What is Data Loss Prevention? And Why You Need It

UPDATE: This post, originally published on March 29, 2024, has been updated to reflect the most recent information about the critical role data loss prevention plays in safeguarding sensitive data across various environments with detailed explanations tailored for both technical professionals and leadership.

Data loss prevention (DLP) is a set of best practices, policies, tools, and rules that aim to protect sensitive data while it’s static, moving, and actively being processed by continuously monitoring data and enforcing security policies.

As organizations digitally transform, data flows far and wide—into containers, virtual machines, laptops, mobile devices, hybrid cloud servers, and desktops. The chances are high that at least some of that sensitive information or critical data will end up somewhere you didn’t anticipate.

In this blog, we’ll explore the basics of DLP, including its definition and some of the most common causes of data loss.

Additionally, we’ve grouped relevant subtopics to address two primary stakeholders: more technical explanations for security professionals, managers, and IT staff around how data loss prevention works, different types of DLP, and best practices for implementing DLP, then we’ll dig deeper to provide business leaders, CISOs, and decision makers what they need to know about DLP, including the benefits, how to measure the potential ROI of DLP solutions, and a real-world example of how mastering DLP can transform your organization’s information security efforts and give you peace of mind as environments continue becoming increasingly connected.

The basics:

• What is data loss prevention? – We’ll provide an overview of DLP, explaining its purpose, key components, and how it helps protect sensitive data from unauthorized access and breaches.
• Common causes of data loss – We’ll explore the various reasons why data loss occurs to help both technical professionals and business leaders understand the risks and the importance of taking preventive measures.

For technical professionals:

• How does data loss prevention work? – We’ll explain the fundamentals and technical mechanisms behind DLP.
• What are the 3 types of DLP solutions? – We’ll help you understand the different DLP approaches and technologies available and provide insights into the growing use of AI.
• Best practices for implementing a DLP strategy in your organization – We leverage our experiences supporting organizations across various industries and scenarios to provide practical advice and strategies for those looking to implement DLP effectively.

What business leaders need to know:

• What are the benefits of data loss prevention? – We’ll highlight the advantages to help you see the value of investing in DLP.
• ROI and cost-benefit analysis of implementing DLP solutions – We’ll examine the financial and economic benefits of using DLP solutions.
• How Tanium empowers organizations to safeguard data and prevent security incidents – We’ll summarize a customer case study to provide a concrete example of how Tanium successfully enables more effective DLP strategies, showcasing real-world results and the impact on security and data protection.

Final takeaway:

• Why enhanced endpoint control unlocks stronger data loss prevention – We’ll discuss how better endpoint management and security can greatly improve data loss prevention.

What is data loss prevention?

Data loss prevention, also referred to as data leakage prevention, is a proactive approach used to ensure data security across various environments, including on-premises systems, endpoint devices, and cloud storage and repositories, by protecting data in use, in motion, or at rest from unauthorized access, disclosure, or misuse.

For example, cloud migration can rapidly expand the number of locations where data resides, outpacing your ability to keep track of it. Additionally, legacy assets may be overlooked and abandoned, resulting in security vulnerabilities. Mass remote working and hybrid RTO policies have also added a whole new fleet of potentially unmanaged endpoints to the mix. These are just a few of the challenges organizations encounter daily, which helps underscore the urgent need for data loss prevention to be a fundamental component of any modern data security strategy.

By prioritizing DLP, organizations can achieve regulatory compliance with critical regulations, such as privacy laws like GDPR and CCPA, cybersecurity frameworks like NIST, and healthcare standards like HIPAA. In the healthcare sector, effective DLP is particularly crucial as it ensures the protection of sensitive patient information, including personally identifiable information (PII) and personal health information (PHI).
 

Operationalizing the NIST Cybersecurity Framework 2.0
with Tanium

Auditing capabilities and reporting mechanisms further enhance the effectiveness of DLP by providing insights into data access and misuse, ensuring that enterprises can proactively address security risks and implement effective remediation actions to maintain operational resilience by preventing data breaches, exfiltration, and accidental exposure.

With this understanding of what data loss prevention entails, it’s important to recognize some of the most common causes of data loss that organizations face today. By digging deeper into the broader context of what can lead or contribute to these common causes, organizations can more easily take proactive measures to prevent data breaches and ensure data security.

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Common causes of data loss

While outsider threats are often cited as a leading cause of data loss, not all breaches are caused by external actors. Data leaks can occur due to various reasons, such as:

Cyberattacks

Hackers may exploit vulnerabilities in your organization’s network, devices, or applications or target users through attacks like phishing and ransomware to gain unauthorized access, allowing them to exfiltrate, encrypt, or erase data. Cyberattacks aiming to cause data loss often involve malware that can steal personal data, including credit card numbers.

[Read also: Learn about the 3 biggest GenAI threats today—and how to fend them off]

Hardware failure and software corruption

Malfunctions or crashes of storage devices, such as hard drives, can result in data loss. Hardware failure is often unpredictable and can lead to significant data loss if proper backups are not in place. Bugs or glitches in software can also corrupt data, making it inaccessible or unusable. Software failures can occur for various reasons, including compatibility issues, updates, or inherent flaws in the software.

[Read also: What is IT asset lifecycle management? Why visibility matters]

Human mistakes

When employees accidentally delete, overwrite, misplace, or send critical information to the wrong recipient, they may inadvertently still cause unintentional exposure through these mistakes. While these actions are not made intentionally like malicious insiders, these negligent or accidental insider threats are equally dangerous.

Insider threats

Insider threats pose a significant risk to organizations. Malicious insiders can steal, sabotage, or expose confidential data for personal gain or revenge. These individuals often have legitimate access and permissions that allow them to access sensitive information, making their actions difficult to detect and prevent.

Migration errors

Migration errors can be a significant source of data loss while moving data between different systems, platforms, or storage solutions. These errors can occur due to mismatched data formats, incomplete transfers, or even software incompatibilities. Ensuring meticulous planning and execution during data migration is essential to prevent such costly mistakes and safeguard valuable data.

Natural disasters

Fire, flood, earthquake, or power outage may damage your physical storage devices or servers. In addition to immediate physical damage, natural disasters can trigger secondary effects, such as prolonged power outages, data corruption, or inaccessibility, further exacerbating data loss and severely impacting business continuity and operations.

[Listen to the podcast: Why it pays to take data privacy seriously with guest Safia Kazi, a privacy professional practice adviser at ISACA]

Organizations clearly face numerous challenges in safeguarding their sensitive information. This leads us to the critical question: How does DLP help prevent these and other causes of data loss?

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How does data loss prevention work?

To achieve more effective data loss prevention, a robust DLP program should help organizations address these main use cases:

• Identification: DLP can classify your data according to its sensitivity, location, or owner and assign appropriate security policies and controls. This involves using advanced data discovery and classification tools to scan and categorize data across various environments, including on-premises, cloud, and hybrid infrastructures.
  
  Solutions that support DLP can accurately identify sensitive information such as PII, financial data, and intellectual property (IP) by leveraging machine learning algorithms and pattern recognition techniques. Unified visibility and comprehensive protection for all endpoints ensure that sensitive data is accurately identified and classified.
• Monitoring: DLP can track and audit your data activity, such as who accesses, modifies, or transfers your data, and can help you detect any anomalies, violations, and potential access control issues. Continuously monitoring data flows and user behavior is crucial for identifying suspicious activities and possible threats in real time. This includes tracking endpoints, network traffic, and cloud services to ensure comprehensive visibility and control over data movements.
  
  Accurate, real-time data is essential for making risk-based decisions. Leveraging solutions that integrate with key infrastructure like security information and event management (SIEM) systems can provide a holistic view of data activity and enhance threat detection capabilities.
• Prevention: DLP can help you enforce your security policies and controls, such as encryption, authentication, authorization, or blocking to prevent unauthorized users or other risky data actions. Implementing preventive measures like data encryption, multi-factor authentication, and role-based access controls ensures that only authorized personnel can access and manipulate sensitive data. Additionally, automatically blocking or quarantining data transfers that violate predefined security policies can significantly reduce the risk of data breaches and unauthorized access.
  
  Secure access management and eliminating standing access are key to effective preventive measures. Solutions that support content inspection and contextual analysis can prevent data exfiltration through various channels, such as email, web uploads, and removable media.
• Response: In case of a critical data loss incident, DLP can alert and notify stakeholders, such as IT and security teams, and take corrective incident response actions, such as quarantining, isolating, recovering, and using pattern matching to quickly delete infected files. Effective incident response involves automated workflows and predefined playbooks to ensure swift and coordinated actions. This includes notifying relevant stakeholders, containing the breach, and initiating recovery procedures to minimize the impact of data loss.
  
  Swift and coordinated incident response actions are crucial for minimizing the impact of data loss. An effective DLP strategy should include integration with incident response platforms to streamline the process and ensure timely remediation.

[Read also: Lean into autonomous incident response with Endpoint Reactions]

Now that we’ve identified the various threats to data security, it’s important to recognize that there’s no one-size-fits-all solution. Different organizations have unique needs and challenges, and there are multiple ways to achieve robust data protection. 

In the next section, we’ll dive into the three major types of DLP solutions. By understanding these options, you’ll be better equipped to choose the approach that best aligns with your organization’s specific requirements.

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What are the 3 types of DLP solutions?

To effectively safeguard sensitive information, organizations typically employ various DLP solutions tailored to address specific data security challenges that each offer unique capabilities to protect data in different environments.

These solutions can be broadly categorized into three main types:

1. Endpoint: This type of DLP controls data “in use,” including data stored or accessed on endpoint devices like laptops, desktops, smartphones, or tablets. Endpoint DLP can enforce encryption, deletion, or the quarantine of sensitive data and restrict the use of removable devices, such as USB drives or CDs, which can be used to introduce threats into or remove data from your environment. It can also prevent data loss via local storage, printing, copying, or offline transfer.
2. Network: This type of DLP monitors network traffic and filters or blocks data “in motion,” such as identifying data transfers that violate predefined policies or rules. Network DLP can be deployed at the network’s perimeter, such as firewalls or proxies, or within the network, such as switches or routers. It can prevent data loss via email, web, cloud, or FTP apps.
3. Cloud: This type of DLP secures data “at rest” or shared in the cloud, such as SaaS applications, cloud storage, cloud repositories, or cloud collaboration platforms. Cloud DLP can scan and classify the data in the cloud, apply consistent policies across different cloud services, and integrate with other security tools, such as cloud access security broker (CASB) or identity and access management (IAM) solutions. Cloud DLP can prevent data loss via cloud-based email messaging, file sharing, or social media.

Additionally, next-generation DLP tools are increasingly leveraging advanced technologies like AI and machine learning to detect suspicious data activity and enforce granular policies. These technologies enhance the ability to identify sensitive information, monitor data flows, and respond to potential threats.

[Read also: What is Agentic AI? What to know about this new AI type]

By integrating AI and machine learning, DLP solutions can analyze historical and real-time data patterns with greater precision, helping organizations stay ahead of evolving threats and maintain a strong security posture.

DLP innovations using AI and machine learning can provide context and risk prioritization around alerts and autonomously prevent and remediate incidents as they happen. By adopting modern DLP solutions that address these concerns and use cases, organizations can greatly reduce their risks and prevent costly data loss.¹

With the growing adoption of AI and machine learning, organizations are transforming their approach to both data loss prevention and cybersecurity. While these advanced technologies are revolutionizing how organizations protect digital assets, there’s a catch: AI and machine learning are only as powerful as the data they rely on.

Imagine navigating a city with an outdated map—no matter how advanced your navigation system is, it won’t lead you to your destination if the map is inaccurate. The same principle applies to AI and machine learning in cybersecurity; their success ultimately depends on the quality and timeliness of the data they process.

Without real-time visibility and up-to-date endpoint data, even the most sophisticated AI systems can’t effectively protect your organization. Real-time data empowers AI to detect, respond to, and mitigate threats as they happen. Anything less leaves your organization vulnerable. To stay ahead of potential threats and ensure robust data protection, you must ensure your organization is equipped with the most accurate, real-time data to truly harness the power of these technologies and safeguard your environment.

[Read also: How AI is redefining data loss prevention]

So, how do you leverage these technologies while ensuring real-time visibility and control over your data? In the following section, we’ll delve into what it takes to implement an effective DLP strategy, from enforcing preventative policies to ensuring robust protection of sensitive data that complies with regulatory requirements.

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Best practices for implementing a DLP strategy in your organization

A lot of noise is made about data loss prevention as a primary defense against data risk. While it’s important, DLP is not a silver bullet.

Data loss prevention programs won’t work if you don’t know what data you hold that needs protecting and where it is. Lack of visibility into where data comes from, where it’s saved, and where it’s going is a common reason why many DLP projects are unsuccessful.

Fortunately, you can quickly strengthen your data loss prevention strategies without reinventing the wheel, and it all starts with gaining visibility and control of your endpoints and the critical data residing on them.

Here are five practical approaches organizations can start leveraging today to help improve data loss prevention efforts:

1. Implement preventative policies
   
   Enforcing preventative policies like hard-disk encryption and backups is an essential but often overlooked best practice to incorporate into your DLP strategy. Common methods include:
   

   • Hard-disk encryption can help prevent data loss by protecting the data stored on your devices from unauthorized access, theft, or tampering. If someone tries to access your encrypted data without the correct password or key, they will not be able to read it or use it.
   
   Encryption can also deter hackers from targeting your devices or network. Hackers will have a harder time breaking into your system and stealing sensitive information. Most operating systems have built-in hard disk encryption functionality, so make sure to enable it.
   
   • Performing regular backups can help you recover quickly from data loss incidents, such as accidental deletion, ransomware attacks, hardware failures, or natural disasters. Backups can also help you comply with regulatory requirements and industry standards that mandate data retention and availability.
   
   Having multiple copies of your data stored in different locations can reduce the risk of losing critical information and ensure business continuity, highlighting one of the many positives of having a robust backup strategy.

2. Take a Zero-Trust approach
   
   Enterprise IT environments are increasingly complex, which extends to corporate network security. The traditional “castle and moat” model built around a secure perimeter is no longer appropriate in a dynamic, cloud-centric world of remote work, mobile devices, and the growing number of malicious actors.
   
   To ensure comprehensive information protection, organizations must assess the identity of each person logging in and the security posture of every endpoint device accessing data. For example, whether to grant full access or provide limited access in the form of VDI must be based on a comprehensive assessment of the endpoint.
   
   The key to this strategy is having insight into whether endpoints are up to date with patches, configured in accordance with policies, and set to block access to only certain types of data based on user access policies. This is the basis of Zero Trust, an increasingly popular, flexible approach built for the challenges of modern business interactions.
3. Proactively searching endpoints and data
   
   Since sensitive IP, regulated data, proprietary data, confidential information, and classified financial data often end up where you least expect them, there is an urgent need to be able to proactively search your endpoints for that data to ensure these locations adhere to data loss prevention policies.
   
   Once you know where sensitive data is, you can take action to transfer that data to a more secure environment or ensure its current location complies with policy. Given today’s complex IT environments, anything less will fail to provide the visibility you need.

 
What does this look like in practice? Watch this demo of a common real-world scenario where Tanium’s sensitive data monitoring capabilities are used to identify and remediate unapproved connections, locate sensitive data, and monitor file changes in real time.

You’ll learn how Tanium’s integration with solutions like ServiceNow can streamline workflows and ensure comprehensive risk management, helping you maintain continuous regulatory compliance and protect your organization’s valuable data.

4. Dynamically assigning controls to streamline global compliance
   
   There are scores of different data protection laws around the world. The most efficient way to deal with these requirements is to adopt the most restrictive regulatory framework and apply those controls and standards across regions, such as setting a geographic ring-fence of controls based on a particularly demanding regulation.
   
   Instead of manually identifying and creating lists of all applicable endpoints to apply and maintain related controls, try basing controls on key attributes like language and time zone settings, network segments, or Active Directory organizational units to dynamically manage compliance controls on endpoints more efficiently.
    

   [Read also: What is Active Directory security? Risks and best practices]

5. Baking privacy into new projects from the start
   
   Privacy-by-design is increasingly the mantra of regulators worldwide. So, whether you’re migrating to the cloud for the first time or designing a new system, service, or product, use the opportunity to think about data protection by asking these questions:

   • What data do you need to perform a given business function?
   • What are your data storage and retention requirements?
   • How are you searching for, identifying, and monitoring sensitive data to understand potential data loss risks better?

   Incorporating privacy and DLP policies from the start is often cheaper and more effective than retrofitting preventative measures for data protection, especially since most organizations will eventually need to comply with specific data regulatory requirements anyway.

A well-structured approach to data loss prevention is essential for safeguarding sensitive information. However, this is only one of many advantages that make DLP an indispensable tool for modern organizations. Let’s explore more of the benefits to better understand how DLP protects your data and enhances overall organizational security and efficiency.

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What are the benefits of data loss prevention?

In addition to helping protect sensitive data by detecting and preventing unauthorized access, transfer, or deletion of confidential information, data loss prevention can help address other common pain points related to improper data usage, such as:

• Better data classification and monitoring: Data loss prevention is crucial for organizations as it helps safeguard valuable and sensitive data from theft, leakage, or corruption.
  
  By implementing DLP, organizations can ensure they know where their sensitive data is located, automate data classification processes, and monitor data access and control. This comprehensive approach not only enhances data security but also streamlines the management of sensitive information, reducing the risk of data breaches and ensuring compliance with regulatory requirements.
• Reducing the risk of data breaches: Data loss prevention is essential for reducing the risk of data breaches. DLP can help prevent data leakage, theft, or data exfiltration by protecting against misuse by employees and external threat actors.
  
  By detecting and blocking suspicious activity, DLP measures enable organizations to reduce the likelihood and impact of data loss incidents. Implementing DLP not only enhances security posture but also strengthens resilience, ensuring that sensitive information remains protected from unauthorized access and potential threats.
• Improving compliance: Data loss can violate contractual obligations, industry standards, or regulatory compliance. Implementing DLP measures can help organizations comply with data protection regulations such as GDPR, HIPAA, or PCI DSS. These regulations mandate safeguarding certain types of data to avoid penalties or sanctions.
  
  By ensuring that sensitive information is protected, DLP helps organizations meet their legal and regulatory requirements, reducing the risk of noncompliance and associated consequences.
• Enhancing reputation: Data loss can significantly erode customer trust, loyalty, and satisfaction. Effective DLP can help demonstrate your commitment to data security and privacy.
  
  By safeguarding sensitive information, DLP helps build and maintain customer trust, loyalty, and satisfaction, ultimately enhancing your organization’s reputation.
• Increasing efficiency: Data loss can negatively impact productivity, efficiency, and the quality of service. DLP can help optimize data management and governance, reducing operational costs and risks.
  
  By improving visibility and control over sensitive information, DLP enhances overall efficiency and ensures that your organization can maintain high service and productivity standards.

[Read also: Huge fines are a wake-up call to prioritize data security]

While these advantages make a compelling case for adopting DLP strategies within any organization, understanding the benefits is just one part of the equation. To make a well-informed decision, it’s also essential to consider the financial implications.

In the next section, we’ll delve into the return on investment (ROI) and metrics to consider when conducting a cost-benefit analysis of implementing DLP solutions to provide a comprehensive view of how DLP not only safeguards your data but can also deliver significant economic value to your organization.

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ROI and the cost-benefit analysis of implementing DLP solutions

Investing in DLP is a transformative step for your organization’s data security efforts. With the right solutions, you create a robust framework that protects sensitive data, ensures compliance with ever-evolving regulations, and mitigates the risks associated with data breaches.

But what makes DLP truly invaluable?

The ROI of DLP solutions can be measured through five key factors that highlight their transformative impact on your organization:
 

1. Financial savings: DLP solutions help prevent data breaches, which can result in substantial economic losses due to fines, legal fees, and compensation claims. Organizations can avoid these costs and protect their revenue streams by safeguarding sensitive information.
2. Operational efficiency: Implementing DLP solutions streamlines data management processes, reducing the time and resources required to monitor and protect data. This efficiency translates into lower operational costs and improved productivity, allowing teams to focus on strategic initiatives rather than manual data protection tasks.
3. Regulatory compliance: DLP solutions ensure compliance with industry regulations such as GDPR, HIPAA, and PCI DSS. Maintaining compliance avoids costly fines and enhances the organization’s reputation and trustworthiness, which can lead to increased customer loyalty and business opportunities.
4. Risk mitigation: By proactively identifying and addressing vulnerabilities, DLP solutions reduce the risk of data breaches and insider threats. This risk mitigation is crucial for maintaining business continuity and protecting intellectual property and sensitive customer information.
5. Enhanced decision-making: Real-time visibility into data activities and potential threats empowers business leaders to make informed decisions about data security strategies. This proactive approach helps prioritize resources and investments, ensuring the organization remains resilient against evolving threats.

Investing in DLP is a strategic move that protects sensitive data and drives long-term business success and resilience. By considering these factors, organizations can conduct a comprehensive cost-benefit analysis and make informed decisions about implementing DLP solutions.

However, implementing a DLP strategy can be daunting, but with the right ally, it becomes a lot easier. That’s where Tanium can be your trusted partner in cybersecurity.

In the next section, we’ll show you how our cutting-edge platform enables organizations to provide unparalleled protection for sensitive information and safeguard data with unmatched security and comprehensive management capabilities.

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How Tanium empowers organizations to safeguard data and prevent security incidents

Tanium’s Risk & Compliance solution takes your security to the next level by helping operations and security teams streamline risk assessment and remediation processes using a centralized platform. With real-time endpoint data, this powerful solution empowers you to make informed decisions, ensuring comprehensive risk management and maintaining up-to-date compliance across your IT infrastructure.

We recently empowered Grand Mental Health, a nonprofit organization that provides mental health services, which was facing significant challenges in protecting sensitive patient data and ensuring compliance with stringent healthcare regulations. By implementing Tanium’s Deploy and Comply modules, which are included in Tanium’s Risk & Compliance solution, the organization gained real-time visibility into its entire IT environment, allowing it to identify and remediate vulnerabilities swiftly.

Read the Grand Mental Health case study

Tanium’s centralized platform also enabled Grand Mental Health to enforce granular policies and controls, preventing data loss and ensuring up-to-date compliance across its infrastructure. This proactive approach enhanced their data security posture and streamlined their risk assessment and remediation processes, ultimately leading to a more secure and compliant healthcare environment.

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Why enhanced endpoint control unlocks stronger data loss prevention

Complexity is the enemy of data protection, and there’s plenty of it in the modern enterprise IT environment.

It can create critical data visibility gaps that could leave an entire organization dangerously vulnerable and noncompliant.

The truth is that as long as humans are involved, things may not go as planned. Data may find its way to places you don’t want, as users often unintentionally circumvent security controls.

What does this mean? Wherever data ends up, you must ensure it’s protected.

To improve data visibility and security, you need a solution that can monitor and protect your data and swiftly and effectively take endpoint actions to mitigate any risks. You need a solution leveraging the latest technologies to identify and respond to threats across your network. You need a solution that integrates with your existing business processes, systems, and workflows to provide actionable insights and recommendations. You need Tanium.

Additional resources about data loss prevention and privacy:

• Drilling down on data privacy: 5 key charts from ISACA’s 2025 report
• What Latanya Sweeney knows about data privacy will trouble you
• 5 steps to securing your organization’s ‘crown jewels’ of data
• What is data privacy management?
• 7 ways to minimize data risk and enhance privacy compliance

Learn more about how Tanium can help:

• 10 ways Tanium improves data risk and privacy
• eBook: Managing risk in the age of data privacy regulation
• eBook: The key to regulatory compliance and sensitive data asset security is integration
• Tanium use case: Know when sensitive data appears on a managed computer
• Sensitive data monitoring: 10 ways Tanium makes it accurate, comprehensive, and lightweight

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With our latest innovation around Autonomous Endpoint Management (AEM), you can more easily harness the power of composite AI, which is designed to leverage machine learning and other AI techniques for better cybersecurity, to identify and prioritize anomalies and threats, streamline your data security and risk management processes, and automate endpoint actions to remediate issues and incidents in minutes, not days.

Tanium provides the leading platform that empowers you to manage and secure your endpoints from a single console by gaining real-time visibility into your data and devices, regardless of where they’re located or how they’re connected.

Additionally, Tanium’s close integration with Microsoft and ServiceNow enhances data loss prevention capabilities by combining Tanium’s real-time analysis with Microsoft Security Copilot and Tanium’s Integrated Risk Management (IRM) for ServiceNow to allow organizations to achieve 100% asset visibility, reduce risk, and improve overall compliance. These integrations also enable seamless cooperation between IT and security teams, creating new opportunities for automation while streamlining patching and threat elimination.

Don’t let your data fall into the wrong hands—protect it with Tanium. Request a demo today and see how Tanium can transform your endpoint security and data protection.