Data Loss Prevention Buyers’ Guide 2025

State of the market: Data Loss Prevention (DLP) solutions protect sensitive data against loss, leaks, and misuse, by detecting unsafe or inappropriate access and transfer. In doing so, they help prevent intellectual and financial damage. In fact, using data security and protection software can reduce the cost of a data breachby a massive USD 166,600 (from a global average of USD 4.88 million).

• The global DLP market was valued at USD 2.4 billion in 2024, and is expected to grow at a CAGR of 19.6% to reach USD 7 billion by 2030.
• Growth is being driven by three key factors: increasing data security concerns, an ever-changing regulatory landscape, and digital expansion.
  • The cost of a data breach is rising year on year, and breaches that involve the loss of sensitive data such as employee PII, customer PII, or intellectual property are the most costly of all. As cyberthreats increase in both number and sophistication, organizations are realizing the need to secure their most sensitive data against external and internal threats. 
  • As the regulatory landscape becomes increasingly complex, organizations are turning to DLP tools to help them avoid non-compliance penalties and legal repercussions as well as protect their data.
  • As organizations transition to the cloud and expand digitally, they produce more data and distribute that data across numerous cloud services, applications, and devices outside the office perimeter. This makes it difficult for IT teams to keep track of where their sensitive data is stored and how it’s used—something a DLP tool can provide visibility into. 

---

Why trust us: We’ve researched, demoed, and tested several leading data loss prevention solutions, spoken to organizations of all sizes about their data protection challenges and the features that are most useful to them, and interviewed executives from leading providers in the DLP space.

You can find our product reviews, interviews, and Top 10 guides to the best DLP products on the market in our Data Loss Prevention Hub.

---

Our recommendations: Before we jump into the details, here are our top tips on how to get the most out of your DLP implementation:

• For easier implementation: Before you start comparing DLP tools, identify your needs and scope. Determine what data you need to protect (e.g., financial records, PII, intellectual property) and whether there are any specific regulatory requirements you need to adhere to. Knowing this beforehand will make it much easier for you to define DLP policies later (e.g., who can access, transfer, or modify data).
• For straightforward setup: Choose a DLP tool that integrates seamlessly with your existing tech stack.
• For ease of management: Most DLP tools come with pre-built templates for pattern matching and user behavior analytics—use these! They’ll help you get the tool up and running more quickly and will work effectively from the get-go.
• For happy end users: Your end users may be frustrated with your DLP tool if it stops them from being able to use or share data in the ways that they’re used to. Use role-based access controls (RBAC) to minimize disruptions to productivity, and educate your end users on the effects and purpose of the tool so they understand the importance of embracing a new—safer—way of working.

---

How DLP solutions work: There are four types of DLP solution, and your deployment method will likely depend on which of type of DLP tool you want to implement:

1. Network DLP monitors and protects data in transit across your network. These tools are typically gateway-based; you deploy DLP appliances or virtual machines at the network perimeter. 
2. Endpoint DLP protects data at rest and in use on workstations, laptops, and USB devices. These tools are typically agent-based; you install endpoint agents on users’ devices. 
3. Cloud DLP protects data in cloud applications and storage, such as Microsoft 365 and Google Workspace. These tools are typically cloud-based and use API integrations or proxies to integrate with SaaS applications.
4. Email and Web DLP prevents data exfiltration via email and web applications. These tools can be agent- or cloud-based.

Once you’ve deployed your DLP solution, it uses pattern matching and fingerprinting to inspect your data, then applies machine learning to classify your data (e.g., public, internal, confidential, or restricted). You create data protection policies based on data classification, user roles, and permissible actions.

With this information, the DLP tool uses contextual analysis—examining metadata, user behavior, and file locations—to identify any risk to sensitive data, such as a user trying to share financial records with someone outside the organization. 

If it identifies such a risk, the solution takes action to mitigate that risk and protect the data in line with the policies you defined. Potential mitigation actions include: 

• Automatically blocking unauthorized or unsafe actions or alerting you to them so you can block them manually.
• Enforcing encryption for secure transmission.
• Redacting sensitive information before transmission. 
• Sending users “just-in-time” warnings to educate them before they violate a policy and prevent them from doing so.

---

Benefits of DLP: There are three main benefits to implementing a data loss prevention solution:

1. Protect your intellectual property and sensitive data against leaks.
   • DLP solutions detect and prevent unauthorized access to or transfers of sensitive data, and they block exfiltration via email, USB drives, cloud uploads, and unauthorized applications—including GenAI apps.
   • This reduces the risk of data leaks—whether unintentional or malicious.
   • “Across about 8,000 [GenAI] applications that we looked at, about 30% of them explicitly train on the data that’s put in,” Alastair Paterson, CEO and Co-Founder at Harmonic Security, told Expert Insights. “So, if you’ve got critical IP about your new product releases, figures that aren’t released to the market yet, customer data, or anything else that’s critical to the business and it goes into someone else’s model, the risk is that it then becomes accessible to others using that same model over time.”
2. Gain better visibility into where your sensitive data is and how it’s being used.  
   • If you don’t know where your data is, you can’t protect it.
   • DLP tools continuously scan, classify, and monitor your sensitive data, tracking how it’s access, shared, and moved across endpoints, networks, and cloud environments in real-time. 
   • This level of visibility is incredibly difficult to achieve manually, particularly for organizations with remote users or multiple office locations, those using cloud services, and those with a diverse device fleet.
   • “Data is getting increasingly dispersed, which means there are multiple different entry points into customers’ data,” Alistair Mackenzie, CEO at Predatar, told Expert Insights. “And, with increasing collaboration and partnerships between companies, that data is being moved inside and outside of the traditional borders. All of this presents opportunities for theft and loss.”
3. Achieve compliance with data protection regulations.
   • By identifying, classifying, and securing sensitive data such as PII and financial records, DLP tools can help you achieve compliance with data protection standards such as GDPR, HIPAA, CCPA, and PCI-DSS.
   • DLP tools also enable you to define policies in line with regulatory requirements, update those policies as requirements change, and generate reports for compliance audits. 

---

Common DLP challenges: There are three main challenges that you might come across when implementing a DLP solution. Here’s what they are and how to overcome them:

1. It can be tricky to determine which data to classify as sensitive, business critical, PII, etc. We recommend finding a DLP tool that automatically classifies sensitive data for you, without manual intervention. Then, all you have to do is create the policies for protecting those categories. Most DLP tools will guide you through the policy configuration process, making this step easier for you.
2. To balance productivity with security, you need to make sure end users can access or share data as required, whilst upholding security policies. To minimize friction for your end users, we recommend implementing granular, role-based data access controls. Some platforms also offer a “just-in-time” approach to DLP, where users can request approval from an admin when they need to access or transfer sensitive data as a one-off. This can help minimize false positives, but it requires you to always have someone available to grant or deny requests.
3. Track data movement and storage across cloud repositories, cloud storage services, and on-prem servers can be complex. To streamline this, we recommend choosing a solution that offers comprehensive coverage across all platforms where your organization stores or processes data. You should also make sure the solution monitors data transfer, storage, access, and use in real time so that you can address any issues as quickly as possible.
4. Your team may struggle to keep on top of alerts. To reduce the number of alerts you receive and minimize false positives, make sure you frequently review your policies to ensure they’re relevant to the roles within your business and any compliance standards you must adhere to. You may also wish to choose a solution that offers a more educational, “hands-off” approach.
   • “[At Harmonic] we can sit in line with the employees and nudge them towards a safe way of getting their job done, instead of blocking them,” says Alastair Paterson of Harmonic Security. “It’s great from an employee’s perspective because it means they’re not getting blocked all the time; they can get on with their job unless they’re putting the company at risk. From a security team’s perspective, we’re calling it ‘zero touch data protection’ because it’s so lightweight on the security team.”

---

Best DLP providers: Our team of software analysts and researchers have put together a shortlist of the best providers of data loss prevention solutions, as well as adjacent lists covering similar topics:

• The Top 11 Data Loss Prevention Software
• The Top 11 User And Entity Behavior Analytics (UEBA) Solutions
• The Top 6 Insider Threat Detection Solutions
• The Top 10 Endpoint Encryption Solutions
• The Top 7 File Encryption Solutions
• The Top 7 Outbound Email Security Solutions
• The Top 9 Business Continuity And Disaster Recovery (BCDR) Solutions

---

Features checklist: When comparing DLP solutions, Expert Insights recommends looking for the following features:

1. Content scanning: The solution should use pattern matching, fingerprinting, and machine learning to automatically identify sensitive data.
2. Data classification: The solution should categorize sensitive data across your networks, endpoints, and cloud environments, based on the type of data it is and who should be able to access/use/share it.
3. Context-based analysis: The solution should assess metadata, user behavior (i.e., their historical and current interactions with data), and file locations to determine the risk posed to your sensitive data and detect threats based on changes to these.
4. Policy enforcement and incident response: The solution should provide workflows for investigating and mitigating security incidents. It should automatically block, quarantine, encrypt, mask, or redact data based on your pre-defined security policies.
5. Real-time monitoring and alerts: The solution should instantly notify you of any potential data breaches or policy violations, including notes on whether the DLP was able to automatically mitigate the risk and whether any action is needed from your team.
6. Comprehensive coverage: The solution should monitor and protect data across endpoints, USB drives, printers, clipboards, local storage, email, web, and cloud applications, and cloud storage.
7. Compliance reporting and auditing: You should be able to generate reports to meet regulatory requirements.
8. Integrations with existing security tools: The solution should integrate easily with your SIEM, IAM, and EDR tools for un-siloed, streamlined protection.  
9. Role based access: You should be able to configure role-based access controls to ensure only authorized users can modify or view sensitive data policies.
10. Scalability: The solution should be able to support large-scale deployments and scale as your organization produces more data, without impacting system performance.

---

Future Trends: Over the next five years, we can expect the DLP landscape to evolve significantly due to advancements in AI, cloud security, and regulatory requirements.  

As we see further developments in AI and machine learning, DLP providers will continue to embrace AI to improve their behavioral analytics capabilities. This will reduce false positives and enable more accurate detection of insider threats.

As cloud adoption grows, we’ll likely see more cloud-native DLP solutions emerging, which integrate seamlessly with SaaS, IaaS, and hybrid environments. We may also see some DLP providers converging their solutions with CASBs to provide more granular control over cloud data.

Finally, evolving data protection regulations (such as updated GDPR rule, the AI act, and evolving US state privacy laws) will drive the need for DLP tools to provide automated compliance management. We may also see more DLP tools introducing data sovereignty controls to help organizations manage cross-border data transfers.

---

Further Reading: You can find all our articles on DLP in our Data Loss Prevention Hub.

Want to jump straight in? Here are a few articles we think you’ll enjoy: 

• Shortlist: The Top 11 Data Loss Prevention Software
• Interview: Alastair Paterson On How Organizations Can Embrace GenAI Without Compromising Security
• Interview: Alistair Mackenzie On Combating Data Loss In A Digital World
• Blog: How To Backup Office 365 Data

---