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Organizations close the data security gap by making data protection and data access part of the same operating model: find sensitive data, classify it, limit access according to approved users and purposes, and audit how it is used. A platform may help coordinate those controls, but it cannot replace the policies, people, and breach-response capabilities needed to run a security program.
Why data protection and data access can conflict
Data is useful when authorized people can find and use it for legitimate work. But when teams cannot see where sensitive information is stored or who can reach it, broad access can increase exposure. At the other extreme, fragmented or overly restrictive controls can prevent appropriate sharing and analysis.
In a 2023 opinion article, Mark Semenenko, then identified as Director of Solutions Architecture at Immuta, described this tension in organizations whose data is spread across systems, locations, and cloud environments. The article is an industry author’s analysis and recommendation, not independent evidence that a particular tool will resolve the problem. Read the BusinessCloud article.
What creates the gap
Data silos and sprawling infrastructure
Information may be copied between databases, cloud services, warehouses, and applications. Each new location or copy can make it harder to maintain a reliable inventory and apply consistent controls. Data outside expected inventories—sometimes called shadow data—can be especially difficult to discover and govern.
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Unclear ownership and access rules
If teams cannot determine who owns a dataset, who is allowed to use it, and for what purpose, they may default either to broad permissions or to blocking access. Both approaches create risk: unnecessary exposure in the first case, and operational friction in the second.
Changing obligations and threats
Privacy and compliance requirements vary by jurisdiction and context, and security teams must account for changing risks, including insider misuse and attacks involving suppliers. The 2023 article discusses these pressures, but it does not provide a current threat measurement or a jurisdiction-specific legal analysis. Organizations should map their own applicable obligations with qualified legal and compliance advisers.
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What the 2023 survey figures do—and do not—show
The following figures were reported by Immuta in a September 2023 release describing an IDC InfoBrief sponsored by Immuta. The release says the findings draw on 108 European organizations. They describe that survey period, not conditions in 2026, and should not be generalized to all organizations or regions. The original survey instrument and methodology are not independently established by the release.
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| Reported finding | Scope and timing |
|---|---|
| 29% said data security challenges prevented them from fully using data within their organization. | European organizations; IDC findings from 2023, reported by Immuta. |
| 42% were confident or highly confident in discovering and classifying known and unknown sensitive data in public cloud. | European businesses; IDC findings from 2023, reported by Immuta. |
| 45% planned to prioritize spending on data security, risk, and compliance in 2023. | European organizations; reported plans for 2023 in IDC findings reported by Immuta. |
| 58% reported an increase in cyberattacks in the preceding 12 months; corresponding reported figures were 49% in DACH and 47% in the Nordics. | UK organizations, DACH, and the Nordics respectively; IDC findings reported in 2023 by Immuta. |
| 49% planned to expand or upgrade data access controls in the following 12 months; 32% intended to increase spending on data discovery and classification. | Security respondents for the access-control figure and European organizations for the discovery/classification figure; IDC findings reported in 2023 by Immuta. |
See Immuta’s September 2023 account of the IDC InfoBrief. Because the report was sponsored by Immuta, treat these numbers as attributed survey findings rather than neutral, current benchmarks.
Build a practical data-security foundation
1. Find and classify the data
Create an inventory that includes the environments where sensitive data is stored, the systems that process it, and known copies. Classification should identify relevant sensitivity levels and support the controls attached to them. Include cloud services and less obvious locations rather than relying only on documented central repositories.
2. Define access by user, purpose, and data
Document who needs access, what data they need, and why. Set permissions to match approved work, then establish a process for reviewing and changing them as roles, projects, and datasets change. A control is only useful if teams can apply it consistently without making legitimate work impractical.
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3. Audit use and policy application
Keep records that let responsible teams review access and understand whether policies are being applied as intended. Decide who reviews those records, how exceptions are handled, and what conditions trigger investigation. An access rule without a way to assess its operation may leave teams unable to spot drift or explain actual use.
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4. Prepare for incidents
Data access governance is one part of protection, not a replacement for detecting, responding to, and recovering from a breach. NIST Special Publication 1800-29, published in February 2024, provides guidance and example technologies for those operational capabilities in the context of data confidentiality attacks. Consult NIST SP 1800-29.
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Questions to ask when evaluating a platform or approach
Evaluate capabilities against your actual architecture and operating needs. The questions below are a decision framework, not a scored comparison of products.
- Discovery and classification: Can the approach find sensitive data—including unknown data—across the environments the organization actually uses?
- Access control: Can policies consistently limit access to approved users, data, and purposes?
- Auditability: Can teams review who accessed data and determine how policies were applied?
- Architecture fit: Does the approach work across the organization’s clouds, warehouses, and other relevant data platforms?
- Operational fit: Can security, data, and compliance teams implement and maintain the controls without needlessly obstructing authorized work?
Ask vendors to demonstrate these capabilities using representative workflows and environments, and distinguish demonstrated functionality from product positioning. A coordinated platform can be one component of a broader program; selecting one does not by itself establish that data is comprehensively inventoried, appropriately governed, or prepared for incident response.
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