How to Evaluate a DSPM Platform

As sensitive data sprawls across cloud services, SaaS applications and on-premises systems, organizations confront a fundamental problem: they no longer know where all their sensitive data lives, who can access it or how exposed it is.

Data Security Posture Management (DSPM) platforms were created to solve this challenge. A DSPM solution discovers and classifies sensitive data, analyzes risk and helps organizations reduce exposure across modern environments.

But there are widely varying options for DSPM platforms on the market, and not all of them are likely to meet your organization’s needs. If you are responsible for data security, risk or compliance, knowing how to evaluate a DSPM platform is essential.

This guide walks through the most important criteria to consider when choosing the best DSPM platform and why these capabilities matter in real-world environments.

Start with Comprehensive Data Discovery

A DSPM platform is only as good as its ability to find data.

Look for solutions that provide:

• Broad discovery across structured and unstructured data
• Coverage for cloud, SaaS and on-premises repositories
• Support for databases, object storage, file shares and collaboration platforms

Incomplete discovery creates blind spots. Shadow data, forgotten backups and unmanaged storage locations often contain some of the highest-risk information.

Equally important is accuracy. Strong platforms use machine learning and context-aware analysis to distinguish true sensitive data from false positives. Accurate classification improves trust in the results and enables confident remediation.

Key questions to ask:

• Does the platform support predefined and custom classifiers?
• Can it identify regulated data such as personal data, health data and financial data?
• How does it validate accuracy and reduce noise?

Evaluate Classification Depth and Intelligence

Look “under the hood” to understand how each platform delivers its classification results. Pattern matching alone is no longer sufficient.

Modern DSPM platforms should:

• Analyze context, not just patterns
• Understand document structure and semantics
• Support multiple classification techniques working together

Advanced classification enables platforms to identify sensitive content embedded in documents, spreadsheets and free-form text.

This level of intelligence is essential for discovering business-critical data such as intellectual property, source code and proprietary research that does not fit simple regex patterns.

Look for Risk-Based Prioritization

Large environments may contain millions of sensitive files. A long list of findings is not helpful unless it is prioritized.

A strong DSPM platform should:

• Assign risk scores based on sensitivity, exposure and accessibility
• Highlight high-impact combinations such as sensitive data with public access
• Surface the most dangerous conditions first

Risk prioritization allows security teams to focus on issues that materially increase breach likelihood rather than chasing low-value findings.

Some platforms also incorporate usage context, identifying unusual access patterns or spikes in data activity around sensitive repositories. This additional context improves confidence when determining what truly matters.

Assess Remediation and Response Capabilities

Discovery without action does not reduce risk.

When evaluating DSPM platforms, examine how they support remediation:

• Guided remediation recommendations
• Automated remediation for common scenarios
• Workflow integration with ticketing or SOAR tools

Examples of valuable remediation actions include removing public access, tightening permissions and alerting data owners.

The most effective platforms close the loop by combining visibility with the ability to fix issues directly or trigger enforcement through integrated security controls.

Automation should be configurable. Organizations may start with human approval and progress toward automation as confidence grows.

Ensure Continuous Monitoring

Effective DSPM takes more than a one-time scan.

Data is constantly created, copied and moved. A platform should continuously monitor for:

• Newly created sensitive data
• Changes in permissions or exposure
• Movement of sensitive data between systems

Continuous monitoring ensures new risks are detected quickly rather than waiting for scheduled scans. This may be available as part of a DSPM product’s core functionality or as an add-on.

Some platforms also support data lineage, showing how sensitive data flows across systems. This capability helps identify risky pipelines and unintended replication.

Prioritize Ecosystem Integration

DSPM should complement your existing security stack, not replace it.

Look for platforms that integrate with other data security capabilities such as:

• Data Loss Prevention (DLP)
• Identity and Access Management (IAM)
• Security Information and Event Management (SIEM)

Integration enables DSPM findings to feed broader security workflows and enables other tools to enforce protections using DSPM context.

Increasingly, organizations prefer DSPM platforms that are part of a unified data security architecture rather than standalone point products. A unified approach simplifies operations and reduces policy fragmentation.

Validate Compliance and Governance Support

DSPM plays a critical role in regulatory compliance and internal governance.

Key capabilities include:

• Prebuilt classifiers for major regulations
• Compliance-oriented reporting
• Identification of redundant, obsolete and trivial data

A strong DSPM platform should answer questions such as:

• Where is all regulated data located?
• Who can access it?
• Is access appropriate?

These insights simplify audits and support ongoing governance programs.

Consider Scalability and Deployment Model

DSPM platforms must operate at enterprise scale.

Important factors include:

• Ability to scan very large environments efficiently
• Minimal performance impact
• Support for hybrid environments

Modern platforms often use multi-stage scanning techniques, starting with metadata analysis and escalating to deeper inspection only where risk is indicated.

Deployment flexibility also matters. Some organizations prefer SaaS-only models. Others require on-premises or private cloud processing for sensitive environments.

Why Forcepoint DSPM Meets these Requirements

Forcepoint DSPM is designed around the best-practice criteria outlined above.

It provides broad discovery across structured and unstructured data in cloud, SaaS and on-premises environments. Its classification engine is powered by Forcepoint AI Mes, which combines multiple specialized models to deliver high accuracy and reduce false positives.

Forcepoint DSPM uses a two-phase scanning approach that enables rapid visibility at scale while focusing deep inspection where risk is most likely. This design supports large environments without overwhelming infrastructure or cloud APIs.

Unlike many DSPM tools that focus only on visibility, Forcepoint DSPM includes built-in remediation workflows and features the Forcepoint Data Detection and Response (DDR) add-on for continuous monitoring. This allows organizations to move from finding risk to fixing risk without stitching together multiple products.

The Advantage of Forcepoint Data Security Cloud

Forcepoint DSPM is part of Forcepoint Data Security Cloud, a unified platform that brings together Forcepoint DSPM, DDR, Data Loss Prevention (DLP), Risk-Adaptive Protection and cloud and web security.

This unified approach delivers:

• Consistent policies across channels
• Centralized visibility into data risk
• Reduced operational complexity

Rather than managing multiple point tools, security teams can manage data protection through a single platform with shared intelligence and enforcement.

For organizations seeking to choose the best DSPM platform, alignment with a broader data security strategy is increasingly important. Forcepoint Data Security Cloud provides that foundation.

Final thoughts on choosing a DSPM platform

Choosing a DSPM platform is a strategic decision that directly affects an organization’s ability to protect sensitive data and meet regulatory obligations.

When evaluating options, focus on:

• Comprehensive discovery
• Intelligent classification
• Risk-based prioritization
• Actionable remediation
• Continuous monitoring
• Strong integration
• Enterprise scalability

Platforms that combine these capabilities with a unified data security architecture deliver the greatest long-term value.

By applying these criteria, organizations can confidently select a DSPM platform that reduces exposure, improves compliance and strengthens overall data security posture.