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20/08/2026 6:07 pm
TL;DR: Moving sensitive data for scanning and classification increases egress exposure, compliance complexity, and cost, according to Sentra’s analysis of zero data movement DSPM. The governance shift is toward analysing and enforcing policy where data already resides, because copying data to secure it often creates the risk it is meant to reduce.
NHIMG editorial — based on content published by Sentra: Zero Data Movement DSPM and how it changes cloud data security
By the numbers:
- Data volumes are expected to reach 181 zettabytes in 2025, which is why movement-heavy security models struggle to keep pace.
Questions worth separating out
Q: How should security teams evaluate DSPM tools for modern data movement?
A: They should test whether the platform can trace sensitive content across SaaS, endpoints, collaboration tools, code repositories, and AI systems.
Q: Why does data movement increase compliance risk in multi-cloud environments?
A: Because each copy or transfer creates a new location that must be governed under residency, retention, access, and audit requirements.
Q: What do teams get wrong about agentless data security tools?
A: They often assume agentless means low-risk by default.
Practitioner guidance
- Audit every data inspection path Trace how sensitive data flows from source storage into scanning, classification, and reporting systems, then eliminate any step that creates unmanaged copies or exports.
- Review service identity permissions Inventory the service accounts, tokens, and cloud roles used by DSPM tooling, and constrain them to the minimum read scope needed for in-place analysis.
- Map controls to residency obligations Align each cloud region and data class to the residency, retention, and audit requirements that apply before a tool is allowed to process it.
What's in the full article
Sentra's full blog post covers the architectural detail this post intentionally leaves for the source:
- How zero data movement is implemented across cloud storage, scanning, and policy enforcement workflows
- The operational differences between in-place inspection, connector-based analysis, and centralised data lake patterns
- Why data residency, compliance, and egress risk change the architecture decision for regulated environments
- Examples of where agentless deployment simplifies scaling without removing governance requirements
👉 Read Sentra's analysis of zero data movement DSPM for cloud data governance →
Zero data movement DSPM: are your data controls still moving risk?
Explore further
20/08/2026 6:42 pm
Zero data movement is becoming a governance standard, not a niche architecture choice. Cloud data estates now span multiple regions, tenants, and legal regimes, so any model that relies on copying information for security work adds avoidable exposure. The practical takeaway is that data governance must increasingly be enforced in place, with less tolerance for inspection workflows that create secondary risk.
A question worth separating out:
Q: How can organisations reduce the risk of hidden data copies?
A: By mapping every scan, classification, backup, and reporting workflow to a specific data class and residency rule, then blocking any workflow that writes sensitive data to shared repositories or external analytics platforms unless that movement is explicitly required and approved.
👉 Read our full editorial: Zero data movement DSPM is changing cloud data governance
