Your AI Is Only as Secure as Your Data: Celebrating a $100M Milestone

The modern enterprise runs on collaboration and nothing powers that more than Microsoft 365. From Exchange Online and OneDrive to SharePoint, Teams, and Copilot workflows, M365 hosts a massive and ever-growing volume of unstructured content: documents, presentations, spreadsheets, image files, chats, attachments, and more.

Yet unstructured = harder to govern. Unlike tidy database tables with defined schemas, unstructured repositories flood in with ambiguous content types, buried duplicates, or unused legacy files. It’s in these stacks that sensitive IP, model training data, or derivative work can quietly accumulate, and then leak.

Consider this: one recent study found that more than 81 % of IT professionals report data-loss events in M365 environments. And to make matters worse, according to the International Data Corporation (IDC), 60% of organizations do not have a strategy for protecting their critical business data that resides in Microsoft 365.

Why Traditional Tools Struggle

• Built-in classification tools (e.g., M365’s native capabilities) often rely on pattern matching or simple keywords, and therefore struggle with accuracy, context, scale and derivative content.
  
  
• Many solutions only surface that a file exists and carries a type label - but stop short of mapping who or what can access it, its purpose, and what its downstream exposure might be.
  
  
• GenAI workflows now pump massive volumes of unstructured data into copilots, knowledge bases, training sets - creating new blast radii that legacy DLP or labeling tools weren’t designed to catch.
  

What a Modern Platform Must Deliver

1. High-accuracy, petabyte-scale classification of unstructured data (so you know what you have, where it sits, and how sensitive it is). And it must keep pace with explosive data growth and do so cost efficiently.
   
   
2. Unified Data Access Governance (DAG) - mapping identities (users, service principals, agents), permissions, implicit shares, federated/cloud-native paths across M365 and beyond.
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3. Data Detection & Response (DDR) - continuous monitoring of data movement, copies, derivative creation, AI agent interactions, and automated response/remediation.

How Sentra addresses this in M365

At Sentra, we’ve built a cloud-native data-security platform specifically to address this triad of capabilities - and we extend that deeply into M365 (OneDrive, SharePoint, Teams, Exchange Online) and other SaaS platforms.

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• A newly announced AI Classifier for Unstructured Data accelerates and improves classification across M365’s unstructured repositories (see: Sentra launches breakthrough unstructured-data AI classification capabilities).
  
  
• Petabyte-scale processing: our architecture supports classification and monitoring of massive file estates without astronomical cost or time-to-value.
  
  
• Seamless support for M365 services: read/write access, ingestion, classification, access-graph correlation, detection of shadow/unmanaged copies across OneDrive and SharePoint—plus integration into our DAG and DDR layers (see our guide: How to Secure Regulated Data in Microsoft 365 + Copilot).
  
  
• Cost-efficient deployment: designed for high scale without breaking the budget or massive manual effort.
  

The Bottom Line

In today’s cloud/AI era, saying “we discovered the PII in my M365 tenant” isn’t enough.

The real question is: Do I know who or what (user/agent/app) can access that content, what its business purpose is, and whether it’s already been copied or transformed into a risk vector?

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If your solution can’t answer that, your unstructured data remains a silent, high-stakes liability and resolving concerns becomes a very costly, resource-draining burden. By embracing a platform that combines classification accuracy, petabyte-scale processing, unified DSPM + DAG + DDR, and deep M365 support, you move from “hope I’m secure” to “I know I’m secure.”

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Want to see how it works in a real M365 setup? Check out our video or book a demo.

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Every organization today is drowning in data - millions of assets spread across cloud platforms, on-premises systems, and an ever-expanding landscape of SaaS tools. Each asset carries value, but also risk. For security and compliance teams, the mandate is clear: sensitive data must be inventoried, managed and protected.

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Scanning every asset for security and compliance is no longer optional, it’s the line between trust and exposure, between resilience and chaos.

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Many data security tools promise to scan and classify sensitive information across environments. In practice, doing this effectively and at scale, demands more than raw ‘brute force’ scanning power. It requires robust visibility and management capabilities: a cockpit view that lets teams monitor coverage, prioritize intelligently, and strike the right balance between scan speed, cost, and accuracy.

Why Scan Tracking Is Crucial

Scanning is not instantaneous. Depending on the size and complexity of your environment, it can take days - sometimes even weeks to complete. Meanwhile, new data is constantly being created or modified, adding to the challenge.

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Without clear visibility into the scanning process, organizations face several critical obstacles:

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• Unclear progress: It’s often difficult to know what has already been scanned, what is currently in progress, and what remains pending. This lack of clarity creates blind spots that undermine confidence in coverage.
  
  
• Time estimation gaps: In large environments, it’s hard to know how long scans will take because so many factors come into play — the number of assets, their size, the type of data - structured, semi-structured, or unstructured, and how much scanner capacity is available. As a result, predicting when you’ll reach full coverage is tricky. This becomes especially stressful when scans need to be completed before a fixed deadline, like a compliance audit. 
  
  "With Sentra’s Scan Dashboard, we were able to quickly scale up our scanners to meet a tight audit deadline, finish on time, and then scale back down to save costs. The visibility and control it gave us made the whole process seamless”, said CISO of Large Retailer.‍
• Poor prioritization: Not all environments or assets carry the same importance. Yet without visibility into scan status, teams struggle to balance historical scans of existing assets with the ongoing influx of newly created data, making it nearly impossible to prioritize effectively based on risk or business value.

Sentra’s End-to-End Scanning Workflow

Managing scans at petabyte scale is complex. Sentra streamlines the process with a workflow built for scale, clarity, and control that features:

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1. Comprehensive Asset Discovery

Before scanning even begins, Sentra automatically discovers assets across cloud platforms, on-premises systems, and SaaS applications. This ensures teams have a complete, up-to-date inventory and visual map of their data landscape, so no environment or data store is overlooked.

Example: New S3 buckets, a freshly deployed BigQuery dataset, or a newly connected SharePoint site are automatically identified and added to the inventory.
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2. Configurable Scan Management

Administrators can fine-tune how scans are executed to meet their organization’s needs. With flexible configuration options, such as number of scanners, sampling rates, and prioritization rules - teams can strike the right balance between scan speed, coverage, and cost control.

For instance, compliance-critical assets can be scanned at full depth immediately, while less critical environments can run at reduced sampling to save on compute consumption and costs.

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3. Real-Time Scan Dashboard

Sentra’s unified Scan Dashboard provides a cockpit view into scanning operations, so teams always know where they stand. Key features include:

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• Daily scan throughput correlated with the number of active scanners, helping teams understand efficiency and predict completion times.
• Coverage tracking that visualizes overall progress and highlights which assets remain unscanned.
• Decision-making tools that allow teams to dynamically adjust, whether by adding scanner capacity, changing sampling rates, or reordering priorities when new high-risk assets appear.

Handling Data Changes

The challenge doesn’t end once the initial scans are complete. Data is dynamic, new files are added daily, existing records are updated, and sensitive information shifts locations. Sentra’s activity feeds give teams the visibility they need to understand how their data landscape is evolving and adapt their data security strategies in real time.

Conclusion

Tracking scan status at scale is complex but critical to any data security strategy. Sentra provides an end-to-end view and unmatched scan control, helping organizations move from uncertainty to confidence with clear prediction of scan timelines, faster troubleshooting, audit-ready compliance, and smarter, cost-efficient decisions for securing data.

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Enhanced DSPM Adoption Is the Most Important Data Security Trend of 2026

Over the past few years, organizations have realized that traditional security tools can’t keep pace with how data moves and grows today. Exploding volumes of sensitive data now flourish across multi-cloud environments, SaaS platforms, and AI systems, often without full visibility by the teams responsible for securing it. Unstructured data presents the greatest risk - representing over 80% of corporate data.

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That’s why Data Security Posture Management (DSPM) has become a critical part of the modern security stack. DSPM tools help organizations automatically discover, classify, monitor, and protect sensitive data - no matter where it lives or travels.

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But in 2026, the data security game is changing. Many DSPMs can tell you what your data is,  but more is needed. Leading DSPM platforms are going beyond visibility. They’re delivering real-time AI-enhanced contextual business insights, automated remediation, and AI-aware accurate protection that scales with your dynamic data.

AI-enhanced DSPM Capabilities in 2026

Not all DSPM tools are built the same. The top platforms share a few key traits that define the next generation of data security posture management:

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Top DSPM Tools to Watch in 2026

Based on recent analyst coverage, market growth, and innovation across the industry, here are the top DSPM platforms to watch this year, each contributing to how data security is evolving.

1. Sentra

As a cloud-native DSPM platform, Sentra focuses on continuous data protection, not just visibility. It discovers and accurately classifies sensitive data in real time across all cloud environments, while automatically remediating risks through policy-driven automation.

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What sets Sentra apart:

• Continuous, automated discovery and classification across your entire data estate - cloud, SaaS, and on-premises.
• Business Contextual insights that understand the purpose of data, accurately linking data, identity, and risk.
• Automatic learning to discern customer unique data types and continuously improve labeling over time.
• Petabyte scaling and low compute consumption for 10X cost efficiency.
• Automated remediation workflows and integrations to fix issues instantly.
• Built-in coverage for data flowing through AI and SaaS ecosystems.

Ideal for: Security teams looking for a cloud-native DSPM platform built for scalability in the AI era with automation at its core.

2. BigID

A pioneer in data discovery and classification, BigID bridges DSPM and privacy governance, making it a good choice for compliance-heavy sectors.

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Ideal for: Organizations prioritizing data privacy, governance, and audit readiness.

3. Prisma Cloud (Palo Alto Networks)

Prisma’s DSPM offering integrates closely with CSPM and CNAPP components, giving security teams a single pane of glass for infrastructure and data risk.

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Ideal for: Enterprises with hybrid or multi-cloud infrastructures already using Palo Alto tools.

4. Microsoft Purview / Defender DSPM

Microsoft continues to invest heavily in DSPM through Purview, offering rich integration with Microsoft 365 and Azure ecosystems. Note: Sentra integrates with Microsoft Purview Information Protection (MPIP) labeling and DLP policies.

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Ideal for: Microsoft-centric organizations seeking native data visibility and compliance automation.

5. Securiti.ai

Positioned as a “Data Command Center,” Securiti unifies DSPM, privacy, and governance. Its strength lies in automation and compliance visibility and SaaS coverage.

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Ideal for: Enterprises looking for an all-in-one governance and DSPM solution.

6. Cyera

Cyera has gained attention for serving the SMB segment with its DSPM approach. It uses LLMs for data context, supplementing other classification methods, and provides integrations to IAM and other workflow tools.

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Ideal for: Small/medium growing companies that need basic DSPM functionality.

7. Wiz

Wiz continues to lead in cloud security, having added DSPM capabilities into its CNAPP platform. They’re known for deep multi-cloud visibility and infrastructure misconfiguration detection.

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Ideal for: Enterprises running complex cloud environments looking for infrastructure vulnerability and misconfiguration management.

8. Varonis

Varonis remains a strong player for hybrid and on-prem data security, with deep expertise in permissions and access analytics and focus on SaaS/unstructured data.

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Ideal for: Enterprises with legacy file systems or mixed cloud/on-prem architectures.

9. Netwrix

Netwrix’s platform incorporates DSPM-related features into its auditing and access control suite.
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‍Ideal for: Mid-sized organizations seeking DSPM as part of a broader compliance solution.

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Emerging DSPM Trends to Watch in 2026

1. AI Data Security: As enterprises adopt GenAI, DSPM tools are evolving to secure data used in training and inference.
   
   
2. Identity-Centric Risk: Understanding and controlling both human and machine identities is now central to data posture.
   
   
3. Automation-Driven Security: Remediation workflows are becoming the differentiator between “good” and “great.”
   
   

Market Consolidation: Expect to see CNAPP, legacy security, and cloud vendors acquiring DSPM startups to strengthen their coverage.

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How to Choose the Right DSPM Tool

When evaluating a DSPM solution, align your choice with your data landscape and goals:

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• Cloud-Native Company Choose tools designed for cloud-first environments (like Sentra, Securiti, Wiz).
  
• Compliance Priority Platforms like Sentra, BigID or Securiti excel in privacy and governance.
  
• Microsoft-Heavy Stack Purview and Sentra DSPM offer native integration.
  
• Hybrid Environment Consider Varonis, Prisma Cloud, or Sentra for extended visibility.
  
• Enterprise Scalability Evaluate deployment ease, petabyte scalability, cloud resource consumption, scanning efficiency, etc. (Sentra excels here)

*Pro Tip: Run a proof of concept (POC) across multiple environments to test scalability, accuracy, and operational cost effectiveness before full deployment.

Final Thoughts: DSPM Is About Action

The best DSPM tools in 2026 share one core principle, they help organizations move from visibility to action.

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At Sentra, we believe that the future of DSPM lies in continuous, automated data protection:

• Real-time discovery of sensitive data @ scale
• Context-aware prioritization for business insight
• Automated remediation that reduces risk instantly

As data continues to power AI, analytics, and innovation, DSPM ensures that innovation never comes at the cost of security. See how Sentra helps leading enterprises protect data across multi-cloud and SaaS environments.

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