Major uses of DLP
Protecting sensitive data
DLP helps identify, classify and protect sensitive data such as personally identifiable information (PII), intellectual property, customer records, etc.
IBM
+2
Fortinet
+2
It monitors data when it is in use (being accessed/edited), in motion (being transferred across networks), and at rest (stored).
Palo Alto Networks
+1
Preventing unauthorized or accidental data sharing/leakage
DLP enforces policies to block, quarantine or encrypt data when a user's action violates "allowed" data movement or sharing.
Microsoft
+2
Palo Alto Networks
+2
This is important for both malicious (insider threat, exfiltration) and accidental (employee mis-send, mis-upload) events.
IBM
+1
Supporting regulatory compliance & governance
Many regulations (e.g., GDPR, HIPAA, PCI DSS) require organizations to control and report on sensitive data use. DLP is a key technology for meeting those obligations.
Fortinet
+1
It also supports policy and audit trails: knowing "who accessed what data, when, from where" and "what data moved where".
Microsoft
Managing and securing cloud-based and hybrid environments
With data increasingly in cloud services (SaaS, IaaS) and hybrid infrastructures, DLP tools are used to extend protection beyond traditional on-premises networks.
Concentric AI
+1
Modern DLP must cover lots of new channels and usage contexts (remote work, collaboration tools, generative AI, etc.)
cyberhaven.com
+1
Reducing risk of data breach and exfiltration
Because data breaches remain costly (e.g., average global cost in recent years) organizations deploy DLP to reduce risk of leaks and exfiltration.
Palo Alto Networks
+1
DLP can provide visibility and controls to pre-empt data loss rather than simply reacting.
cyberhaven.com
Some emerging / evolving use-cases in 2025
Monitoring of generative AI / shadow AI: Companies are finding new risks where employees paste sensitive content into public AI tools. Modern DLP now needs to detect such flows.
Palo Alto Networks
+1
Data-lineage and movement tracking: Rather than just matching keywords, the most advanced DLP tools trace how data flows from origin to destination (e.g., from CRM → document → upload) to reduce false positives.
cyberhaven.com
Covering collaboration tools and non-traditional channels: DLP now must handle cloud apps, real-time chat, file sharing, endpoints, mobile, etc.
Top DLP solutions
Microsoft Purview Data Loss Prevention – Cloud/endpoint DLP integrated with Microsoft 365, OneDrive, Teams etc.
Centraleyes
+2
Seraphic Security
+2
Google Cloud DLP – Focused on data classification & de-identification in Google Cloud Platform environments.
Centraleyes
+1
Netskope DLP – Cloud-native DLP covering SaaS/IaaS/web traffic, good for cloud-first organisations.
Centraleyes
+1
Symantec Data Loss Prevention (by Broadcom) – Strong enterprise-grade solution with deep content inspection (endpoints, network, cloud).
cyberhaven.com
+1
Forcepoint DLP – Unified DLP across web/email/cloud and behavioral analytics for user risk.
Centraleyes
+1
Proofpoint Enterprise DLP – Emphasis on email/endpoint/cloud DLP with ML-driven content classification.
Proofpoint
+1
Endpoint Protector (by CoSoSys) – More focussed on endpoint & removable device control, good for hybrid environments.
zluri.com
+1
Digital Guardian DLP – Endpoint/Network DLP solution, often recommended for organisations with sensitive IP/data.
TechTarget
+1
Zscaler DLP – Unified DLP across web, endpoint, email; rated well in 2025 user reviews.
Info-Tech Research Group
+1
Safetica DLP – Good user-centric DLP, especially for insider risk & productivity-aware organisations