutions both on the premises. It helps to organize structured and unstructured data into categories. It is useful for the organization in all the industries. It defines a piece of information based on various attributes making it easy to manage data. Data classification provides a clear picture of the data within your organization’s control, and an understanding of where data is stored, how it is most easily accessed.

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