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How to Scale DSAR Compliance (Without Breaking Your Team)

April 21, 2025
Min Read
Compliance

Privacy regulations such as GDPR (EU), CCPA/CPRA (California), and others are not just about legal checkboxes, they’re about building trust. In today’s data-driven world, customers expect organizations to be transparent about how their personal information is collected, used, and protected. When companies take privacy seriously, they demonstrate respect for their users, which in turn fosters loyalty and long-term engagement.

But among the many privacy requirements, Data Subject Access Requests (DSARs) can be the most complex to support. DSARs give individuals the right to request access to the personal data that an organization holds about them—often with a firm deadline of just 30 days to respond. For large enterprises with data scattered across multiple systems, both in the cloud and on-premises, even a single request can trigger a chaotic search across different platforms, manual reviews and legal oversight—it quickly becomes a race against the clock, with compliance, trust, and reputation on the line.

Key Challenges in Responding to DSARs

Data Discovery & Inventory
For large organizations, pinpointing where personal data resides across a diverse ecosystem of information systems, including databases, SaaS applications, data lakes, and legacy environments, is a complex challenge. The presence of fragmented IT infrastructure and third-party platforms often leads to limited visibility, which not only slows down the DSAR response process but also increases the likelihood of missing or overlooking critical personal data.

Linking Identities Across Systems
A single individual may appear in multiple systems under different identifiers, especially if systems have been acquired or integrated over time. Accurately correlating these identities to compile a complete DSAR response requires sophisticated identity resolution and often manual effort.


Unstructured Data Handling
Unlike structured databases, where data is organized into labeled fields and can be efficiently queried, unstructured data (like PDFs, documents, and logs) is free-form and lacks consistent formatting. This makes it much harder to search, classify, or extract relevant personal information.

Response Timeliness
Regulatory deadlines force organizations to respond quickly, even when data must be gathered from multiple sources and reviewed by legal teams. Manual processes can lead to delays, risking non-compliance and fines.

Volume & Scalability
While most organizations can handle an occasional DSAR manually, spikes in request volume — driven by events like regulatory campaigns or publicized incidents — can overwhelm privacy and legal teams. Without scalable automation, organizations face mounting operational costs, missed deadlines, and an increased risk of inconsistent or incomplete responses.


The Role of Data Security Platforms in DSAR Automation

Sentra is a modern data security platform dedicated to helping organizations gain complete visibility and control over their sensitive data. By continuously scanning and classifying data across all environments (including cloud, SaaS, and on-premises systems) Sentra maintains an always up-to-date data map, giving organizations a clear understanding of where sensitive data resides, how it flows, and who has access to it. This data map forms the foundation for efficient DSAR automation, enabling Sentra’s DSAR module to search for user identifiers only in locations where relevant data actually exists - ensuring high accuracy, completeness, and fast response times.

Data Security Platform example of US SSN finding

Another key factor in managing DSAR requests is ensuring that sensitive customer PII doesn’t end up in unauthorized or unintended environments. When data is copied between systems or environments, it’s essential to apply tokenization or masking to prevent unintentional sprawl of PII. Sentra helps identify misplaced or duplicated sensitive data and alerts when it isn’t properly protected. This allows organizations to focus DSAR processing within authorized operational environments, significantly reducing both risk and response time.

Smart Search of Individual Data

To initiate the generation of a Data Subject Access Request (DSAR) report, users can submit one or more unique identifiers—such as email addresses, Social Security numbers, usernames, or other personal identifiers—corresponding to the individual in question. Sentra then performs a targeted scan across the organization’s data ecosystem, focusing on data stores known to contain personally identifiable information (PII). This includes production databases, data lakes, cloud storage services, file servers, and both structured and unstructured data sources.

Leveraging its advanced classification and correlation capabilities, Sentra identifies all relevant records associated with the provided identifiers. Once the scan is complete, it compiles a comprehensive DSAR report that consolidates all discovered personal data linked to the data subject that can be downloaded as a PDF for manual review or securely retrieved via Sentra’s API.

DSAR Requests

Establishing a DSAR Processing Pipeline

Large organizations that receive a high volume of DSAR (Data Subject Access Request) submissions typically implement a robust, end-to-end DSAR processing pipeline. This pipeline is often initiated through a self-service privacy portal, allowing individuals to easily submit requests for access or deletion of their personal data. Once a request is received, an automated or semi-automated workflow is triggered to handle the request efficiently and in compliance with regulatory timelines.

  1. Requester Identity Verification: Confirm the identity of the data subject to prevent unauthorized access (e.g., via email confirmation or secure login).

  2. Mapping Identifiers: Collect and map all known identifiers for the individual across systems (e.g., email, user ID, customer number).

  3. Environment-Wide Data Discovery (via Sentra): Use Sentra to search all relevant environments — cloud, SaaS, on-prem — for personal data tied to the individual. By using Sentra’s automated discovery and classification, Sentra can automatically identify where to search for.

  4. DSAR Report Generation (via Sentra): Compile a detailed report listing all personal data found and where it resides.

  5. Data Deletion & Verification: Remove or anonymize personal data as required, then rerun a search to verify deletion is complete.

  6. Final Response to Requester: Send a confirmation to the requester, outlining the actions taken and closing the request.

Sentra plays a key role in the DSAR pipeline by exposing a powerful API that enables automated, organization-wide searches for personal data. The search results can be programmatically used to trigger downstream actions like data deletion. After removal, the API can initiate a follow-up scan to verify that all data has been successfully deleted.

Benefits of DSAR Automation 

With privacy regulations constantly growing, and DSAR volumes continuing to rise, building an automated, scalable pipeline is no longer a luxury - it’s a necessity.


  • Automated and Cost-Efficient: Replaces costly, error-prone manual processes with a streamlined, automated approach.
  • High-Speed, High-Accuracy: Sentra leverages its knowledge of where PII resides to perform targeted searches across all environments and data types, delivering comprehensive reports in hours—not days.
  • Seamless Integration: A powerful API allows integration with workflow systems, enabling a fully automated, end-to-end DSAR experience for end users.

By using Sentra to intelligently locate PII across all environments, organizations can eliminate manual bottlenecks and accelerate response times. Sentra’s powerful API and deep data awareness make it possible to automate every step of the DSAR journey - from discovery to deletion - enabling privacy teams to operate at scale, reduce costs, and maintain compliance with confidence. 

Turning DSAR Compliance into a Scalable Advantage

As privacy expectations grow and regulatory pressure intensifies, DSARs are no longer just a checkbox. They are a reflection of how seriously an organization takes user trust. Manual, reactive processes simply can’t keep up with the scale and complexity of modern data environments.

By automating DSAR workflows with tools like Sentra, organizations can achieve faster response times, lower operational costs, and sustained compliance - while freeing up teams to focus on higher-value privacy initiatives.

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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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Ward Balcerzak
Ward Balcerzak
December 11, 2025
3
Min Read

US State Privacy Laws 2026: DSPM Compliance Requirements & What You Need to Know

US State Privacy Laws 2026: DSPM Compliance Requirements & What You Need to Know

By 2026, American data privacy will look very different as a wave of new state laws redefines what it means to protect sensitive information. Organizations face a regulatory maze: more than 20 states will soon require not only “reasonable security” but also Data Protection Impact Assessments (DPIAs), explicit limits on data collection, and, in some cases, detailed data inventories. These requirements are quickly becoming standard, and ignoring them simply isn’t an option. The risk of penalties and enforcement actions is climbing fast.

But through all these changes, one major question remains: How can any organization comply if it doesn’t even know where its most sensitive data is? Data Security Posture Management (DSPM) has become the solution, making data visibility and automation central for meeting ongoing compliance needs.

Mapping the New Wave of State Privacy Mandates

Several state privacy laws going into effect in 2025 and 2026 are raising the stakes for compliance. Kentucky, Indiana, and Rhode Island’s new laws, effective January 1, 2026, require both security measures and DPIAs for handling high-risk or sensitive data. Minnesota’s law stands out even more: it moves past earlier vague “reasonable” security language and mandates comprehensive data inventories.

Other key states include Minnesota, which explicitly requires data inventories, Maryland with strict data minimization rules, and Tennessee, which gives organizations an affirmative defense if they’ve adopted a NIST-aligned privacy program. These requirements mean organizations now need to track what data they collect, know exactly where it’s stored, and show evidence of compliance when asked. If your organization operates in more than one state, keeping up with this web of laws will soon become impossible without dedicated solutions (US consumer privacy laws 2025 update).

Why Data Visibility is Now Foundational to Compliance

To meet DPIA, minimization, and security safeguard rules, you need full visibility into where sensitive or regulated data lives - and how it moves across your environment. Recent privacy laws are moving closer to GDPR-like standards, with DPIAs required not only for biometric data but also for broad categories like targeted advertising and profiling. Minnesota leads with its clear requirement for full data inventories, setting the standard that you can’t prove compliance unless you understand your data (US cybersecurity and data privacy review and outlook 2025).

This shift puts DSPM front and center: you now need ongoing discovery and classification of your entire sensitive data footprint. Without a strong data foundation, organizations will find it hard to complete DPIAs, handle audits, or defend themselves in investigations.

Automation: The Only Viable Path for Assessment and Audit Readiness

State privacy rules are getting more complicated, and many enforcement authorities are shortening or removing 'right-to-cure' periods. That means manual compliance simply won’t keep up. Automation is now the only way to manage compliance as regulations tighten (5 trends to watch: 2025 US data privacy & cybersecurity).

With DSPM and automation, organizations get ongoing discovery, real-time data classification, and instant evidence collection - all required for fast DPIAs and responsive audits. For companies facing regulators or preparing for multi-state oversight, this means you already have the proof and documentation you need. Relying on spreadsheets or one-time assessments at this point only increases your risk.

Sentra: Your Strategic Bridge to Privacy Law Compliance

Sentra’s DSPM platform is built to tackle these expanding privacy law requirements. The agentless platform covers AWS, Azure, GCP, SaaS, and hybrid environments, removing both visibility gaps and the hassle found in older solutions (Sentra: DSPM for compliance use cases).

With continuous, automated discovery and data classification, you always know exactly where your sensitive data is, how it moves, and how it’s being protected. Sentra’s integrated Data Detection & Response (DDR) catches and fixes risks or policy violations early, closing gaps before regulators - or attackers - can take advantage (Sensitive data exposure insight). Combined with clear reporting and on-demand audit documentation, Sentra helps you meet new state privacy laws and stay audit-ready, even as your business or data needs change.

Conclusion

The arrival of new state privacy laws in 2025 and 2026 is changing how organizations must handle sensitive data. Security safeguards, DPIAs, minimization, and full inventories are now required - not just nice-to-have.

DSPM is now a compliance must-have. Without complete data visibility and automation, following the web of state rules isn’t difficult - it’s impossible. Sentra’s agentless, multi-cloud platform keeps your organization continuously informed, giving compliance, security, and privacy teams the control they need to keep up with new regulations.

Want to see how your organization stacks up for 2026 laws? Book a DSPM Compliance Readiness Assessment or check out Sentra’s automated DPIA tools today.

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David Stuart
David Stuart
Gilad Golani
Gilad Golani
December 4, 2025
3
Min Read

Zero Data Movement: The New Data Security Standard that Eliminates Egress Risk

Zero Data Movement: The New Data Security Standard that Eliminates Egress Risk

Cloud adoption and the explosion of data have boosted business agility, but they’ve also created new headaches for security teams. As companies move sensitive information into multi-cloud and hybrid environments, old security models start to break down. Shuffling data for scanning and classification adds risk, piles on regulatory complexity, and drives up operational costs.

Zero Data Movement (ZDM) offers a new architectural approach, reshaping how advanced Data Security Posture Management (DSPM) platforms provide visibility, protection, and compliance. This post breaks down what makes ZDM unique, why it matters for security-focused enterprises, and how Sentra provides an innovative agentless and scalable design that is genuinely a zero data movement DSPM .

Defining Zero Data Movement Architecture

Zero Data Movement (ZDM) sets a new standard in data security. The premise is straightforward: sensitive data should stay in its original environment for security analysis, monitoring, and enforcement. Older models require copying, exporting, or centralizing data to scan it, while ZDM ensures that all security actions happen directly where data resides.

ZDM removes egress risk -shrinking the attack surface and reducing regulatory issues. For organizations juggling large cloud deployments and tight data residency rules, ZDM isn’t just an improvement - it's essential. Groups like the Cloud Security Alliance and new privacy regulations are moving the industry toward designs that build in privacy and non-stop protection.

Risks of Data Movement: Compliance, Cost, and Egress Exposure

Every time data is copied, exported, or streamed out of its native environment, new risks arise. Data movement creates challenges such as:

  • Egress risk: Data at rest or in transit outside its original environment  increases risk of breach, especially as those environments may be less secure.
  • Compliance and regulatory exposure: Moving data across borders or different clouds can break geo-fencing and privacy controls, leading to potential violations and steep fines.
  • Loss of context and control: Scattered data makes it harder to monitor everything, leaving gaps in visibility.
  • Rising total cost of ownership (TCO): Scanning and classification can incur heavy cloud compute costs - so efficiency matters.  Exporting or storing data, especially shadow data, drives up storage, egress, and compliance costs as well.

As more businesses rely on data, moving it unnecessarily only increases the risk - especially with fast-changing cloud regulations.

Legacy and Competitor Gaps: Why Data Movement Still Happens

Not every security vendor practices true zero data movement, and the differences are notable. Products from Cyera, Securiti, or older platforms still require temporary data exporting or duplication for analysis. This might offer a quick setup, but it exposes users to egress risks, insider threats, and compliance gaps - problems that are worse in regulated fields.

Competitors like Cyera often rely on shortcuts that fall short of ZDM’s requirements. Securiti and similar providers depend on connectors, API snapshots, or central data lakes, each adding potential risks and spreading data further than necessary. With ZDM, security operations like monitoring and classification happen entirely locally, removing the need to trust external storage or aggregation. For more detail on how data movement drives up risk.

The Business Value of Zero Data Movement DSPM

Zero data movement DSPM changes the equation for businesses:

  • Designed for compliance: Data remains within controlled environments, shrinking audit requirements and reducing breach likelihood.
  • Lower TCO and better efficiency: Eliminates hidden expenses from extra storage, duplicate assets, and exporting to external platforms.
  • Regulatory clarity and privacy: Supports data sovereignty, cross-border rules, and new zero trust frameworks with an egress-free approach.

Sentra’s agentless, cloud-native DSPM provides these benefits by ensuring sensitive data is never moved or copied. And Sentra delivers these benefits at scale - across multi-petabyte enterprise environments - without the performance and cost tradeoffs others suffer from. Real scenarios show the results: financial firms keep audit trails without data ever leaving allowed regions. Healthcare providers safeguard PHI at its source. Global SaaS companies secure customer data at scale, cost-effectively while meeting regional rules.

Future-Proofing Data Security: ZDM as the New Standard

With data volumes expected to hit 181 zettabytes in 2025, older protection methods that rely on moving data can’t keep up. Zero data movement architecture meets today's security demands and supports zero trust, metadata-driven access, and privacy-first strategies for the future.

Companies wanting to avoid dead ends should pick solutions that offer unified discovery, classification and policy enforcement without egress risk. Sentra’s ZDM architecture makes this possible, allowing organizations to analyze and protect information where it lives, at cloud speed and scale.

Conclusion

Zero Data Movement is more than a technical detail - it's a new architectural standard for any organization serious about risk control, compliance, and efficiency. As data grows and regulations become stricter, the old habits of moving, copying, or centralizing sensitive data will no longer suffice.

Sentra stands out by delivering a zero data movement DSPMplatform that's agentless, real-time, and truly multicloud. For security leaders determined to cut egress risk, lower compliance spending, and get ahead in privacy, ZDM is the clear path forward.

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Charles Garlow
Charles Garlow
December 3, 2025
3
Min Read

Petabyte Scale is a Security Requirement (Not a Feature): The Hidden Cost of Inefficient DSPM

Petabyte Scale is a Security Requirement (Not a Feature): The Hidden Cost of Inefficient DSPM

As organizations scramble to secure their sprawling cloud environments and deploy AI, many are facing a stark realization: handling petabyte-scale data is now a basic security requirement. With sensitive information multiplying across multiple clouds, SaaS, and AI-driven platforms, security leaders can't treat true data security at scale as a simple add-on or upgrade.

At the same time, speeding up digital transformation means higher and less visible operational costs for handling this data surge. Older Data Security Posture Management (DSPM) tools, especially those boasting broad, indiscriminate scans as evidence of their scale, are saddling organizations with rising cloud bills, slowdowns, and dangerous gaps in visibility. The costs of securing petabyte-scale data are now economic and technical, demanding efficiency instead of just scale. Sentra solves this with a highly-efficient cloud-native design, delivering 10x lower cloud compute costs.

Why Petabyte Scale is a Security Requirement

Data environments have exploded in both size and complexity. For Fortune 500 companies, fast-growing SaaS providers, and global organizations, data exists across public and hybrid clouds, business units, regions, and a stream of new applications.

Regulations such as GDPR, HIPAA, and rules from the SEC now demand current data inventories and continuous proof of risk management. In this environment, defending data at the petabyte level is now essential. Failing to classify and monitor this data efficiently means risking compliance and losing business trust. Security teams are feeling the strain. I meet security teams everyday and too many of them still struggle with data visibility and are already seeing the cracks forming in their current toolset as data scales.

The Hidden Cost of Inefficient DSPM: API Calls and Egress Bills

How DSPM tools perform scanning and discovery drives the real costs of securing petabyte-scale data. Some vendors highlight their capacity to scan multiple petabytes daily. But here's the reality: scanning everything, record by record, relying on huge numbers of API calls, becomes very expensive as your data estate grows.

Every API call can rack up costs, and all the resulting data egress and compute add up too. Large organizations might spend tens of thousands of dollars each month just to track what’s in their cloud. Even worse, older "full scan" DSPM strategies jam up operations with throttling, delays, and a flood of alerts that bury real risk. These legacy approaches simply don’t scale, and organizations relying on them end up paying more while knowing less.

 

Cyera’s "Petabyte Scale" Claims: At What Cloud Cost?

Cyera promotes its tool as an AI-native, agentless DSPM that can scan as much as 2 petabytes daily . While that’s an impressive technical achievement, the strategy of scanning everything leads directly to massive cloud infrastructure costs: frequent API hits, heavy egress, and big bills from AWS, Azure, and GCP.

At scale, these charges don’t just appear on invoices, they can actually stop adoption and limit security’s effectiveness. Cloud operations teams face API throttling, slow results, and a surge in remediation tickets as risks go unfiltered. In these fast-paced environments, recognizing the difference between a real threat and harmless data comes down to speed. The Bedrock Security blog points out how inefficient setups buckle under this weight, leaving teams stuck with lagging visibility and more operational headaches.

Sentra’s 10x Efficiency: Optimized Scanning for Real-World Scale

Sentra takes another route to manage the costs of securing petabyte-scale data. By combining agentless discovery with scanning guided by context and metadata, Sentra uses pattern recognition and an AI-driven clustering algorithm designed to detect machine-generated content—such as log files, invoices, and similar data types. By intelligently sampling data within each cluster, Sentra delivers efficient scanning while reducing scanning costs.

This approach enables data scanning to be prioritized based on risk and business value, rather than wasting time and money scanning the same data over and over again, skipping unnecessary API calls, lowering egress, and keeping cloud bills in check.

Large organizations gain a 10x efficiency edge: quicker classification of data, instant visibility into actual threats, lower operational expenses, and less demand on the network. By focusing attention only where it matters, Sentra matches data security posture management to the demands of current cloud growth and regulatory requirements.

This makes it possible for organizations to hit regulatory and audit targets without watching expenses spiral or opening up security gaps.Sentra offers multiple sampling levels, Quick (default), Moderate, Thorough, and Full, allowing customers to tailor their scanning strategy to balance cost and accuracy. For example, a highly regulated environment can be configured for a full scan, while less-regulated environments can use more efficient sampling. Petabyte-scale security gives the user complete control of their data enterprise and turns into something operationally and financially sustainable, rather than a technical milestone with a hidden cost. 

Efficiency is Non-Negotiable

Fortune 500 companies and digital-first organizations can’t treat efficiency as optional. Inefficient DSPM tools pile on costs, drain resources, and let vulnerabilities slip through, turning their security posture into a liability once scale becomes a factor. Sentra’s platform shows that efficiency is security: with targeted scanning, real context, and unified detection and response, organizations gain clarity and compliance while holding down expenses.

Don’t let your data protection approach crumble under petabyte-scale pressure. See what Sentra can do, reduce costs, and keep essential data secure - before you end up responding to breaches or audit failures.

Conclusion

Securing data at the petabyte level isn't some future aspiration - it's the standard for enterprises right now. Treating it as a secondary feature isn’t just shortsighted; it puts your company at risk, financially and operationally.

The right DSPM architecture brings efficiency, not just raw scale. Sentra delivers real-time, context-rich security posture with far greater efficiency, so your protection and your cloud spending can keep up with your growing business. Security needs to grow along with scale. Rising costs and new risks shouldn’t grow right alongside it.

Want to see how your current petabyte security posture compares? Schedule a demo and see Sentra’s efficiency for yourself.

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