Data classification is especially important when it comes to risk management, regulatory compliance, and overall data security. In this article, we’ll cover what data classification is, its importance, and how solutions such as WinZip® Enterprise enable data security through data classification.
Categorizing data risk
Classifying data does more than make data easier to find. Companies produce large volumes of data and understanding what kinds of sensitive information your organization holds is essential to optimizing security efforts.
The average organization’s data volume grows approximately 63% per month, which requires an organized framework to drive adequate data protection measures. Some data is more sensitive and important than others, so data classification helps you identify which data sets require higher levels of protection. For example, your organization’s internal emails and documents require greater protection than your public website content.
There are four common types of data classification levels. These levels are based on the type of data, its sensitivity, and the risk to your company if the data is compromised.
Public data. Public data is considered low risk because it can be freely disclosed without negative consequences if it is accessed or used by people outside the organization. For example, general information about your organization or its products and services is considered public data.
Private data. Private data should be safeguarded from public access to maintain its integrity. This information is typically for internal use only, which poses some risk if disclosed. Your company’s plans, strategies, spreadsheets, and revenue projections are all examples of private internal data.
Confidential data. Data that requires clearance or authorization to access is confidential. This type of information could negatively impact the company if it is disclosed, so it is typically limited in access to specific teams or individuals. Examples of confidential data include financial accounts, pricing information, and marketing strategies.
Restricted data. Restricted data is extremely sensitive and requires strict controls to prevent unauthorized access. If disclosed, restricted data could pose a large risk for your organization because it includes data such as personally identifiable information (PII), protected health information (PHI), payment card industry (PCI) information, intellectual property, and information protected by confidentiality agreements.
Why data classification is important
Data classification is a foundational component of your company’s overall data security. It is what enables you to make knowledgeable decisions regarding how to protect information from both external and internal threats.
It is impossible to deploy all your security resources to protect every piece of data. By grouping data sets into one of the four classification levels, you are better able to identify the range of controls needed to keep it safe.
For example, highly sensitive data (e.g., restricted, confidential) requires a significant amount of your resources to keep it safe. Otherwise, it could pose severe risks to your organization if it is exfiltrated or accessed by unauthorized users.
Risk management is how businesses identify, assess, and control factors that could threaten their capital and earnings. An important element of a risk management program is establishing full visibility over all the data a company collects, stores, and transmits.
Most enterprise-level organizations deal with a high volume of multiple types of data. Data classification helps you provide the right level of protection based on the data’s value, sensitivity, and the risk posed to the organization if that data is lost, stolen, or exposed.
Companies that leverage data classification are better positioned to protect organizational assets. Each data classification category includes information relevant to risk management, such as security considerations for the safe retrieval, transmission, and storage of data.
According to Gartner, modern privacy regulations will cover the personal information of 65% of the world’s population by 2023. This makes it more important than ever to ensure the integrity, security, and availability of your organizational data.
To date, around 80 counties have enacted data privacy laws. Even the United States is moving closer to establishing a national standard for data protection—a draft of the American Data Privacy and Protection Act (ADPPA) was released by a bipartisan committee in June 2022. For now, Americans’ data is protected through a patchwork of state-and sector-specific laws.
Data classification ensures that sensitive, regulated data stays in compliance with all applicable rules, regulations, and privacy laws. Some of these common compliance provisions include the following:
Health Insurance Portability and Accountability Act (HIPAA). HIPPA imposes strict requirements for data privacy and security for healthcare related entities. You must properly locate and tag HIPAA-related data, such as PHI and PII. Since the Privacy Rule limits the uses and disclosures of PHI, data classification plays a key role prioritizing data security controls.
Payment Card Industry Data Security Standard (PCI DSS). PCI DSS places great importance on data classification for the protection of cardholder data. In fact, PCI DSS Requirement 9.6.1 specifically requires organizations to classify media so that the sensitivity of the data is determined.
Systems and Organizations Controls 2 (SOC 2). The SOC 2 framework helps companies demonstrate the security controls in place to protect cloud-based customer data. Data classification is an important component of the Confidentiality category of a SOC 2 report.
General Data Protection Regulation (GDPR). To comply with GDPR, organizations that handle the personal data of EU citizens must classify all the data they collect. Data classification also streamlines the process of creating a Data Protection Impact Assessment (DPIA), which is required for all high-risk data processing activities that could negatively impact people’s personal information.
Gramm-Leach-Bliley Act (GLBA). The GLBA Safeguards Rule requires financial institutions to adopt controls that address and enhance data classification. These controls are part of the larger, more detailed requirements for a company’s information security program.
Comprehensive Data Security
You cannot protect data if you don’t know which type of data and information your company has, where it is stored, or the controls required to protect it. This is why data classification is critical to your overall data security strategy. Instead of a one-size-fits-all approach to security measures, data classification informs which areas need additional risk controls.
For example, restricted data is the most sensitive data classification level. As such, it requires the highest level of control over how users’ access, share, and interact with this data. This is why many enterprises encrypt their sensitive data, which renders information inaccessible without the correct encryption key.
While confidential data is less sensitive than restricted data, it still needs a high level of protective control. It’s also important to control access and sharing of confidential data, even within your organization. A data classification system makes it easy to apply the appropriate access controls and restrictions based on data sensitivity.
To protect their most sensitive data, companies leverage WinZip Enterprise. This comprehensive solution makes it easy to encrypt, compress, back up, and share critical data.
Depending on the data classification level, you can keep information safe with file encryption or convert files to PDFs and protect them with a password. WinZip Enterprise is also highly customizable, giving your IT teams the ability to set and enforce encryption standards, password policies, access controls, and more.