Blog Blog Posts Business Management Process Analysis

What is Data Classification?

The process of organization and categorization of data is known as data classification. In this blog, we will discuss the ways to do data classification and its essentials. 

Table of Contents

Learn the Ethical Hacking course in-depth by watching the video below

“@context”: “”,
“@type”: “VideoObject”,
“name”: “Ethical Hacking Course | Ethical Hacking Tutorial Online | Learn Ethical Hacking | Intellipaat”,
“description”: “What is Data Classification?”,
“thumbnailUrl”: “”,
“uploadDate”: “2023-07-18T08:00:00+08:00”,
“publisher”: {
“@type”: “Organization”,
“name”: “Intellipaat Software Solutions Pvt Ltd”,
“logo”: {
“@type”: “ImageObject”,
“url”: “”,
“width”: 124,
“height”: 43
“embedUrl”: “”

What is Data Classification?

Ensuring data security is the purpose of data classification. It carefully looks into the way data is stored, processed, and transmitted securely. It involves analyzing data, evaluating its importance, and assigning a classification level based on its attributes. The classification level determines the level of protection and management requirements for the data.

The data classification process consists of the following steps:

Data Classification Process

Interested to learn about Ethical Hacking? Enroll now in Ethical Hacking Training!

Importance of Data Classification

Data classification is crucial for organizations for the following reasons:

Check Out  Ethical Hacking Interview Questions to crack your ethical hacking job interview!

Types of Data Classification

Types of Data Classification

There are different types of data classification based on the attributes. Some of the common types of data classification are:

Read On: Ethical Hacking Tutorial to enhance your knowledge!

How to Implement Data Classification?

Once the data has been identified, it can be classified based on various criteria, such as content, format, purpose, and sensitivity. Some common classification categories include confidential, internal use only, public, and restricted access.

 Manual classification is another method where a person goes through each piece of data and assigns a category.  This method can be time-consuming and prone to human error. However,  it allows for a more personalized and specific approach to classification. 

On the other hand,  automatic classification requires software to analyze data and classifies it based on predetermined rules. This method is faster and more consistent. Nevertheless, it may not be as accurate as manual classification.

There are several techniques used in data classification, such as rule-based classification, where a set of rules is used to determine the classification of data. The rules can be based on keywords, file types, or other criteria.  Machine learning-based classification is another technique. In this, machine learning algorithms are used to analyze data and classify it based on patterns and characteristics.

Benefits of Data Classification

Below we will highlight some of the benefits of data classification:

Example of Data Classification

Let’s find out an example of data classification by considering a scenario where you manage an e-commerce company’s customer database. 

You have a Google Sheets spreadsheet containing customer information, such as names, email addresses, and purchase history. You classify the data based on customer types to ensure data consistency and accuracy.

Here is an example of data classification using Google Sheets with data validation:

Data validation ensures that only specific values (customer types) can be selected in the “Customer Type” column, thereby classifying the customers accordingly. This classification enables you to segment your customers and perform targeted analysis or marketing strategies based on their type.

Challenges in Data Classification

One of the challenges of Data classification is the lack of a standardized classification system. Different organizations may use different classification categories, making it difficult to share data between organizations.  The constant evolution of data is another challenge. As new types of data emerge, classification criteria may need to be updated to reflect these changes.

One of the most significant challenges in data classification is the lack of clear guidelines or standard procedures to follow. Different organizations have different data classification criteria, which can result in inconsistent classification across departments or even within the same department. This can lead to confusion and errors in the classification process, affecting the quality and usefulness of the data.

Data classification is only as good as the data it is based on. Incomplete or inaccurate data can lead to incorrect classification, making the process of informed decisions challenging the accuracy of data classification relies heavily on the quality of data, which can be affected by various factors, such as data collection methods, data storage, and data management practices.

The rapid evolution of data types, particularly unstructured data, poses a significant challenge in data classification. The traditional methods of data classification may not be effective in categorizing the vast amounts of unstructured data generated daily. Unstructured data, such as emails, social media posts, and images, can be difficult to classify since they lack a standard structure, making it hard to apply consistent classification criteria.

Data classification is a complex process that requires a considerable amount of human input. Human error, such as typos, incorrect categorization, and inconsistent application of classification criteria, can lead to incorrect data classification, making it difficult to make informed decisions. However, clear and concise guidelines,  training, and carefully assigning tasks can minimize the risk of human error.

Data classification can be a time-consuming and resource-intensive process. It requires a considerable amount of resources, such as personnel, technology, and infrastructure, which can be expensive for organizations, especially for small and medium-sized businesses. The cost and resource requirements of data classification can deter organizations from implementing effective data classification strategies.

Lack of awareness or understanding of data classification can be a significant challenge for organizations. Many businesses do not fully understand the benefits of data classification, leading to underinvestment in the process. This can result in suboptimal data management practices, compromising the quality and usefulness of data.


Proper data classification is crucial for efficient data management and protection. It allows for easier data retrieval and protects sensitive information from unauthorized access. However, the challenges, such as the lack of a standardized classification system, the constant evolution of data, and the risk of human error, can impact the data. Therefore, it’s essential to be careful while classifying the data.

If you have any questions, ask them in our Cyber Security Community.

The post What is Data Classification? appeared first on Intellipaat Blog.

Blog: Intellipaat - Blog

Leave a Comment

Get the BPI Web Feed

Using the HTML code below, you can display this Business Process Incubator page content with the current filter and sorting inside your web site for FREE.

Copy/Paste this code in your website html code:

<iframe src="" frameborder="0" scrolling="auto" width="100%" height="700">

Customizing your BPI Web Feed

You can click on the Get the BPI Web Feed link on any of our page to create the best possible feed for your site. Here are a few tips to customize your BPI Web Feed.

Customizing the Content Filter
On any page, you can add filter criteria using the MORE FILTERS interface:

Customizing the Content Filter

Customizing the Content Sorting
Clicking on the sorting options will also change the way your BPI Web Feed will be ordered on your site:

Get the BPI Web Feed

Some integration examples