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GDPR Compliance Failures Lead to Surge in Fines

October 9, 2025
4
Min Read
Compliance

In recent years, the landscape of data privacy and protection has become increasingly stringent, with regulators around the world cracking down on companies that fail to comply with local and international standards.

The latest high-profile case involves TikTok, which was recently fined a staggering €530 million ($600 million) by the Irish Data Protection Commission (DPC) for violations related to the General Data Protection Regulation (GDPR). This is a wake up call for multinational companies.

Graph showing the rise of GDPR fines from 2018-2025

What is GDPR?

The General Data Protection Regulation (GDPR) is a data protection law that came into effect in the EU in May 2018. Its goal is to give individuals more control over their personal data and unify data protection rules across the EU.

GDPR gives extra protection to special categories of sensitive data. Both 'controllers' (who decide how data is processed) and 'processors' (who act on their behalf) must comply. Joint controllers may share responsibility when multiple entities manage data.

Who Does the GDPR Apply To?

GDPR applies to both EU-based and non-EU organizations that handle the data of EU residents. The regulation requires organizations to obtain clear consent for data collection and processing, and it gives individuals rights to access, correct, and delete their data. Organizations must also ensure strong data security and report any data breaches promptly.

What Are Data Subject Access Requests (DSARs)?

One of the core rights granted to individuals under GDPR is the ability to understand and control how their personal data is used. This is made possible through Data Subject Access Requests (DSARs).

A DSAR allows any EU resident to request access to the personal data an organization holds about them. In response, the organization must provide a comprehensive overview, including:

  • What personal data is being processed
  • The purpose of processing
  • Data sources and recipients
  • Retention periods
  • Information about automated decision-making

Organizations are required to respond to DSARs within one month, making them a time-sensitive and resource-intensive obligation, especially for companies with complex data environments.

What Are the Penalties for Non-Compliance with GDPR?

Non-compliance with the General Data Protection Regulation (GDPR) can result in substantial penalties.

Article 83 of the GDPR establishes the fine framework, which includes the following:

Maximum Fine: The maximum fine for GDPR non-compliance can reach up to 20 million euros, or 4% of the company’s total global turnover from the preceding fiscal year, whichever is higher.

Alternative Penalty: In certain cases, the fine may be set at 10 million euros or 2% of the annual global revenue, as outlined in Article 83(4).

Additionally, individual EU member states have the authority to impose their own penalties for breaches not specifically addressed by Article 83, as permitted by the GDPR’s flexibility clause.

So far, the maximum fine given under GDPR was to Meta in 2023, which was fined $1.3 billion for violating GDPR laws related to data transfers. We’ll delve into the details of that case shortly.

Can Individuals Be Fined for GDPR Breaches?

While fines are typically imposed on organizations, individuals can be fined under certain circumstances. For example, if a person is self-employed and processes personal data as part of their business activities, they could be held responsible for a GDPR breach. However, UK-GDPR and EU-GDPR do not apply to data processing carried out by individuals for personal or household activities. 

According to GDPR Chapter 1, Article 4, “any natural or legal person, public authority, agency, or body” can be held accountable for non-compliance. This means that GDPR regulations do not distinguish significantly between individuals and corporations when it comes to breaches.

Specific scenarios where individuals within organizations may be fined include:

  • Obstructing a GDPR compliance investigation.
  • Providing false information to the ICO or DPA.
  • Destroying or falsifying evidence or information.
  • Obstructing official warrants related to GDPR or privacy laws.
  • Unlawfully obtaining personal data without the data controller's permission.

The Top 3 GDPR Fines and Their Impact

1.  Meta - €1.2 Billion ($1.3 Billion), 2023 

In May 2023, Meta, the U.S. tech giant, was hit with a staggering $1.3 billion fine by an Irish court for violating GDPR regulations concerning data transfers between the E.U. and the U.S. This massive penalty came after the E.U.-U.S. Privacy Shield Framework, which previously provided legal cover for such transfers, was invalidated in 2020. The court found that the framework failed to offer sufficient protection for EU citizens against government surveillance. This fine now stands as the largest ever under GDPR, surpassing Amazon’s 2021 record.

2. Amazon - €746 million ($781 million), 2021

Which leads us to Amazon at number 2, not bad. In 2021, Amazon Europe received the second-largest GDPR fine to date from Luxembourg’s National Commission for Data Protection (CNPD). The fine was imposed after it was determined that the online retailer was storing advertisement cookies without obtaining proper consent from its users.

3. TikTok – €530 million ($600 million), 2025

The Irish Data Protection Commission (DPC) fined TikTok for failing to protect user data from unlawful access and for violating GDPR rules on international data transfers in May 2025. The investigation found that TikTok allowed EU users’ personal data to be accessed from China without ensuring adequate safeguards, breaching GDPR’s requirements for cross-border data protection and transparency. The DPC also cited shortcomings in how TikTok informed users about where their data was processed and who could access it. The case reinforced regulators’ focus on international data transfers and children’s privacy on social media platforms.

The Implications for Global Companies

The growing frequency of such fines sends a clear message to global companies: compliance with data protection regulations is non-negotiable. As European regulators continue to enforce GDPR rigorously, companies that fail to implement adequate data protection measures risk facing severe financial penalties and reputational harm.

In the case of Uber, the company’s failure to use appropriate mechanisms for data transfers, such as Standard Contractual Clauses, led to significant repercussions. This situation emphasizes the importance of staying current with regulatory changes, such as the introduction of the E.U.-U.S. Data Privacy Framework, and ensuring that all data transfer practices are fully compliant.

How Sentra Helps Organizations Stay Compliant with GDPR

Sentra helps organizations maintain GDPR compliance by effectively tagging data belonging to European citizens.

When EU citizens' Personally Identifiable Information (PII) is moved or stored outside of EU data centers, Sentra will detect and alert you in near real-time. Our continuous monitoring and scanning capabilities ensure that any data violations are identified and flagged promptly.

Example of EU citizens PII stored outside of EU data centers

Unlike traditional methods where data replication can obscure visibility and lead to issues during audits, Sentra provides ongoing visibility into data storage. This proactive approach significantly reduces the risk by alerting you to potential compliance issues as they arise.

Sentra does automatic classification of localized data - specifically in this case, EU data. Below you can see an example of how we do this. 

Sentra's automatic classification of localized data

The Rise of Compliance Violations: A Wake-up Call

The increasing number of compliance violations and the related hefty fines should serve as a wake-up call for companies worldwide. As the regulatory environment becomes more complex, it is crucial for organizations to prioritize data protection and privacy. By doing so, they can avoid costly penalties and maintain the trust of their customers and stakeholders.

Solutions such as Sentra provide a cost-effective means to ensure sensitive data always has the right posture and security controls - no matter where the data travels - and can alert on exceptions that require rapid remediation. In this way, organizations can remain regulatory compliant, avoid the steep penalties for violations, and ensure the proper, secure use of data throughout their ecosystem.

To learn more about how Sentra's Data Security Platform can help you stay compliant, avoid GDPR penalties, and ensure the proper, secure use of data, request a demo today.

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Meni is an experienced product manager and the former founder of Pixibots (A mobile applications studio). In the past 15 years, he gained expertise in various industries such as: e-commerce, cloud management, dev-tools, mobile games, and more. He is passionate about delivering high quality technical products, that are intuitive and easy to use.

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Nikki Ralston
Nikki Ralston
January 19, 2026
3
Min Read

One Platform to Secure All Data: Moving from Data Discovery to Full Data Access Governance

One Platform to Secure All Data: Moving from Data Discovery to Full Data Access Governance

The cloud has changed how organizations approach data security and compliance. Security leaders have mostly figured out where their sensitive data is, thanks to data security posture management (DSPM) tools. But that's just the beginning. Who can access your data? What are they doing with it?

Workloads and sensitive assets now move across multi-cloud, hybrid, and SaaS environments, increasing the need for control over access and use. Regulators, boards, and customers expect more than just awareness. They want real proof that you are governing access, lowering risk, and keeping cloud data secure. The next priority is here: shifting from just knowing what data you have to actually governing access to it. Sentra provides a unified platform designed for this shift.

Why Discovery Alone Falls Short in the Cloud Era

DSPM solutions make it possible to locate, classify, and monitor sensitive data almost anywhere, from databases to SaaS apps. This visibility is valuable, particularly as organizations manage more data than ever. Over half of enterprises have trouble mapping their full data environment, and 85% experienced a data loss event in the past year.

But simply seeing your data won’t do the job. DSPM can point out risks, like unencrypted data or exposed repositories, but it usually can’t control access or enforce policies in real time. Cloud environments change too quickly for static snapshots and scheduled reviews. Effective security means not only seeing your data but actively controlling who can reach it and what they can do.

Data Access Governance: The New Frontier for Cloud Data Security

Data Access Governance (DAG) covers processes and tools that constantly monitor, control, and audit who can access your data, how, and when, wherever it lives in the cloud.

Why does DAG matter so much now? Consider some urgent needs:

  • Compliance and Auditability: 82% of organizations rank compliance as their top cloud concern. Data access controls and real-time audit logs make it possible to demonstrate compliance with GDPR, HIPAA, and other data laws.
  • Risk Reduction: Cloud environments change constantly, so outdated access policies quickly become a problem. DAG enforces least-privilege access, supports just-in-time permissions, and lets teams quickly respond to risky activity.
  • AI and New Threats: As generative AI becomes more common, concerns about misuse and unsupervised data access are growing. Forty percent of organizations now see AI as a data leak risk.

DAG gives organizations a current view of “who has access to my data right now?” for both employees and AI agents, and allows immediate changes if permissions or risks shift.

The Power of a Unified, Agentless Platform for DSPM and DAG

Why should security teams look for a unified platform instead of another narrow tool? Most large companies use several clouds, with 83% managing more than one, but only 34% have unified compliance. Legacy tools focused on discovery or single clouds aren’t enough.

Sentra’s agentless, multi-cloud solution meets these needs directly. With nothing extra to install or maintain, Sentra provides:

  • Automated discovery and classification of data in AWS, Azure, GCP, and SaaS
  • Real-time mapping and management of every access, from users to services and APIs
  • Policy-as-code for dynamic enforcement of least-privilege access
  • Built-in detection and response that moves beyond basic rules

This approach combines data discovery with ongoing access management, helping organizations save time and money. It bridges the gaps between security, compliance, and DevOps teams. GlobalNewswire projects the global market for unified data governance will exceed $15B by 2032. Companies are looking for platforms that can keep things simple and scale with growth.

Strategic Benefits: From Reduced Risk to Business Enablement

What do organizations actually achieve with cloud-native, end-to-end data access governance?

  • Operational Efficiency: Replace slow, manual reviews and separate tools. Automate access reviews, policy enforcement, and compliance, all in one platform.
  • Faster Remediation and Lower TCO: Real-time alerts pinpoint threats faster, and automation speeds up response and reduces resource needs.
  • Future-Proof Security: Designed to handle multi-cloud and AI demands, with just-in-time access, zero standing privilege, and fast threat response.
  • Business Enablement and Audit Readiness: Central visibility and governance help teams prepare for audits faster, gain customer trust, and safely launch digital products.

In short, a unified platform for DSPM and DAG is more than a tech upgrade, it gives security teams the ability to directly support business growth and agility.

Why Sentra: The Converged Platform for Modern Data Security

Sentra covers every angle: agentless discovery, continuous access control, ongoing threat detection, and compliance, all within one platform. Sentra unites DSPM, DAG, and Data Detection & Response (DDR) in a single solution.

With Sentra, you can:

  • Stop relying on periodic reviews and move to real-time governance
  • See and manage data across all cloud and SaaS services
  • Make compliance easier while improving security and saving money

Conclusion

Data discovery is just the first step to securing cloud data. For compliance, resilience, and agility, organizations need to go beyond simply finding data and actually managing who can use it. DSPM isn’t enough anymore, full Data Access Governance is now a must.

Sentra’s agentless platform gives security and compliance teams a way to find, control, and protect sensitive cloud data, with full oversight along the way. Make the switch now and turn cloud data security into an asset for your business.

Looking to bring all your cloud data security and access control together? Request a Sentra demo to see how it works, or watch a 5-minute product demo for more on how Sentra helps organizations move from discovery to full data governance.

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Gilad Golani
Gilad Golani
January 18, 2026
3
Min Read

False Positives Are Killing Your DSPM Program: How to Measure Classification Accuracy

False Positives Are Killing Your DSPM Program: How to Measure Classification Accuracy

As more organizations move sensitive data to the cloud, Data Security Posture Management (DSPM) has become a critical security investment. But as DSPM adoption grows, a big problem is emerging: security teams are overwhelmed by false positives that create too much noise and not enough useful insight. If your security program is flooded with unnecessary alerts, you end up with more risk, not less.

Most enterprises say their existing data discovery and classification solutions fall short, primarily because they misclassify data. False positives waste valuable analyst time and deteriorate trust in your security operation. Security leaders need to understand what high-quality data classification accuracy really is, why relying only on regex fails, and how to use objective metrics like precision and recall to assess potential tools. Here’s a look at what matters most for accuracy in DSPM.

What Does Good Data Classification Accuracy Look Like?

To make real progress with data classification accuracy, you first need to know how to measure it. Two key metrics - precision and recall - are at the core of reliable classification. Precision tells you the share of correct positive results among everything identified as positive, while recall shows the percentage of actual sensitive items that get caught. You want both metrics to be high. Your DSPM solution should identify sensitive data, such as PII or PCI, without generating excessive false or misclassified results.

The F1-score adds another perspective, blending precision and recall for a single number that reflects both discovery and accuracy. On the ground, these metrics mean fewer false alerts, quicker responses, and teams that spend their time fixing problems rather than chasing noise. "Good" data classification produces consistent, actionable results, even as your cloud data grows and changes.

The Hidden Cost of Regex-Only Data Discovery

A lot of older DSPM tools still depend on regular expressions (regex) to classify data in both structured and unstructured systems. Regex works for certain fixed patterns, but it struggles with the diverse, changing data types common in today’s cloud and SaaS environments. Regex can't always recognize if a string that “looks” like a personal identifier is actually just a random bit of data. This results in security teams buried by alerts they don’t need, leading to alert fatigue.

Far from helping, regex-heavy approaches waste resources and make it easier for serious risks to slip through. As privacy regulations become more demanding and the average breach hit $4.4 million according to the annual "Cost of a Data Breach Report" by IBM and the Ponemon Institute, ignoring precision and recall is becoming increasingly costly.

How to Objectively Test DSPM Accuracy in Your POC

If your current DSPM produces more noise than value, a better method starts with clear testing. A meaningful proof-of-value (POV) process uses labeled data and a confusion matrix to calculate true positives, false positives, and false negatives. Don’t rely on vendor promises. Always test their claims with data from your real environment. Ask hard questions: How does the platform classify unstructured data? How much alert noise can you expect? Can it keep accuracy high even when scanning huge volumes across SaaS, multi-cloud, and on-prem systems? The best DSPM tool cuts through the clutter, surfacing only what matters.

Sentra Delivers Highest Accuracy with Small Language Models and Context

Sentra’s DSPM platform raises the bar by going beyond regex, using purpose-built small language models (SLMs) and advanced natural language processing (NLP) for context-driven data classification at scale. Customers and analysts consistently report that Sentra achieves over the highest classification accuracy for PII and PCI, with very few false positives.

Gartner Review - Sentra received 5 stars

How does Sentra get these results without data ever leaving your environment? The platform combines multi-cloud discovery, agentless install, and deep contextual awareness - scanning extensive environments and accurately discerning real risks from background noise. Whether working with unstructured cloud data, ever-changing SaaS content, or traditional databases, Sentra keeps analysts focused on real issues and helps you stay compliant. Instead of fighting unnecessary alerts, your team sees clear results and can move faster with confidence.

Want to see Sentra DSPM in action? Schedule a Demo.

Reducing False Positives Produces Real Outcomes

Classification accuracy has a direct impact on whether your security is efficient or overwhelmed. With compliance rules tightening and threats growing, security teams cannot afford DSPM solutions that bury them in false positives. Regex-only tools no longer cut it - precision, recall, and truly reliable results should be standard.

Sentra’s SLM-powered, context-aware classification delivers the trustworthy performance businesses need, changing DSPM from just another alert engine to a real tool for reducing risk. Want to see the difference yourself? Put Sentra’s accuracy to the test in your own environment and finally move past false positive fatigue.

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Ward Balcerzak
Ward Balcerzak
January 14, 2026
4
Min Read

The Real Business Value of DSPM: Why True ROI Goes Beyond Cost Savings

The Real Business Value of DSPM: Why True ROI Goes Beyond Cost Savings

As enterprises scale cloud usage and adopt AI, the value of Data Security Posture Management (DSPM) is no longer just about checking a tool category box. It’s about protecting what matters most: sensitive data that fuels modern business and AI workflows.

Traditional content on DSPM often focuses on cost components and deployment considerations. That’s useful, but incomplete. To truly justify DSPM to executives and boards, security leaders need a holistic, outcome-focused view that ties data risk reduction to measurable business impact.

In this blog, we unpack the real, measurable benefits of DSPM, beyond just cost savings, and explain how modern DSPM strategies deliver rapid value far beyond what most legacy tools promise. 

1. Visibility Isn’t Enough - You Need Context

A common theme in DSPM discussions is that tools help you see where sensitive data lives. That’s important, but it’s only the first step. Real value comes from understanding context. Who can access the data, how it’s being used, and where risk exists in the wider security posture. Organizations that stop at discovery often struggle to prioritize risk and justify spend.

Modern DSPM solutions go further by:

  • Correlating data locations with access rights and usage patterns
  • Mapping sensitive data flows across cloud, SaaS, and hybrid environments
  • Detecting shadow data stores and unmanaged copies that silently increase exposure
  • Linking findings to business risk and compliance frameworks

This contextual intelligence drives better decisions and higher ROI because teams aren’t just counting sensitive data, they’re continuously governing it.

2. DSPM Saves Time and Shrinks Attack Surface Fast

One way DSPM delivers measurable business value is by streamlining functions that used to be manual, siloed, and slow:

  • Automated classification reduces manual tagging and human error
  • Continuous discovery eliminates periodic, snapshot-alone inventories
  • Policy enforcement reduces time spent reacting to audit requests

This translates into:

  • Faster compliance reporting
  • Shorter audit cycles
  • Rapid identification and remediation of critical risks

For security leaders, the speed of insight becomes a competitive advantage, especially in environments where data volumes grow daily and AI models can touch every corner of the enterprise.

3. Cost Benefits That Matter, but with Context

Lately I’m hearing many DSPM discussions break down cost components like scanning compute, licensing, operational expenses, and potential cloud savings. That’s a good start because DSPM can reduce cloud waste by identifying stale or redundant data, but it’s not the whole story.

 

Here’s where truly strategic DSPM differs:

Operational Efficiency

When DSPM tools automate discovery, classification, and risk scoring:

  • Teams spend less time on manual reports
  • Alert fatigue drops as noise is filtered
  • Engineers can focus on higher-value work

Breach Avoidance

Data breaches are expensive. According to industry studies, the average cost of a data breach runs into millions, far outweighing the cost of DSPM itself. A DSPM solution that prevents even one breach or major compliance failure pays for itself tenfold

Compliance as a Value Center

Rather than treating compliance as a cost center consider that:

  • DSPM reduces audit overhead
  • Provides automated evidence for frameworks like GDPR, HIPAA, PCI DSS
  • Improves confidence in reporting accuracy

That’s a measurable business benefit CFOs can appreciate and boards expect.

4. DSPM Reduces Risk Vector Multipliers Like AI

One benefit that’s often under-emphasized is how DSPM reduces risk vector multipliers, the factors that amplify risk exponentially beyond simple exposure counts.

In 2026 and beyond, AI systems are increasingly part of the risk profile. Modern DSPM help reduce the heightened risk from AI by:

  • Identifying where sensitive data intersects with AI training or inference pipelines
  • Governing how AI tools and assistants can access sensitive content
  • Providing risk context so teams can prevent data leakage into LLMs

This kind of data-centric, contextual, and continuous governance should be considered a requirement for secure AI adoption, no compromise.

5. Telling the DSPM ROI Story

The most convincing DSPM ROI stories aren’t spreadsheets, they’re narratives that align with business outcomes. The key to building a credible ROI case is connecting metrics, security impact, and business outcomes:

Metric Security Impact Business Outcome
Faster discovery & classification Fewer blind spots Reduced breach likelihood
Consistent governance enforcement Fewer compliance issues Lower audit cost
Contextual risk scoring Better prioritization Efficient resource allocation
AI governance Controlled AI exposure Safe innovation

By telling the story this way, security leaders can speak in terms the board and executives care about: risk reduction, compliance assurance, operational alignment, and controlled growth.

How to Evaluate DSPM for Real ROI

To capture tangible return, don’t evaluate DSPM solely on cost or feature checklists. Instead, test for:

1. Scalability Under Real Load

Can the tool discover and classify petabytes of data, including unstructured content, without degrading performance?

2. Accuracy That Holds Up

Poor classification undermines automation. True ROI requires consistent, top-performing accuracy rates.

3. Operational Cost Predictability

Beware of DSPM solutions that drive unexpected cloud expenses due to inefficient scanning or redundant data reads.

4. Integration With Enforcement Workflows

Visibility without action isn’t ROI. Your DSPM should feed DLP, IAM/CIEM, SIEM/SOAR, and compliance pipelines (ticketing, policy automation, alerts).

ROI Is a Journey, Not a Number

Costs matter, but value lives in context. DSPM is not just a cost center, it’s a force multiplier for secure cloud operations, AI readiness, compliance, and risk reduction. Instead of seeing DSPM as another tool, forward-looking teams view it as a fundamental decision support engine that changes how risk is measured, prioritized, and controlled.

Ready to See Real DSPM Value in Your Environment?

Download Sentra’s “DSPM Dirty Little Secrets” guide, a practical roadmap for evaluating DSPM with clarity, confidence, and production reality in mind.

👉 Download the DSPM Dirty Little Secrets guide now

Want a personalized walkthrough of how Sentra delivers measurable DSPM value?
👉 Request a demo

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