What to Consider When Choosing Data Classification Software
Data classification has become a cornerstone of modern digital security strategies. As data volumes continue to grow, manual classification is no longer feasible. This is where data classification software comes into play.
But with dozens of options available, what should you look for when choosing the right solution?
1. Automated Classification Capabilities
A good data classification tool should automatically analyze content and assign the appropriate classification quickly and accurately. Critical features include:
- Keyword and pattern recognition (e.g., Regex, credit card numbers, national ID numbers)
- Natural Language Processing (NLP) for contextual analysis
- Suggested labeling based on file content
2. Compliance and Regulatory Integration
The software should support labeling structures that align with regulations such as GDPR, KVKK, and ISO 27001. For example:
- “Personal Data”
- “Health Information”
- “Financial Data”
- “Corporate Confidential”
These classification levels should also be customizable according to the organization’s own data governance policies.
3. Integration with DLP and Other Security Systems
The solution must integrate seamlessly with Data Loss Prevention (DLP) systems, email servers, and cloud platforms (e.g., Google Workspace, Microsoft 365).
Example:
If a file is classified as “Confidential”, the DLP solution should be able to block its transfer via USB or email.
4. Reporting and Visualization
Organizations should be able to periodically monitor how data is classified and used.
- Distribution reports by label
- Who is using which classification the most
- Misclassification events and corrections
This enables continuous measurement and improvement of data security posture.
5. User-Friendly Interface and Easy Adoption
- Simple, intuitive user interface
- Integrated buttons in familiar apps like Outlook and Word
- Minimal IT support required for onboarding
- Feedback mechanisms (e.g., mislabeling alerts)
6. Performance and Security
Data classification software should:
- Not slow down the system
- Minimize resource usage
- Avoid delays in critical processes (e.g., file saving, email sending)
- Ensure data privacy through centralized logging and encryption
7. Local Development & National Trust – The Veriket Example
Veriket is the first locally developed, nationally trusted data classification solution in Turkey.
- High accuracy in Turkish content analysis
- Full KVKK compliance
- Support for Windows, Linux, macOS
- Microsoft Outlook and Office add-ins
- Google Workspace and Zimbra integrations
- MSSP infrastructure support
Thanks to its high performance, flexible rule engine, and seamless DLP integration, Veriket is an ideal solution for regulation-bound organizations.
Conclusion: Choose the Right Tool for Your Needs
When selecting a data classification solution, avoid generic tools. Choose a secure and flexible platform that aligns with your organization’s size, industry, and regulatory requirements.
Frequently Asked Questions
Should the software be cloud-based or on-premises?
A hybrid model is ideal: critical data stays on-prem, while low-risk data can be processed in the cloud.
Can users bypass classification?
No, not with a proper tool. For example, saving a file or sending an email can be blocked until a classification label is applied.
Should all departments use the same classification rules?
No. You can (and should) define department-specific data policies for more accurate and relevant classification.
