What Is Data Classification & Why Is It Important?

Data classification is an integral part of data processing, business intelligence, and data security. Data classification ensures organizations don’t lose track of data, especially its meaning and priority concerning privacy and intellectual property protections. 

To fully appreciate data classification, though, it is first essential to understand what it is.

What Is Data Classification?

Data classification is the process of organizing and coherently labeling data using predefined criteria to determine its type, business value, and degree of sensitivity. As a result, it becomes easier to subject data to business intelligence activities, such as retrieval, sorting, merging, and improved storage for future use.

Types of Data

Before understanding how data is labeled and organized, it is essential to understand that not all data is the same. All of the following are among the most common forms of data that organizations and their employees handle on a regular basis:

• Public: This is information in the public domain. Public information can be freely used and distributed without legal restrictions on its access or usage. A prime example is publicly disclosed information organizations can use for market research.
   
• Internal: Internal data is information that’s internal to an organization’s employees, contractors, communications, and operations, like memos, email messages, and corporate guidelines. If disclosed without authorization, it could cause at least moderate harm to the company. As a result, it has low-security requirements.
• Confidential/Restricted: This is sensitive information like government-classified data or patient health information that requires legal restriction and needs to be handled with utmost care. This is because it has reputational, even national security implications if it falls into the wrong hands.

• Sensitive: These are of utmost concern to an organization and include protected health information (PHI) and intellectual property.
• Confidential: The data category here is a notch lower than sensitive, although still confidential because it contains internal company workings like employee reviews and supply chain information such as vendor contracts.
• Private: This is mainly personal information that may or may not be protected by law, such as sensitive or non-sensitive personally identifiable information (PII).
• Proprietary: These are business secrets, organizational processes, and company proprietary information that gives a business a competitive advantage.

Types of Data Classification

There are several ways to classify the various types of data listed above. However, the most common and obvious include, but are not limited to the following:

• Context-based: This classification is based on the context of data, typically utilizing the following attributes:
  • The author or creator of the data.
  • The location where the data is stored, created, or modified.
  • The use case and application of the data, like whether it’s used for finance, insurance, or healthcare.
• Content-based: This categorization isn’t based on context but on the content of the data. Therefore, it is necessary to determine whether a file or document contains personal, sensitive, or confidential information.
• User-based: This utilizes the user’s knowledge and discretion to flag what they perceive as sensitive content or data for classification. 

Why Is Data Classification Important?

Data classification is one of the main prerequisites of data security. This is because you can only effectively prioritize data security after you’ve been able to identify and organize data based on its privacy and relative importance to a business’s competitive advantage. 

Data classification is more than essential with unstructured data. Data classification is also necessary for companies to maintain the integrity of data.

Without data classification, organizations can’t achieve common compliance standards of regulatory bodies like GDPR, HIPAA, and SOC 2. For instance, data classification makes it feasible for organizations to fulfill the GDPR requirement of providing individuals with the right to access, modify, or even delete their personal data. 

Here are the main purposes of data classification:

• Meeting governance and regulatory compliance: Data classification allows organizations to adhere to the substantial body of local and global data protection regulations.
• Know where sensitive data is stored and located: By pinpointing where your sensitive data resides, organizations can accomplish the following:
  • Gain clarity on who can assess, modify, and delete data.
  • Adjust data security controls that align with your priorities for data security.
  • Assess risk to your data based on prevailing threats, data protection levels, and the potential impact of such a breach on your business.
• Prioritize data security procedures: Data classification enables security teams to evaluate the data security measures to be adopted for each data category.
• Determine risk management strategies to apply: Data classification helps organizations align themselves with regulatory compliance processes, including legal discovery and risk mitigation features. 

The Benefits of Data Classification

Most of the benefits of data classification are interlinked and interwoven. Moreover, some of the benefits dovetail with the purpose of data classification listed previously.

• Data security: The overwhelming advantage of data classification is fortifying data security, especially when it drives downstream security solutions. Data classification solutions pair with and enhance other security solutions like data loss prevention (DLP), data rights management (DRM), and encryption to help organizations identify and protect valuable, sensitive data.
• Regulatory compliance: Data protection and privacy issues have spurred regulatory bodies like GDPR, PCI DSS, and HIPAA. Data classification lays the groundwork for effective compliance with current and future regulatory standards.
  
  Meeting these standards requires managing data governance policies through appropriate tagging to enable quarantining and other legal holds to implement data protection requirements.
• Boosts business goals: Data in the modern age represents a competitive advantage and is at the forefront of digital transformation. With data classification, an organization can establish a consistent model of labeling data. This, in turn, enhances efficiency and productivity by providing the appropriate storage and encryption mechanisms.
• Cost and efficiency optimization: Data classification reduces data storage and maintenance costs for organizations. Part of the reason is that it allows businesses to apply data normalization techniques to identify and remove duplication and redundancies. 

What is the data classification process?

The data classification process involves analyzing data, both structured and unstructured, using relevant values, criteria, and subgroups to label them accordingly. This involves several activities, like tagging with the right classification labels to assign them relevant file types and pertinent metadata. 

These are the general steps to classify data elements effectively: 

1. Set up a clear policy to guide data classification. This ensures the process isn’t done in an ad hoc manner. Part of this includes following the earlier exercise of identifying and defining the main purpose of an organization’s data classification exercise.
2. Discover the scope of data, including the data environment. This also involves identifying where all relevant data is stored.
3. Tag the data appropriately by applying relevant labels. This tagging adds metadata to files, which imprints them with the classification results for easier identification.
4. It’s best not to exceed three or four classification levels to avoid introducing undue complexity or ambiguity.
5. Data classification is a dynamic, ongoing, iterative process. So, use automated systems to streamline the process by removing tedious manual steps.

How Fortra’s Vera Can Help You Organize and Secure Your Data

Fortra’s Vera, working in conjunction with our data classification software, Fortra’s Titus, provides both top-notch data classification and end-to-end security. While our classification tools provide you with the ability to organize both structured and unstructured data by applying appropriate identification attributes, Vera’s digital rights management wraps data with granular controls allowing you to manage how the data is accessed, modified, and shared, even after it’s left your corporate network.

To learn more, explore our definitive guide to data security today.