Data centric security
36Verified suppliers
Built for
The challenge
Your organization faces an uphill battle securing increasingly distributed data. Traditional perimeter-based security models are obsolete in the face of cloud computing, remote work, and shadow AI. This leaves your sensitive data vulnerable to breaches, compliance violations, and financial losses. You need a solution that protects the data itself, regardless of location or access method, providing persistent security and granular control to mitigate risks and maintain compliance.
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77-95%
of data breaches are caused by human error
279 days
average time to detect/contain a breach in healthcare
$10M
average cost of a data breach in the US
The solution
Data centric security addresses your unique challenges through modern solutions and key capabilities.
Automated sensitive data inventory
Discover data across IaaS, SaaS, PaaS, and on-premises environments without manual intervention, providing a comprehensive view of your data landscape.
Context-aware classification
Use machine learning to identify data type and context, differentiating between live customer data and test data to prioritize protection efforts.
Granular access governance
Enforce least privilege with field-level and column-level controls, limiting access to sensitive data based on user roles and responsibilities.
Encryption and tokenization
Render data unusable to unauthorized parties while maintaining its format for use in business applications, ensuring data is protected both in transit and at rest.
Data detection and response (DDR)
Monitor data behavior in real-time, identifying risky combinations and triggering automated remediation to prevent breaches.
Audit readiness and forensics
Continuously log data interactions for automated compliance reporting, simplifying audits and demonstrating adherence to regulations like GDPR and HIPAA.
See how data centric security suppliers stack up
Our Palomarr Insights chart shows the full landscape of data centric security solutions.
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How to evaluate data centric security
1
Deployment architecture (agentless vs. agent-based)
Prioritize agentless, API-first solutions that operate out-of-band to avoid impacting application performance and disrupting production environments.
2
Integration with the modern data stack
Ensure deep integration with analytical (Snowflake, Databricks) and operational (Salesforce, ServiceNow) platforms, as well as identity management and security operations tools.
3
Total cost of ownership (TCO)
Consider personnel costs, implementation services, and ongoing maintenance beyond licensing fees to accurately assess the overall investment.
4
Vendor stability and roadmap
Evaluate the vendor's long-term vision and investment in emerging technologies like AI governance and quantum-safe protocols.
Questions to ask suppliers
Use these questions during supplier evaluations to ensure you're choosing the right partner for your needs.
Data centric security RFP guide- What is the specific precision and recall rate for your classification engine on unstructured 'messy' data, and how is this validated?
- Can your solution protect data as it moves outside our environment to a third-party partner who does not use your software?
- What is the average 'Time-to-Value' for your enterprise customers, and what percentage of Year 1 budget should we reserve for professional services?
- How does your platform handle 'Shadow AI' usage, and can you prevent sensitive PII from being uploaded to public LLMs in real-time?