In this era of data, organizations are struggling hard with the enormous amount of data. Handling and securing a huge amount of data is a daunting task for every other enterprise. To maintain and secure data in compliance with regulations, enterprises have to rely on various best practices and tools that allow to safeguard data. Data classification is one of the tools used to manage and secure data.

The privacy and security of data have to be protected by identifying and tagging the delicate information across the enterprise. The tagging of the data has to be done based on the regulatory compliance of the organization.

What is data classification?

The process of organizing and classifying data into relevant categories to enhance the security of data is termed data classification. The data will be classified based on the pre-defined sensitivity level of data. The process involves data labelling based on its type, accessibility, content, and regulatory compliances.

Data classification allows enterprises to organize structured and unstructured data, which helps to segregate the valuable and unproductive data to make informed business decisions. The classification of data also eliminates the risk of data breaches and helps to secure organizational data.

Purpose of data classification

What is the purpose of data classification?  The major purpose of data classification is to ensure that the data can be found and retrieved easily without much effort.  Once the data is segregated, the organization can implement necessary security measures to reduce the risk of data exposure, eliminate the severity of incidents, decrease the data storage footprint, boost operational efficiency, understand the sensitivity of data, and mitigate security issues.

Well-planned data classification helps to meet the regulatory standards of the industry such as GDPR, HIPAA, PCIDSS, and SOX. Data classification offers data visibility and allows to track how these datasets have been used in different scenarios.

Types of data classification

As mentioned earlier, data has to be classified by tagging the piece of information as per the specified parameters. Mainly, there are three types of data classification such as user-based classification, content-based classification, and context-based classification.

• User-based classification: This type of classification is performed manually and the data will be classified based on the judgement of the person involved. The individual who is working on the data can categorize and verify the sensitivity of the documents based on the discretion made.
• Content-based classification: The classification is done by investigating the sensitive information and interprets the information available. The data will be classified based on the confidentiality and importance of the information stored.
• Context-based classification: In this type of classification, files are being classified by verifying the applications used to create the files, details of the location where the data modification occurred, and creator of the documentation.

Significance of data classification

As discussed earlier in this article, the data classification is important in an organization to reduce data exposure, decrease data footprint, boost operational efficiency, understand the sensitivity of data, and mitigate security issues.

• Reduces data exposure: Data classification helps the organizations to reduce data exposure by keeping the access only to authorized users, identifying the severity of various data types, encrypting data, storing in safe servers, and using strong firewalls.

• Decreases data footprint: Today, a humongous amount of data has been generated daily, which creates security breaches within the organization.  The gradual increase in the sensitive data will make it difficult to prevent these data breaches. The process of classification helps to segregate outdated, extraneous and redundant data from the organizational database, which will decrease the data footprint. Decreasing the data footprint will help in protecting the business data easily and effectively.

• Increases operational efficiency: Enterprises can drive operational efficiency and business performance through data mining and data classification. Classified data enables the businesses to execute the daily operations efficiently. How? It allows them to trace the stored data and the changes made in the information easily.

• Identifies the sensitivity level of data: Classification of the data is done based on the sensitivity levels such as high, low, and medium. Breaches in high sensitivity data such as financial records, data authentication, financial records, etc., will be disastrous for the organization. Data of low sensitivity are those that are for public use like website content. Documentations and emails without confidential data come under medium sensitivity level.

• Mitigates security issues: Segregation and labeling of data help in implementing appropriate cybersecurity measures based on the security and regulation standards of the business. The security measures can be devised based on the location of the stored data and the importance of the data for the organization. By using the right enterprise security solutions, the data can be protected against breaches.

Wrapping up

Based on the enterprise requirements, data has to be categorized in a strategic way to protect, store and manage as per the regulatory and legal compliances. Data classification helps not only in securing the data but also enhances the productivity and decision-making power of the organization.