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2026 Cybersecurity Budget Planning: Make Data Visibility a Priority

October 20, 2025
3
Min Read
Data Security

Why Data Visibility Belongs in Your 2026 Cybersecurity Budget

As the fiscal year winds down and security leaders tackle cybersecurity budget planning for 2026, you need to decide how to use every remaining 2025 dollar wisely and how to plan smarter for next year. The question isn’t just what to cut or keep, it’s what creates measurable impact. Across programs, data visibility and DSPM deliver provable risk reduction, faster audits, and clearer ROI,making them priority line items whether you’re spending down this year or shaping next year’s plan. Some teams discover unspent funds after project delays, postponed renewals, or slower-than-expected hiring. Others are already deep in planning mode, mapping next year’s security priorities across people, tools, and processes. Either way, one question looms large: where can a limited security budget make the biggest impact - right now and next year?

Across the industry, one theme is clear: data visibility is no longer a “nice-to-have” line item, it’s a foundational control. Whether you’re allocating leftover funds before year-end or shaping your 2026 strategy, investing in Data Security Posture Management (DSPM) should be part of the plan.

As Bitsight notes, many organizations look for smart ways to use remaining funds that don’t roll over. The goal isn’t simply to spend, it’s to invest in initiatives that improve posture and provide measurable, lasting value. And according to Applied Tech, “using remaining IT funds strategically can strengthen your position for the next budget cycle.”

That same principle applies in cybersecurity. Whether you’re closing out this year or planning for 2026, the focus should be on spending that improves security maturity and tells a story leadership understands. Few areas achieve that more effectively than data-centric visibility.

(For additional background, see Sentra’s article on why DSPM should take a slice of your cybersecurity budget.)

Where to Allocate Remaining Year-End Funds (Without Hurting Next Year’s Budget)

It’s important to utilize all of your 2025 budget allocations because finance departments frequently view underspending as a sign of overfunding, leading to smaller allocations next year. Instead, strategic security teams look for ways to convert every remaining dollar into evidence of progress.

That means focusing on investments that:

  • Produce measurable results you can show to leadership.
  • Strengthen core program foundations: people, visibility, and process.
  • Avoid new recurring costs that stretch future budgets.

Top Investments That Pay Off

1. Invest in Your People

One of the strongest points echoed by security professionals across industry communities: the best investment is almost always your people. Security programs are built on human capability. Certifications, practical training, and professional growth not only expand your team’s skills but also build morale and retention, two things that can’t be bought with tooling alone.

High-impact options include:

  • Hands-on training platforms like Hack The Box, INE Skill Dive, or Security Blue Team, which develop real-world skills through simulated environments.
  • Professional certifications (SANS GIAC, OSCP, or cloud security credentials) that validate expertise and strengthen your team’s credibility.
  • Conference attendance for exposure to new threat perspectives and networking with peers.
  • Cross-functional training between SOC, GRC, and AppSec to create operational cohesion.

In practitioner discussions, one common sentiment stood out: training isn’t just an expense, it’s proof of leadership maturity.

As one manager put it, “If you want your analysts to go the extra mile during an incident, show you’ll go the extra mile for them when things are calm.”

2. Invest in Data Visibility (DSPM)

While team capability drives execution, data visibility drives confidence. In recent conversations among mid-market and enterprise security teams, Data Security Posture Management (DSPM) repeatedly surfaced as one of the most valuable investments made in the past year, especially for hybrid-cloud environments.

One security leader described it this way:

“After implementing DSPM, we finally had a clear picture of where sensitive data actually lived. It saved our team hours of manual chasing and made the audit season much easier.”

That feedback reflects a growing consensus: without visibility into where sensitive data resides, who can access it, and how it’s secured, every other layer of defense operates partly in the dark.

*Tip: If your remaining 2025 budget won’t suffice for a full DSPM deployment, you can scope an initial implementation with the remaining budget, then expand to full coverage in 2026.

DSPM solutions provide that clarity by helping teams:

  • Map and classify sensitive data across multi-cloud and SaaS environments.
  • Identify access misconfigurations or risky sharing patterns.
  • Detect policy violations or overexposure before they become incidents.

Beyond security operations, DSPM delivers something finance and leadership appreciate, measurable proof. Dashboards and reports make risk tangible, allowing CISOs to demonstrate progress in data protection and compliance.

The takeaway: DSPM isn’t just a good way to use remaining funds, it’s a baseline investment every forward-looking security program should plan for in 2026 and beyond.

3. Invest in Testing

Training builds capability. Visibility builds understanding. Testing builds credibility.

External red team, purple team, or security posture assessments continue to be among the most effective ways to validate your defenses and generate actionable findings.

Security practitioners often point out that testing engagements create outcomes leadership understands:

“Training is great, but it’s hard to quantify. An external assessment gives you findings, metrics, and a roadmap you can point to when defending next year’s budget.”

Well-scoped assessments do more than uncover vulnerabilities—they benchmark performance, expose process gaps, and generate data-backed justification for continued investment.

4. Preserve Flexibility with a Retainer

If your team can’t launch a new project before year-end, a retainer with a trusted partner is an efficient way to preserve funds without waste. Retainers can cover services like penetration testing, incident response, or advisory hours, providing flexibility when unpredictable needs arise. This approach, often recommended by veteran CISOs, allows teams to close their books responsibly while keeping agility for the next fiscal year.

5. Strengthen Your Foundations

Not every valuable investment requires new tools. Several practitioners emphasized the long-term returns from process improvements and collaboration-focused initiatives:

  • Threat modeling workshops that align development and security priorities.
  • Framework assessments (like NIST CSF or ISO 27001) that provide measurable baselines.
  • Automation pilots to eliminate repetitive manual work.
  • Internal tabletop exercises that enhance cross-team coordination.

These lower-cost efforts improve resilience and efficiency, two metrics that always matter in budget conversations.

How to Decide: A Simple, Measurable Framework

When evaluating where to allocate remaining or future funds, apply a simple framework:

  1. Identify what’s lagging. Which pillar - people, visibility, or process most limits your current effectiveness?
  2. Choose something measurable. Prioritize initiatives that produce clear, demonstrable outputs: reports, dashboards, certifications.
  3. Aim for dual impact. Every investment should strengthen both your operations and your ability to justify next year’s funding.

Final Thoughts

A strong security budget isn’t just about defense, it’s about direction. Every spend tells a story about how your organization prioritizes resilience, efficiency, and visibility.

Whether you’re closing out this year’s funds or preparing your 2026 plan, focus on investments that create both operational value and executive clarity. Because while technologies evolve and threats shift, understanding where your data is, who can access it, and how it’s protected remains the cornerstone of a mature security program.

Or, as one practitioner summed it up: “Spend on the things that make next year’s budget conversation easier.”

DSPM fits that description perfectly.

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Ward Balcerzak is Field CISO at Sentra, bringing nearly two decades of cybersecurity experience across Fortune 500 companies, defense, manufacturing, consulting, and the vendor landscape. He has built and led data security programs in some of the world’s most complex environments, and is passionate about making true data security achievable. At Sentra, Ward helps bridge real-world enterprise needs with modern, cloud-native security solutions.

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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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Ofir Yehoshua
Ofir Yehoshua
January 13, 2026
3
Min Read

Why Infrastructure Security Is Not Enough to Protect Sensitive Data

Why Infrastructure Security Is Not Enough to Protect Sensitive Data

For years, security programs have focused on protecting infrastructure: networks, servers, endpoints, and applications. That approach made sense when systems were static and data rarely moved. It’s no longer enough.

Recent breach data shows a consistent pattern. Organizations detect incidents, restore systems, and close tickets, yet remain unable to answer the most important question regulators and customers often ask:

Where does my sensitive data reside?

Who or what has access to this data and are they authorized?

Which specific sensitive datasets were accessed or exfiltrated?

Infrastructure security alone cannot answer that question.

Infrastructure Alerts Detect Events, Not Impact

Most security tooling is infrastructure-centric by design. SIEMs, EDRs, NDRs, and CSPM tools monitor hosts, processes, IPs, and configurations. When something abnormal happens, they generate alerts.

What they do not tell you is:

  • Which specific datasets were accessed
  • Whether those datasets contained PHI or PII
  • Whether sensitive data was copied, moved, or exfiltrated

Traditional tools monitor the "plumbing" (network traffic, server logs, etc.) While they can flag that a database was accessed by an unauthorized IP, they often cannot distinguish between an attacker downloading a public template or downloading a table containing 50,000 Social Security numbers. An alert is not the same as understanding the exposure of the data stored inside it. Without that context, incident response teams are forced to infer impact rather than determine it.

The “Did They Access the Data?” Problem

This gap becomes pronounced during ransomware and extortion incidents.

In many cases:

  • Operations are restored from backups
  • Infrastructure is rebuilt
  • Access is reduced
  • (Hopefully!) attackers are removed from the environment

Yet organizations still cannot confirm whether sensitive data was accessed or exfiltrated during the dwell time.

Without data-level visibility:

  • Legal and compliance teams must assume worst-case exposure
  • Breach notifications expand unnecessarily
  • Regulatory penalties increase due to uncertainty, not necessarily damage

The inability to scope an incident accurately is not a tooling failure during the breach, it is a visibility failure that existed long before the breach occurred. Under regulations like GDPR or CCPA/CPRA, if an organization cannot prove that sensitive data wasn’t accessed during a breach, they are often legally required to notify all potentially affected parties. This ‘over-notification’ is costly and damaging to reputation.

Data Movement Is the Real Attack Vulnerability

Modern environments are defined by constant data movement:

  • Cloud migrations
  • SaaS integrations
  • App dev lifecycles
  • Analytics and ETL pipelines
  • AI and ML workflows

Each transition creates blind spots.

Legacy platforms awaiting migration often exist in a “wait state” with reduced monitoring. Data copied into cloud storage or fed into AI pipelines frequently loses lineage and classification context. Posture may vary and traditional controls no longer apply consistently. From an attacker’s perspective, these environments are ideal. From a defender’s perspective, they are blind spots.

Policies Are Not Proof

Most organizations can produce policies stating that sensitive data is encrypted, access-controlled, and monitored. Increasingly, regulators are moving from point-in-time audits to requiring continuous evidence of control.  

Regulators are asking for evidence:

  • Where does PHI live right now?
  • Who or what can access it?
  • How do you know this hasn’t changed since the last audit?

Point-in-time audits cannot answer those questions. Neither can static documentation. Exposure and access drift continuously, especially in cloud and AI-driven environments.

Compliance depends on continuous control, not periodic attestation.

What Data-Centric Security Actually Requires

Accurately proving compliance and scoping breach impact requires security visibility that is anchored to the data itself, not the infrastructure surrounding it.

At a minimum, this means:

  • Continuous discovery and classification of sensitive data
  • Consistent compliance reporting and controls across cloud, SaaS, On-Prem, and migration states
  • Clear visibility into which identities, services, and AI tools can access specific datasets
  • Detection and response signals tied directly to sensitive data exposure and movement

This is the operational foundation of Data Security Posture Management (DSPM) and Data Detection and Response (DDR). These capabilities do not replace infrastructure security controls; they close the gap those controls leave behind by connecting security events to actual data impact.

This is the problem space Sentra was built to address.

Sentra provides continuous visibility into where sensitive data lives, how it moves, and who or what can access it, and ties security and compliance outcomes to that visibility. Without this layer, organizations are forced to infer breach impact and compliance posture instead of proving it.

Why Data-Centric Security Is Required for Today's Compliance and Breach Response

Infrastructure security can detect that an incident occurred, but it cannot determine which sensitive data was accessed, copied, or exfiltrated. Without data-level evidence, organizations cannot accurately scope breaches, contain risk, or prove compliance, regardless of how many alerts or controls are in place. Modern breach response and regulatory compliance require continuous visibility into sensitive data, its lineage, and its access paths. Infrastructure-only security models are no longer sufficient.

Want to see how Sentra provides complete visibility and control of sensitive data?

Schedule a Demo

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