The Top 10 Data Classification Software Products of 2024

What are data classification products, and why do you need them?

Data classification products help organizations to identify, categorize, and protect sensitive information. These tools use advanced algorithms and machine learning (ML) to classify data based on its sensitivity and importance. By implementing data classification solutions, organizations can enhance their data security posture, ensure compliance with leading regulations, and reduce the risk of data breaches.

What are the benefits of data classification products?

Data classification products offer several benefits, including the following:

• Enhanced security: Protect sensitive information by identifying and classifying it, thereby making it easier to apply appropriate security measures. This includes Personally Identifiable Information (PII), Protected Health Information (PHI), and Payment Card Information (PCI), as well as secrets and Intellectual Property (IP).
• Regulatory compliance: Ensure compliance with various regulations, such as GDPR, HIPAA, and PCI-DSS. 
• Risk management: Mitigate risks associated with data loss, insider threats, and data breaches.‍
• Improved data management: Get better visibility into data usage to help manage data more efficiently across an organization.

What are the top data classification products of Summer 2024?

1. Nightfall AI

Nightfall AI is the comprehensive, AI-native data security platform that enables organizations to discover and protect sensitive data where end users work in the modern enterprise: across SaaS apps, GenAI apps, email providers, and endpoint devices. Whether you're looking to prevent secret sprawl, stop data exfiltration, or secure AI usage, Nightfall's industry-leading detection engine and flexible APIs cover a wide variety of use cases.

Powered by advanced AI and machine learning techniques, Nightfall's PII, PCI, PHI, secret, and IP detectors deliver greater accuracy than legacy DLP solutions, which are built on regular expressions (regexes) and heuristics. This increased accuracy means that security teams can respond to high-priority alerts across the SaaS ecosystem, and maintain continuous compliance with leading standards like HIPAA, PCI-DSS, SOC 2, and GDPR. 

Get a demo of Nightfall here.

Key features:

• AI-driven detection and classification
• Real-time data leak prevention, including comprehensive retrospective scanning for SaaS apps and inline scanning for emails
• Integrations with SaaS apps, GenAI apps, email, and endpoints
• Automated remediation for PII, PCI, PHI, secrets, and IP

2. Forcepoint

Forcepoint DLP offers data protection across various channels, including cloud, network, and endpoint channels. Customers might choose Forcepoint for its strong focus on user behavior analytics as well as its ability to provide context-aware security policies.

However, some users report that Forcepoint's DLP can have a steep learning curve and may require significant tuning to reduce false positives. The solution's pricing structure can also be complex, potentially leading to unexpected costs.

Key features:

• Advanced analytics and machine learning
• Comprehensive data visibility and control
• Detailed policy management
• Integrations with various data sources

3. Microsoft Purview

Microsoft Purview stands out as a robust DLP solution, offering comprehensive data protection across cloud, on-premises, and hybrid environments. Its integration with Microsoft 365 provides seamless coverage for SharePoint, OneDrive, and other Microsoft Office products. Purview's policy enforcement and automated response features also help maintain compliance with various regulations. However, some users find the initial setup complex, and may experience limitations in coverage and flexibility compared to other DLP solutions.

Key features:

• Integration with Microsoft 365 ecosystem
• Customizable sensitivity labels and policies
• Real-time data protection
• Compliance monitoring and reporting

4. Google Cloud DLP

Google Cloud DLP offers data loss prevention (DLP) capabilities as part of its broader cloud security platform. Customers might choose Google Cloud DLP over Microsoft Purview for its strong integration with Google Cloud services and its advanced ML-based content inspection.

However, Google Cloud DLP may be less suitable for organizations that are heavily invested in a SaaS ecosystem beyond the Google suite, or those looking for a more comprehensive and unified DLP experience.

Key features:

• Scalable data classification for Google Cloud
• Advanced content inspection and context-based analysis
• Integration with Google Cloud services
• Comprehensive reporting and compliance features

5. Symantec

Symantec DLP, now part of Broadcom, offers a comprehensive data protection solution across endpoints, networks, and cloud environments. Customers might choose Symantec DLP for its long-standing reputation in the security industry and its broad range of deployment options.

However, some users find Symantec DLP to be resource-intensive and complex to manage, especially in large, diverse environments. The solution may also require significant investment in other Broadcom security products to realize its full potential.

Key features:

• Machine learning-based data classification
• Endpoint, network, and cloud protection
• Granular policy controls
• Integration with various security tools

6. Varonis

Varonis specializes in data security and analytics with a focus on protecting sensitive information and detecting insider threats. Organizations may opt for Varonis due to its powerful capabilities in data classification, access monitoring, and behavioral analytics.

However, some users find Varonis to be costly and complex to deploy, especially for smaller organizations. Additionally, its extensive feature set can result in a steep learning curve and may require dedicated resources for optimal configuration and management.

Key features:

• Advanced data access analytics
• Insider threat detection
• Compliance monitoring
• Integrations with various data sources

7. Netskope

Netskope is favored for data security due to its robust cloud-native framework and seamless integration with cloud services like SaaS, IaaS, and web environments. It offers in-depth visibility and control over data, providing real-time threat protection and DLP. This helps organizations maintain compliance with regulatory standards while ensuring robust security against advanced threats.

However, Netskope has its drawbacks. Its complex and time-consuming deployment can be challenging for larger organizations. Performance issues, including bandwidth degradation, also impact user experience.

Key features:

• Cloud-native data classification
• Deep visibility into cloud applications
• Advanced threat protection
• Compliance and data loss prevention features

8. Palo Alto Networks

Palo Alto Networks (PANW) offers Enterprise DLP as part of its broader security platform. Customers might choose Palo Alto Networks for its comprehensive security ecosystem and strong network security heritage.

However, some users find that the full implementation of Palo Alto's DLP can be complex and resource-intensive. The solution may also be more suited to larger enterprises with substantial security budgets.

Key features:

• Advanced threat detection
• Real-time data protection
• Integration with various security tools
• Comprehensive policy management

9. Forta

Forta focuses on data security and governance with an emphasis on enhancing data visibility and control. Organizations might select Forta for its innovative approach to data classification, risk management, and compliance.

However, Forta may have a steep learning curve for new users, and its performance may be influenced by the scale and complexity of an organization's data environment. Some users also find that Forta's feature set may be more suited to larger organizations with extensive data management needs.

Key features:

• Scalable data classification
• Flexible data protection solutions
• Compliance and security features
• Integration with diverse platforms

10. Code42

Code42 is known for its strong focus on endpoint data protection and insider threat detection. It provides effective DLP and recovery features, making it suitable for organizations that are concerned about data breaches and accidental data loss. However, Code42's cloud and SaaS coverage is limited compared to other DLP solutions.

Key features:

• Insider threat detection
• Advanced data loss prevention
• Comprehensive data monitoring
• Integration with various security tools

What's the TL;DR on data classification?

Selecting the right data classification tool is crucial for protecting sensitive information and ensuring regulatory compliance. By choosing a tool that fits your organization’s needs, you can enhance your data security and manage sensitive information more effectively.

FAQs

What are data classification products, and why are they important?

Data classification products help organizations categorize sensitive information based on its level of sensitivity and importance. They are crucial for applying appropriate security measures, managing data efficiently, ensuring regulatory compliance, and reducing the risk of data breaches.

How can data classification products help with compliance?

Data classification tools assist with compliance by identifying and categorizing sensitive data, making it easier to apply the necessary controls and protections required by regulations like GDPR, HIPAA, and PCI-DSS. They work to ensure that data handling practices meet regulatory requirements and reduce the risk of noncompliance.

What are some key features to look for in a data classification software products?

When evaluating data classification products, consider features such as:

• Advanced algorithms for accurate data detection and classification
• Integration capabilities with existing platforms and applications
• Real-time protection for immediate data leak prevention
• Customizable policies to tailor data protection measures to specific needs
• Compliance support to aid in meeting regulatory requirements

How do data classification products enhance data leak prevention (DLP)?

Data classification products enhance DLP by identifying and categorizing sensitive information, allowing organizations to apply targeted security measures. This helps prevent unauthorized access, data breaches, and leaks by ensuring that sensitive data is properly protected and monitored.

What role does machine learning (ML) play in data classification?

Machine learning enhances data classification tools by improving their ability to detect and categorize data accurately. It allows these tools to adapt to new data patterns and threats, providing more effective protection and reducing the likelihood of false positives or missed detections.

Why should organizations consider while integrating data classification products with their existing systems?

Integrating data classification tools with existing systems ensures seamless data management and protection. It allows for real-time monitoring, automated data handling, and comprehensive security across various platforms, thereby enhancing overall data protection and compliance efforts.