Key Takeaway
On-prem data remains critical to business operations and should not be overlooked. With the right discovery methods and deployment models, it is possible to apply consistent security standards across both on-prem and cloud environments.
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Securing on-premises data often feels slow and complex, but it doesn't have to be.
Despite years of cloud adoption, 39% of organizations still store most of their data on-prem. This data powers regulated workloads, legacy systems, high-performance applications, and core business operations. It also holds some of the most sensitive personal data and proprietary business IP in the enterprise.
Yet on-prem environments are consistently the least visible and hardest to secure. As data estates sprawl across on-prem, SaaS, DBaaS, and IaaS environments, and as AI systems begin consuming data at machine speed, the challenge grows.
This blog examines how to stop treating on-prem security as a legacy chore and start treating it as a strategic strength.
3 Practical Steps to Modernize On-Prem Data Discovery
Reducing scan times from months to days requires a shift in technical approach. Here is how Cyera addresses the scale and complexity of on-prem environments:
1. Replace heavy agents with smart sampling
Legacy tools often attempt to scan every file in full, which can overwhelm infrastructure and impact performance.
A more efficient approach is to use sampling and clustering. By analyzing representative portions of databases and grouping similar files, it is possible to classify large volumes of data quickly and with minimal impact on infrastructure and performance. For example, classifying 130 TB in under 24 hours is achievable without the overhead of full scans.
2. Move from pattern matching to AI-native object-level classification
Traditional tools rely on pattern matching, which works for known patterns in structured data like credit card numbers. However, this approach often misses sensitive information in unstructured data such as intellectual property or legal documents.
Object-level classification uses AI, among other methods, to understand the context and intent of documents, not just search for patterns. This approach can identify sensitive data that traditional rules-based systems overlook and can achieve high levels of precision (95%+) in large-scale environments.
3. Reduce deployment friction with connector-less architecture
Managing connectors and agents is often a significant, hidden cost in on-prem security projects. A connector-less architecture allows data to remain within the organization's network while still enabling advanced analysis. This reduces deployment time and complexity, providing visibility much faster than traditional approaches that require lengthy infrastructure changes. If connector-less deployment is not possible, Cyera’sa lightweight connector-based deploymentapproach can achieve similar outcomes.
What this approach delivers in practice
Teams using these methods by Cyera have seen results that legacy tools struggle to achieve:
- Scale: Scanned 82 million NetApp files in 40 days.
- Speed: Classified 100 TB of file server data in under 3 days.
- Efficiency: Reduced breach likelihood by 80% by remediating high-risk exposures, not just reporting on them.
How Cyera Helps Secure On-Prem Data
Cyera’s DSPM platform helps organizations secure on-prem data by delivering autonomous discovery, enriched classification, and actionable insights that enable confident remediation at scale.
Here’s how the platform works in practice:
- Fast deployment: Connector-less deployment delivers complete data visibility and rapid time to value-without ongoing connector maintenance or operational drag.
- Classification teams can trust: Cyera’s enriched classification uncovers sensitive data across structured and unstructured sources, including what is unique to your business. Built on an AI-native engine, Cyera continuously adapts to your environment based on business context and classifies data automatically, without manual tuning or rule maintenance.
- Data, Identity, and Access Convergence: Map every data asset to human and non-human identities, understand who can and did access it, and enforce least-privilege controls.
- Effective Prioritization: AI-driven severity scoring correlates sensitivity, identity, and exposure to surface the highest-impact risks-dramatically reducing noise for analysts.
- Actionable Insights: Address risks with confidence by using insights that are based on trusted data or by routing issues with context directly to data owners.
This approach gives teams the visibility, context, and speed required to reduce risk and support compliance across on-prem and cloud environments.
Get the Buyer’s Guide for a step-by-step checklist on evaluating modern DSPM for on-prem environments at enterprise scale.
FAQ About Securing On-Prem Data at Scale
Q.) What is on-prem data security?
On-prem data security focuses on protecting sensitive data stored in on-premises systems such as databases, file shares, and legacy platforms. It includes discovery, classification, access visibility, and remediation to reduce exposure and support compliance.
Q.) Why is on-prem data security still important?
Many enterprises keep regulated workloads on-prem for performance and compliance reasons, including frameworks such as GDPR and HIPAA, which require strong visibility and access controls.
Q.) Why is on-prem data risk increasing?
Hybrid environments are now the norm. Many organizations keep sensitive workloads on-prem. As on-prem data volumes grow and become accessible to AI and automation, misclassified or exposed data can be misused at scale. This makes security controls for the data that powers AI systems essential.
Q.) How does Cyera DSPM improve on-prem data security?
Cyera DSPM provides autonomous discovery, enriched classification, and proactive remediation across on-prem data stores. Unlike traditional DSPM tools, Cyera automatically adapts as data changes and helps teams focus on the highest-impact risks using a modern DSPM platform.
Q.) How does Cyera discover on-prem data without disrupting operations?
Cyera supports connector-less and lightweight connector-based discovery using smart sampling, clustering, and change-based monitoring.
Q.) Does Cyera require agents or heavy connectors?
No. Cyera supports fully connector-less deployments and a lightweight connector option.
Q.) How is Cyera’s classification different from traditional tools?
Traditional tools rely on static pattern matching. Cyera uses an AI-native, adaptive classification engine that applies regular expressions, machine learning, and fine-tuned LLMs based on data type, enabling classification in the full business context with 95%+ precision.
Q.) How does Cyera help prioritize real on-prem data risk?
Cyera enriches data with context such as sensitivity, business purpose, identities, access, and exposure conditions. AI-driven severity scoring correlates these signals to highlight the highest-impact risks and reduce noise.
Q.) How does on-prem data security fit into hybrid environments?
Cyera unifies data security across on-prem, SaaS, DBaaS, and IaaS environments, enabling consistent policies, correlated risk analysis, and end-to-end visibility across hybrid data estates.
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