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The Importance of Data Security for Growth: A Blueprint for Innovation

January 15, 2025
3
Min Read

“For whosoever commands the sea commands the trade; whosoever commands the trade of the world commands the riches of the world, and consequently the world itself.” — Sir Walter Raleigh.

For centuries, power belonged to those who ruled the seas. Today, power belongs to those who control and harness their data’s potential. But let’s face it—many organizations are adrift, overwhelmed by the sheer volume of data and rushing to keep pace in a rapidly shifting threatscape. Navigating these waters requires clarity, foresight, and the right tools to stay afloat and steer toward success. Sound familiar? 

In this new reality, controlling data now drives success. But success isn’t just about collecting data, it’s about being truly data-driven. For modern businesses, data isn’t just another resource. Data is the engine of growth, innovation, and smarter decision-making.

Yet many leaders still grapple with critical questions:

  • Are you really in control of your data?
  • Do you make decisions based on the insights your data provides?
  • Are you using it to navigate toward long-term success?

In this blog, I’ll explore why mastering your data isn’t just a strategic advantage—it’s the foundation of survival in today’s competitive market - Data is the way to success and prosperity in an organization. I’ll also break down how forward-thinking organizations are using comprehensive Data Security Platforms to navigate this new era where speed, innovation, and security can finally coexist.

The Role of Data in Organizational Success

Data drives innovation, fuels growth, and powers smart decision-making. Businesses use data to develop new products, improve customer experiences, and maintain a competitive edge. But let’s be clear, collecting vast amounts of data isn’t enough. True success comes from securing it, understanding it, and putting it to work effectively.

If you don’t fully understand or protect your data, how valuable can it really be?

Organizations face a constant barrage of threats: data breaches, shadow data, and excessive access permissions. Without strong safeguards, these vulnerabilities don’t just pose risks—they become ticking time bombs.

For years, controlling and understanding your data was impossible—it was a complex, imprecise, expensive, and time-consuming process that required significant resources. Today, for the first time ever, there is a solution. With innovative approaches and cutting-edge technology, organizations can now gain the clarity and control they need to manage their data effectively!

With the right approach, businesses can transform their data management from a reactive process to a competitive advantage, driving both innovation and resilience. As data security demands grow, these tools have evolved into something much more powerful: comprehensive Data Security Platforms (DSPs). Unlike basic solutions, you can expect a data security platform to deliver advanced capabilities such as enhanced access control, real-time threat monitoring, and holistic data management. This all-encompassing approach doesn’t just protect sensitive data—it makes it actionable and valuable, empowering organizations to thrive in an ever-changing landscape.

Building a strong data security strategy starts with visionary leadership. It’s about creating a foundation that not only protects data but enables organizations to innovate fearlessly in the face of uncertainty.

The Three Key Pillars for Securing and Leveraging Data

1. Understand Your Data

The foundation of any data security strategy is visibility. Knowing where your data is stored, who has access to it, and what sensitive information it contains is essential. Data sprawl remains a challenge for many organizations. The latest tools, powered by automation and intelligence, provide unprecedented clarity by discovering, classifying, and mapping sensitive data. These insights allow businesses to make sharper, faster decisions to protect and harness their most valuable resource.

Beyond discovery, advanced tools continuously monitor data flows, track changes, and alert teams to potential risks in real-time. With a complete understanding of their data, organizations can shift from reactive responses to proactive management.

2. Control Your Data

Visibility is the first step; control is the next. Managing access to sensitive information is critical to minimizing risk. This involves identifying overly broad permissions and ensuring that access is granted only to those who truly need it.

Having full control of your data becomes even more challenging when data is copied or moved between environments—such as from private to public or from encrypted to unencrypted. This process creates "similar data," in which data that was initially secure becomes exposed to greater risk by being moved into a lower environment. Data that was once limited to a small, regulated group of identities (users) then becomes accessible by a larger number of users, resulting in a significant loss of control.

Effective data security strategies go beyond identifying these issues. They enforce access policies, automate corrective actions, and integrate with identity and access management systems to help organizations maintain a strong security posture, even as their business needs change and evolve. In addition to having robust data identification methods, it’s crucial to prioritize the implementation of access control measures. This involves establishing Role-based Access Control (RBAC) and Attribute-based Access Control (ABAC) policies, so that the right users have permissions at the right times.

3. Monitor Your Data

Real security goes beyond awareness—it demands a dynamic approach. Real-time monitoring doesn’t just detect risks and threats; it anticipates them. By spotting unusual behaviors or unauthorized access early, businesses can preempt incidents and maintain trust in an increasingly volatile digital environment. Advanced tools provide visibility into suspicious activities, offer real-time alerts, and automate responses, enabling security teams to act swiftly. This ongoing oversight ensures that businesses stay resilient and adaptive in an ever-changing environment.

Being Fast and Secure

In today’s competitive market, speed drives success—but speed without security is a recipe for disaster. Organizations must balance rapid innovation with robust protection.

Modern tools streamline security operations by delivering actionable insights for faster, more informed risk responses. A comprehensive Data Security Platform goes further by integrating security workflows, automating threat detection, and enabling real-time remediation across multi-cloud environments. By embedding security into daily processes, businesses can maintain agility while protecting their most critical assets.

Why Continuous Data Security is the Key to Long-Term Growth

Data security isn’t a one-and-done effort—it’s an ongoing commitment. As businesses scale and adopt new technologies, their data environments grow more complex, and security threats continue to evolve. Organizations that continuously understand and control their data are poised to turn uncertainty into opportunity. By maintaining this control, they sustain growth, protect trust, and future-proof their success.

Adaptability is the foundation of long-term success. A robust data security platform evolves with your business, providing continuous visibility, automating risk management, and enabling proactive security measures. By embedding these capabilities into daily operations, organizations can maintain speed and agility without compromising protection.

In today’s data-driven world, success hinges on making informed decisions with secure data. Businesses that master continuous data security will not only safeguard their assets but also position themselves to thrive in an ever-changing competitive landscape.

Conclusion: The Critical Link Between Data Security and Success

Data is the lifeblood of modern businesses, driving growth, innovation, and decision-making. But with this immense value comes an equally immense responsibility: protecting it. A comprehensive data security platform goes beyond the basics, unifying discovery, classification, access governance, and real-time protection into a single proactive approach. True success in a data-driven world demands more than agility—it requires mastery. Organizations that embrace data security as a catalyst for innovation and resilience are the ones who will lead the way in today’s competitive landscape.

The question is: Will you lead the charge or risk being left behind? The opportunity to secure your future starts now.

Final thought: In my work with organizations across industries, I’ve seen firsthand how those who treat data security as a strategic enabler, rather than an obligation, consistently outperform their peers. The future belongs to those who lead with confidence, clarity, and control.

If you're interested in learning how Sentra's Data Security Platform can help you understand and protect your data to drive success in today’s competitive landscape, request a demo today.

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Yoav Regev has over two decades of experience in the world of cybersecurity, cloud, big data, and machine learning. He was the Head of Cyber Department (Colonel) in the Israeli Military Intelligence (Unit 8200) for nearly 25 years. Reflecting on this experience, it was clear to him that sensitive data had become the most important asset in the world. In the private sector, enterprises that were leveraging data to generate new insights, develop new products, and provide better experiences, were separating themselves from the competition. As data becomes more valuable, it becomes a bigger target, and as the amount of sensitive data grows, so does the importance of finding the most effective way to secure it. That’s why he co-founded Sentra, together with accomplished co-founders, Asaf Kochan, Ron Reiter, and Yair Cohen.

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Ward Balcerzak
Ward Balcerzak
December 17, 2025
3
Min Read

How CISOs Will Evaluate DSPM in 2026: 13 New Buying Criteria for Security Leaders

How CISOs Will Evaluate DSPM in 2026: 13 New Buying Criteria for Security Leaders

Data Security Posture Management (DSPM) has quickly become part of mainstream security, gaining ground on older solutions and newer categories like XDR and SSE. Beneath the hype, most security leaders share the same frustration: too many products promise results but simply can't deliver in the messy, large-scale settings that enterprises actually have. The DSPM market is expected to jump from $1.86B in 2024 to $22.5B by 2033, giving buyers more choice - and greater pressure - to demand what really sets a solution apart for the coming years.

Instead of letting vendors dictate the RFP, what if CISOs led the process themselves? Fast-forward to 2026 and the checklist a CISO uses to evaluate DSPM solutions barely resembles the checklists of the past. Here are the 12 criteria everyone should insist on - criteria most vendors would rather you ignore, but industry leaders like Sentra are happy to highlight.

Why Legacy DSPM Evaluation Fails Modern CISOs

Traditional DSPM/DCAP evaluations were all about ticking off feature boxes: Can it scan S3 buckets? Show file types? But most CISO I meet point to poor data visibility as their biggest vulnerability. It's already obvious that today’s fragmented, agent-heavy tools aren’t cutting it.

So, what’s changed for 2026? Massive data volumes, new unstructured formats like chat logs or AI training sets, and rapid cloud adoption mean security leaders now need a different class of protection.

The right platform:

  • Works without agents, everywhere you operate
  • Focuses on bringing real, risk-based context - not just adding more alerts
  • Automates compliance and fixes identity/data governance gaps
  • Manages both structured and unstructured data across the whole organization

Old evaluation checklists don’t come close. It’s time to update yours.

The 13 DSPM Buying Criteria Vendors Hope You Don’t Ask

Here’s what should be at the heart of every modern assessment, especially for 2026:

  1. Is the platform truly agentless, everywhere? Agent-based designs slow you down and block coverage. The best solutions set up in minutes, with absolutely no agents - across SaaS, IaaS, or on-premises and will always discover any unknown and shadow data
  1. Does it operate fully in-environment? Your data needs to stay in your cloud or region - not copied elsewhere for analysis. In-environment processing guards privacy, simplifies compliance, and matches global regulations (Cloud Security Alliance).
  1. Can it accurately classify unstructured data (>98% accuracy)? Most tools stumble outside of databases. Insist on AI-powered classification that understands language, context, and sensitivity. This covers everything from PDF files to Zoom recordings to LLM training data.
  1. How does it handle petabyte-scale scanning and will it  break the bank? Legacy options get expensive as data grows. You need tools that can scan quickly and stay cost-effective across multi-cloud and hybrid environments at massive scale.
  1. Does it unify data and identity governance? Very few platforms support both human and machine identities - especially for service accounts or access across clouds. Only end-to-end coverage breaks down barriers between IT, business, and security.
  1. Can it surface business-contextualized risk insights? You need more than technical vulnerability. Leading platforms map sensitive data by its business importance and risk, making it easier to prioritize and take action.
  1. Is deployment frictionless and multi-cloud native? DSPM should work natively in AWS, Azure, GCP, and SaaS, no complicated integrations required. Insist on fast, simple onboarding.
  1. Does it offer full remediation workflow automation? It’s not enough to raise the alarm. You want exposures fixed automatically, at scale, without manual effort.

  2. Does this fit within my Data Security Ecosystem? Choose only platforms that integrate and enrich your current data governance stack so every tool operates from the same source of truth without adding operational overhead. 
  1. Are compliance and security controls bridged in a unified dashboard? No more switching between tools. Choose platforms where compliance and risk data are combined into a single view for GRC and SecOps.
  1. Does it support business-driven data discovery (e.g., by project, region, or owner)? You need dynamic views tied to business needs, helping cloud initiatives move faster without adding risk, so security can become a business enabler.
  1. What’s the track record on customer outcomes at scale? Actual results in complex, high-volume settings matter more than demo promises. Look for real stories from large organizations.
  2. How is pricing structured for future growth? Beware of pricing that seems low until your data doubles. Look for clear, usage-based models so expansion won’t bring hidden costs.

Agentless, In-Environment Power: Why It’s the New Gold Standard

Agentless, in-environment architecture removes hassles with endpoint installs, connectors, and worries about where your data goes. Gartner has highlighted that this approach reduces regulatory headaches and enables fast onboarding. As organizations keep adding new cloud and hybrid systems, only these platforms can truly scale for global teams and strict requirements.

Sentra’s platform keeps all processing inside your environment. There’s no need to export your data; offering peace of mind for privacy, sovereignty, and speed. With regulations increasing everywhere, this approach isn’t just helpful; it’s essential.

Classification Accuracy and Petabyte-Scale Efficiency: The Must-Haves for 2026

Unstructured data is growing fast, and workloads are now more diverse than ever. The difference between basic scanning and real, AI-driven classification is often the difference between protecting your company or ending up on the breach list. Leading platforms, including Sentra, deliver over 95% classification accuracy by using large language models and in-house methods across both structured and unstructured data.

Why is speed and scale so important? Old-school solutions were built with smaller data volumes in mind. Today, DSPM platforms must quickly and affordably identify and secure data in vast environments. Sentra’s scanning is both fast and affordable, keeping up as your data grows. To learn more about these challenges read: Reducing Cloud Data Attack Risk.

Don’t Settle: Redefining Best-in-Class DSPM Buying Criteria for 2026

Many vendors are still only comfortable offering the basics, but the demands facing CISOs today are anything but basic. Combining identity and data governance, multi-cloud support that works out of the box, and risk insights mapped to real business needs - these are the essential elements for protecting today’s and tomorrow’s data. If a solution doesn’t check all 12 boxes, you’re already limiting your security program before you start.

Need a side-by-side comparison for your next decision?  Request a personalized demo to see exactly how Sentra meets every requirement.

Conclusion

With AI further accelerating data growth, security teams can’t afford to settle for legacy features or generic checklists. By insisting on meaningful criteria - true agentless design, in-environment processing, precise AI-driven classification, scalable affordability, and business-first integration - CISOs set a higher standard for both their own organizations and the wider industry.

Sentra is ready to help you raise the bar. Contact us for a data risk assessment, or to discuss how to ensure your next buying decision leads to better protection, less risk, and a stronger position for the future.

Continue the Conversation

If you want to go deeper into how CISOs are rethinking data security, I explore these topics regularly on Guardians of the Data, a podcast focused on real-world data protection challenges, evolving DSPM strategies, and candid conversations with security leaders.

Watch or listen to Guardians of the Data for practical insights on securing data in an AI-driven, multi-cloud world.

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Nikki Ralston
Nikki Ralston
Romi Minin
Romi Minin
December 16, 2025
3
Min Read

Sentra Is One of the Hottest Cybersecurity Startups

Sentra Is One of the Hottest Cybersecurity Startups

We knew we were on a hot streak, and now it’s official.

Sentra has been named one of CRN’s 10 Hottest Cybersecurity Startups of 2025. This recognition is a direct reflection of our commitment to redefining data security for the cloud and AI era, and of the growing trust forward-thinking enterprises are placing in our unique approach.

This milestone is more than just an award. It shows our relentless drive to protect modern data systems and gives us a chance to thank our customers, partners, and the Sentra team whose creativity and determination keep pushing us ahead.

The Market Forces Fueling Sentra’s Momentum

Cybersecurity is undergoing major changes. With 94% of organizations worldwide now relying on cloud technologies, the rapid growth of cloud-based data and the rise of AI agents have made security both more urgent and more complicated. These shifts are creating demands for platforms that combine unified data security posture management (DSPM) with fast data detection and response (DDR).

Industry data highlights this trend: over 73% of enterprise security operations centers are now using AI for real-time threat detection, leading to a 41% drop in breach containment time. The global cybersecurity market is growing rapidly, estimated to reach $227.6 billion in 2025, fueled by the need to break down barriers between data discovery, classification, and incident response 2025 cybersecurity market insights. In 2025, organizations will spend about 10% more on cyber defenses, which will only increase the demand for new solutions.

Why Recognition by CRN Matters and What It Means

Landing a place on CRN’s 10 Hottest Cybersecurity Startups of 2025 is more than publicity for Sentra. It signals we truly meet the moment. Our rise isn’t just about new features; it’s about helping security teams tackle the growing risks posed by AI and cloud data head-on. This recognition follows our mention as a CRN 2024 Stellar Startup, a sign of steady innovation and mounting interest from analysts and enterprises alike.

Being on CRN’s list means customers, partners, and investors value Sentra’s straightforward, agentless data protection that helps organizations work faster and with more certainty.

Innovation Where It Matters: Sentra’s Edge in Data and AI Security

Sentra stands out for its practical approach to solving urgent security problems, including:

  • Agentless, multi-cloud coverage: Sentra identifies and classifies sensitive data and AI agents across cloud, SaaS, and on-premises environments without any agents or hidden gaps.
  • Integrated DSPM + DDR: We go further than monitoring posture by automatically investigating incidents and responding, so security teams can act quickly on why DSPM+DDR matters.
  • AI-driven advancements: Features like domain-specific AI Classifiers for Unstructure advanced AI classification leveraging SLMs, Data Security for AI Agents and Microsoft M365 Copilot help customers stay in control as they adopt new technologies Sentra’s AI-powered innovation.

With new attack surfaces popping up all the time, from prompt injection to autonomous agent drift, Sentra’s architecture is built to handle the world of AI.

A Platform Approach That Outpaces the Competition

There are plenty of startups aiming to tackle AI, cloud, and data security challenges. Companies like 7AI, Reco, Exaforce, and Noma Security have been in the news for their funding rounds and targeted solutions. Still, very few offer the kind of unified coverage that sets Sentra apart.

Most competitors stick to either monitoring SaaS agents or reducing SOC alerts. Sentra does more by providing both agentless multi-cloud DSPM and built-in DDR. This gives organizations visibility, context, and the power to act in one platform. With features like Data Security for AI Agents, Sentra helps enterprises go beyond managing alerts by automating meaningful steps to defend sensitive data everywhere.

Thanks to Our Community and What’s Next

This honor belongs first and foremost to our community: customers breaking new ground in data security, partners building solutions alongside us, and a team with a clear goal to lead the industry.

If you haven’t tried Sentra yet, now’s a great time to see what we can do for your cloud and AI data security program. Find out why we’re at the forefront: schedule a personalized demo or read CRN’s full 2025 list for more insight.

Conclusion

Being named one of CRN’s hottest cybersecurity startups isn’t just a milestone. It pushes us forward toward our vision - data security that truly enables innovation. The market is changing fast, but Sentra’s focus on meaningful security results hasn't wavered.

Thank you to our customers, partners, investors, and team for your ongoing trust and teamwork. As AI and cloud technology shape the future, Sentra is ready to help organizations move confidently, securely, and quickly.

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Meni Besso
Meni Besso
December 15, 2025
3
Min Read

AI Governance Starts With Data Governance: Securing the Training Data and Agents Fuelling GenAI

AI Governance Starts With Data Governance: Securing the Training Data and Agents Fuelling GenAI

Generative AI isn’t just transforming products and processes - it’s expanding the entire enterprise risk surface. As C-suite executives and security leaders rush to unlock GenAI’s competitive advantages, a hard truth is clear: effective AI governance depends on solid, end-to-end data governance.

Sensitive data is increasingly used for model training and autonomous agents. If organizations fail to discover, classify, and secure these resources early, they risk privacy breaches, regulatory violations, and reputational damage. To make GenAI safe, compliant, and trustworthy from the start, data governance for generative AI needs to be a top boardroom priority.

Why Data Governance is the Cornerstone of GenAI Trustworthiness and Safety

The opportunities and risks of generative AI depend not only on algorithms, but also on the quality, security, and history of the underlying data. AWS reports that 39% of Chief Data Officers see data cleaning, integration, and storage as the main barriers to GenAI adoption, and 49% of enterprises make data quality improvement a core focus for successful AI projects (AWS Enterprise Strategy - Data Governance). Without strong data governance, sensitive information can end up in training sets, leading to unintentional leaks or model behaviors that break privacy and compliance.

Regulatory requirements, such as the Generative AI Copyright Disclosure Act, are evolving fast, raising the pressure to document data lineage and make sure unauthorized or non-compliant datasets stay out. In the world of GenAI, governance goes far beyond compliance checklists. It’s essential for building AI that is safe, auditable, and trusted by both regulators and customers.

New Attack Surfaces: Risks From Unsecured Data and Shadow AI Agents

GenAI adoption increases risk. Today, 79% of organizations have already piloted or deployed agentic AI, with many using LLM-powered agents to automate key workflows (Wikipedia - Agentic AI). But if these agents, sometimes functioning as "shadow AI" outside official oversight, access sensitive or unclassified data, the fallout can be severe.

In 2024, over 30% of AI data breaches involve insider threats or accidental disclosure, according to Quinnox Data Governance for AI. Autonomous agents can mistakenly reveal trade secrets, financial records, or customer data, damaging brand trust. The risk multiplies rapidly if sensitive data isn’t properly governed before flowing into GenAI tools. To stop these new threats, organizations need up-to-the-minute insight and control over both data and the agents using it.

Frameworks and Best Practices for Data Governance in GenAI

Leading organizations now follow data governance frameworks that match changing regulations and GenAI's technical complexity. Standards like NIST AI Risk Management Framework (AI RMF) and ISO/IEC 42001:2023 are setting the benchmarks for building auditable, resilient AI programs (Data and AI Governance - Frameworks & Best Practices).

Some of the most effective practices:

  • Managing metadata and tracking full data lineage
  • Using data access policies based on role and context
  • Automating compliance with new AI laws
  • Monitoring data integrity and checking for bias

A strong data governance program for generative AI focuses on ongoing data discovery, classification, and policy enforcement - before data or agents meet any AI models. This approach helps lower risk and gives GenAI efforts a solid base of trust.

Sentra’s Approach: Proactive Pre-Integration Discovery and Continuous Enforcement

Many tools only secure data after it’s already being used with GenAI applications. This reactive strategy leaves openings for risk. Sentra takes a different path, letting organizations discover, classify, and protect sensitive data sources before they interact with language models or agentic AI.

By using agentless, API-based discovery and classification across multi-cloud and SaaS environments, Sentra delivers immediate visibility and context-aware risk scoring for all enterprise data assets. With automated policies, businesses can mask, encrypt, or restrict data access depending on sensitivity, business requirements, or audit needs. Live Continuous monitoring tracks which AI agents are accessing data, making granular controls and fast intervention possible. These processes help stop shadow AI, keep unauthorized data out of LLM training, and maintain compliance as rules and business needs shift.

Guardrails for Responsible AI Growth Across the Enterprise

The future of GenAI depends on how well businesses can innovate while keeping security and compliance intact. As AI regulations become stricter and adoption speeds up, Sentra’s ability to provide ongoing, automated discovery and enforcement at scale is critical. Further reading: AI Automation & Data Security: What You Need To Know.

With Sentra, organizations can:

  • Stop unapproved or unchecked data from being used in model training
  • Identify shadow AI agents or risky automated actions as they happen
  • Support audits with complete data classification
  • Meet NIST, ISO, and new global standards with ease

Sentra gives CISOs, CDOs, and executives a proactive, scalable way to adopt GenAI safely, protecting the business before any model training even begins.

AI Governance Starts with Data Governance

AI governance for generative AI starts, and is won or lost, at the data layer. If organizations don’t find, classify, and secure sensitive data first, every other security measure remains reactive and ineffective. As generative AI, agent automation, and regulatory demands rise, a unified data governance strategy isn’t just good practice, it’s an urgent priority. Sentra gives security and business teams real control, making sure GenAI is secure, compliant, and trusted.

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