Best 9 Data-Centric Security Software For Enterprise (2026)
We reviewed 9 data-centric security platforms on classification accuracy, policy enforcement across storage locations, and how well each controls access to sensitive data when it leaves managed environments.
Written by
Alex Zawalnyski
Technical Review by
Laura Iannini
Quick Summary
Data-centric security software protects sensitive information at the data layer — through classification, encryption, and access controls — regardless of where that data moves or is stored. Unlike perimeter-based security, data-centric approaches ensure protection travels with the data itself. We reviewed 9 platforms and found Thales DSPM, Aikido Security, and BigID Data Security Platform to be the strongest on classification accuracy and policy enforcement consistency.
Data-centric security means treating sensitive data as your primary security perimeter. Most organizations have security controls at the network and application layers, but when attackers breach those boundaries, uncontrolled data access creates catastrophic exposure. Ransomware operators don’t care about your firewall quality, they care about finding your most valuable data and encrypting it before you can stop them.
Knowing that sensitive data exists is the easy part. Understanding where it lives, who can access it, whether those permissions are justified, and what attack paths could expose it. You need tools that discover sensitive data across infrastructure you probably don’t fully control, classify it without manual tagging, and show you the path an attacker could take from initial compromise to your most valuable assets.
We evaluated multiple data-centric security platforms across discovery accuracy, classification precision, access control visibility, attack path analysis, and real-world remediation capabilities. We evaluated across cloud, hybrid, and on-premises environments with varying data types, structured databases, unstructured file systems, alongside SaaS applications and legacy systems. We assessed whether platforms helped teams actually remediate exposure or just generate more alerts nobody acts on.
Our Recommendations
We found that data-centric security often falls into the trap of generating alerts without context. The strongest tools don’t just find data, and they show you which data matters and why, then connect that to actual risk.
- Best For Legacy and Hybrid Database Environments: Thales Data Security: Supports 65+ data repository types across legacy, cloud, and hybrid architectures.
- Best For Agentless Cloud Data Discovery: Wiz DSPM: Agentless deployment connects to cloud accounts and starts scanning within hours.
- Best For Developer-Focused AppSec: Aikido Security: Unified platform replaces multiple point solutions for SAST, SCA, IaC, and container scanning.
- Best For ML-Driven Data Classification: BigID Data Security Platform: ML-driven classification accurately identifies sensitive data across petabytes of information.
- Best For Semantic Data Understanding: Concentric AI Semantic Intelligence: Semantic classification understands data context, cutting false positives versus regex-based tools.
- Best For Real-Time Threat Detection: Dig Security Data Detection and Response: Real-time DDR detects ransomware and exfiltration attempts before damage occurs across cloud providers.
- Best For Privacy and Compliance Integration: Securiti Data Security Posture Management: Unified platform combines DSPM with privacy automation including DSR and consent management.
- Best For SIEM and Advanced Query Flexibility: Splunk Enterprise Security: SPL and schema-on-read enable flexible queries against unstructured data without predefined schemas.
- Best For Automated Remediation at Scale: Varonis: Automated remediation fixes broken ACLs and open access at scale without manual intervention.
Thales DSPM
Thales is a strong choice for organizations that need a data security posture management platform built for multi-cloud environments. At the center of the offering is the CipherTrust Data Security Platform, and the key differentiator is that CipherTrust doesn’t just identify where sensitive data lives and hand off to third-party tools for protection. It runs the full encryption, tokenization, and key management stack natively.
Thales DSPM Key Features
Thales unifies data discovery, classification, encryption, tokenization, dynamic data masking, and centralized key management in a single environment. Most cloud-native DSPM tools concentrate on visibility and posture assessment, relying on external integrations to enforce protection controls. The platform applies format-preserving encryption, vaultless tokenization, and dynamic masking directly at the data layer, across structured and unstructured stores, covering AWS, Azure, GCP, on-premise databases, and SaaS environments.
It also addresses agentic AI and generative AI workloads. Policy-driven controls ensure that RAG pipelines, fine-tuned models, and AI agents can only access data they’re explicitly authorized to consume, and that sensitive data is encrypted or masked before it reaches AI systems. File Activity Monitoring extends visibility into unstructured data access patterns and user behavior across servers, cloud services, and file shares, adding operational telemetry to posture management. Thales also integrates existing IAM and Hardware Security Module capabilities for granular identity governance and access control, with FIPS 140-3 Level 3 compliant HSM support.
Our Take
We think Thales is a strong option for organizations that need a single platform covering discovery, classification, and native data protection without relying on multiple vendors. The case is particularly strong for regulated industries and organizations with on-premise or hybrid infrastructure, where cloud-native DSPM tools often fall short. If your security requirements include full encryption key ownership, tokenization, and data masking enforced at the data layer across cloud and on-premise environments, Thales is well worth the investment.
Strengths
- Deep database activity monitoring with AI-powered risk analysis
- Encryption and key management capabilities
- Real-time intrusion detection across on-prem and cloud databases
- Covers both structured and unstructured data classificatiNative encryption, tokenization, and dynamic data masking with no third-party dependency for core protection
- Centralized key management natively integrated within the platform
- Consistent discovery, classification, and protection across multi-cloud, hybrid, and on-premise environments
- AI and agentic AI data security controls enforced at the data layer
- Comprehensive posture evaluation, risk assessment, and continuous monitoring across all data environments
Cautions
- Initial setup complexity for teams without prior data security platform experience
Aikido Security is a code, cloud, and runtime security platform that helps developers find and fix vulnerabilities in their code and applications. It helps protect against data loss by improving the security of applications from code to runtime, with auto-triage and auto-remediation features powered by AI.
Aikido Security Key Features
Aikido’s biggest strength is that it consolidates multiple application scanning features into a single, easy-to-use platform. It offers a wide range of scanning tools, including scanning source code (SAST), software components (SCA), infrastructure components (IaC), APIs, and cloud infrastructure (CSPM) for vulnerabilities. It uses open-source engines and its own proprietary engines to scan code. It also integrates with compliance platforms and can detect compliance misconfigurations for SOC 2, ISO 27001, and more. Meanwhile, Aikido’s runtime security solution, Zen, enables you to monitor and control network traffic. It automatically blocks inbound network risks and provides reporting.
Aikido prioritizes vulnerabilities based on severity and uses AI to help developers fix issues faster. Its AI AutoTriage tool summarizes risks and provides recommendations, while the AI AutoFix tool can actually generate code to fix CVEs, misconfigurations, and vulnerabilities. The platform is secure; it never requires access to any of your code, and only needs read-only access to your code repositories.
Our Take
Aikido offers a free plan for up to two developers. Paid plans start at $350 USD per month for up to 10 users. We recommend Aikido for developers looking to shift left, moving data-centric security to the code and application level. The platform is a strong choice for both startups and large teams of developers.
Strengths
- AI AutoTriage summarizes risks; AI AutoFix generates code to fix vulnerabilities
- Consolidates SAST, SCA, IaC, API scanning, and CSPM into one platform
- Runtime security via Zen blocks inbound network threats automatically
- Read-only access model; never edits your code
- Free plan available; paid plans start at $350 USD per month
Cautions
- Breadth of features may be more than smaller teams with simple testing needs require
BigID
BigID is an enterprise data security platform that unifies DSPM, AI security posture management, cloud DLP, and data access governance in one solution. We think it fits organizations that need deep visibility into where sensitive data lives, who accesses it, and how it flows across multicloud, SaaS, and hybrid environments. The platform covers structured, unstructured, and semi-structured data at scale.
BigID Key Features
We found the identity-aware discovery particularly strong; BigID links data risk to real user identities rather than just storage locations, which gives security teams actionable context. The platform now includes agentic remediation that uses AI-guided prioritization to tell you what to fix first and how to fix it. AI security posture management assesses model and agent vulnerabilities, controls access, and flags sensitive data use within AI systems. AskBigID GPT lets users query their entire risk posture in plain language, which is good to see for making data security accessible to non-technical stakeholders.
What Customers Say
Customers praise the depth of data discovery and classification accuracy across complex environments. The platform’s flexibility in handling diverse data types gets high marks. Something to be aware of is that initial configuration and tuning require significant investment, and some users report the interface can feel dense when navigating large-scale deployments.
Our Take
We think BigID hits the mark for enterprises that need a single platform covering data security, privacy, and AI governance. The identity-aware approach adds context that pure classification tools miss. If your priority is understanding not just where sensitive data is but who touches it and why, BigID is well worth considering.
Strengths
- Identity-aware discovery links data risk to real users
- Agentic AI-guided remediation with prioritized fix recommendations
- Covers structured, unstructured, and semi-structured data across multicloud
- AI security posture management for model and agent governance
Cautions
- Customers note initial configuration requires significant investment
- Reviews mention the interface feels dense in large-scale deployments
Concentric AI
Concentric AI is a data security governance platform that uses context-aware AI to discover, classify, and protect sensitive data across cloud and on-prem environments. We think it works well for organizations that need autonomous data security with minimal manual rule-writing. The platform uses natural language processing to understand the meaning of content rather than relying solely on pattern matching.
Concentric AI Key Features
The NLP-based classification stood out in our review; it reads content contextually rather than just scanning for regex patterns, which improves accuracy on unstructured data. The platform discovers sensitive data regardless of storage location, monitors risk continuously, and automates remediation actions. Concentric AI has added GenAI data security capabilities that protect sensitive data from entering or leaking through tools like Copilot, Gemini, and ChatGPT, which is good to see as AI adoption accelerates. The platform also supports CMMC compliance workflows for organizations in the defense supply chain.
What Customers Say
Customers highlight the accuracy of autonomous classification and the reduction in manual policy creation. The platform’s ability to surface risks without extensive rule configuration gets positive feedback. Something to be aware of is that some users report the reporting interface could be more customizable, and integration with certain legacy systems requires additional configuration.
Our Take
We think Concentric AI fits organizations that want data classification driven by content understanding rather than rigid rules. The NLP approach reduces false positives on unstructured data where pattern matching struggles. If your environment includes diverse data types and you want to minimize manual policy management, this is a good option to evaluate.
Strengths
- NLP-based classification understands content context, not just patterns
- Autonomous risk monitoring with automated remediation
- GenAI data security prevents leakage through AI tools
- Minimal manual rule-writing required for accurate classification
Cautions
- Users report the reporting interface could be more customizable
- Reviews mention legacy system integrations require extra configuration
Dig Security (Palo Alto Networks)
Dig Security provides DSPM and data detection and response capabilities, now integrated into Palo Alto Networks’ cloud security platform following its acquisition in December 2023. We think it fits organizations already invested in the Palo Alto ecosystem that want agentless data security across their cloud estate. The DSPM module provides sensitive data mapping within 24 hours without connectors.
Dig Security Key Features
The agentless approach is a real strength; Dig analyzes cloud logs, backups, and snapshots to discover and classify data without deploying agents or proxies. We found the speed of initial discovery impressive, with complete sensitive data mapping achievable within 24 hours. Data detection and response capabilities monitor for real-time threats to sensitive data. The integration with the broader cloud security platform means DSPM findings connect directly to workload vulnerabilities, identity risks, and network exposure for full attack path analysis.
What Customers Say
Customers praise the speed of deployment and the agentless architecture that avoids performance overhead. The data classification accuracy across diverse cloud data stores gets positive feedback. Something to be aware of is that the platform is now tightly coupled with the broader cloud security suite; organizations not using other Palo Alto products may find the standalone DSPM value harder to access. The legacy Prisma Cloud Data Security module reached end of sale in August 2024.
Our Take
We think Dig Security works best for organizations already running Palo Alto’s cloud security platform. The agentless DSPM and data detection capabilities are strong, and the integration with the wider security stack adds context that standalone tools lack. If you need cloud-native data security within an existing Palo Alto environment, this is well worth considering.
Strengths
- Agentless architecture with no performance overhead
- Sensitive data mapping within 24 hours of deployment
- Data detection and response for real-time threat monitoring
- Full attack path context through platform integration
Cautions
- Users report standalone DSPM value is harder to access outside the Palo Alto ecosystem
- Reviews note the legacy data security module has reached end of sale
Securiti
Securiti’s Data Command Center is a unified platform for data security, privacy, governance, and AI trust across hybrid multicloud environments. Following its $1.7 billion acquisition by Veeam in December 2025, the platform now combines data resilience with DSPM and AI governance. We think it fits enterprises that need a single platform spanning data discovery, access governance, privacy automation, and compliance.
Securiti Key Features
The platform’s knowledge graph architecture stood out in our review; it connects data assets, identities, regulations, and policies in a unified model that drives automated decisions. Securiti automatically discovers cloud-native, shadow, and dark data assets using AI-powered contextual classification. Breach impact analysis with automated notification workflows is particularly useful for incident response. The platform has added AI governance capabilities including Agent Commander for managing enterprise AI agent access, and prompt and response firewalls for protecting AI interactions, which is good to see as organizations scale AI adoption.
What Customers Say
Customers praise the breadth of capabilities and the unified approach to data security and privacy. The automated compliance workflows save significant manual effort. Something to be aware of is that the platform’s depth means onboarding takes longer than simpler point solutions, and some users report the learning curve is steep for teams new to DSPM and privacy automation.
Our Take
We think Securiti fits organizations that want data security, privacy, and AI governance unified in one platform rather than stitched together from multiple tools. The knowledge graph approach provides context that siloed tools miss. The Veeam acquisition adds data resilience and recovery capabilities to the mix. If you need a platform that spans DSPM, privacy, and AI trust, Securiti is well worth evaluating.
Strengths
- Knowledge graph architecture connects data, identities, and regulations
- Automated breach impact analysis with notification workflows
- AI governance with agent access controls and prompt firewalls
- Veeam integration adds data resilience and recovery capabilities
Cautions
- Customers note onboarding takes longer than simpler point solutions
- Reviews mention a steep learning curve for teams new to DSPM
Splunk Enterprise Security
Splunk Enterprise Security is a threat detection, investigation, and response platform that now sits within Cisco’s security portfolio following its $28 billion acquisition in March 2024. We think it fits security operations teams that need data-aware threat detection with deep analytics across large, diverse data environments. The platform ingests and correlates security data at scale to surface threats targeting sensitive information.
Splunk Enterprise Security Key Features
We found the analytics-driven approach effective for identifying data-centric threats; the platform correlates events across endpoints, network, cloud, and identity sources to surface attack patterns that target sensitive data. The 2026 release adds agentic AI capabilities including a Triage Agent for automated alert investigation, AI Playbook Authoring, and a Personalized Detection SPL Generator. Cisco Talos threat intelligence is now integrated directly, which is good to see for enriching detections with real-world threat context. Splunk Enterprise Security is available in two editions: Premier bundles UEBA, SOAR, and the AI Assistant; Essentials provides a lighter entry point with detection and the AI Assistant.
What Customers Say
Customers praise the depth of analytics and the flexibility to build custom detections. The correlation engine’s ability to surface complex attack patterns gets strong feedback. Something to be aware of is that licensing costs scale with data ingestion volume, which can become expensive for organizations with large data footprints. The query language has a learning curve for analysts without prior experience.
Our Take
We think Splunk Enterprise Security fits organizations that need analytics-driven data threat detection at scale. The Cisco integration strengthens the threat intelligence and network visibility story. The new agentic AI capabilities should reduce analyst workload on triage and investigation. If your data security strategy needs a strong detection and response layer, this is a serious option to consider.
Strengths
- Analytics-driven detection correlates events across diverse data sources
- Agentic AI for automated triage, playbooks, and detection generation
- Cisco Talos threat intelligence integrated directly
- Two editions for different organizational needs and budgets
Cautions
- Users report licensing costs scale steeply with data ingestion volume
- Customers note the query language has a learning curve for new analysts
Varonis
Varonis is a data security platform that combines DSPM, data access governance, data detection and response, and automated remediation in a single SaaS solution. We think it fits enterprises with large unstructured data estates across cloud and on-prem environments that need to reduce overexposed data and detect insider threats. The platform is built around an access graph that maps who can reach what data and how.
Varonis Key Features
The access graph is the standout capability; it factors in entitlements, group memberships, sharing links, and inherited permissions to show the true blast radius of any user account. Automated remediation removes stale permissions without human intervention, which directly shrinks the attack surface. The forensic audit trail logs every data access event, permission change, and sharing action with full attribution. Varonis launched Managed Data Detection and Response in 2026 with a 30-minute SLA for ransomware detection, which is good to see for organizations that need 24/7 coverage. The platform also acquired AllTrue.ai to add AI trust and risk management, governing how internal AI models access sensitive data.
What Customers Say
Customers praise the granularity of access visibility and the automated remediation of overexposed data. The forensic audit trail is frequently highlighted for incident investigation. Something to be aware of is that initial deployment and data scanning across large environments takes time, and some users report the volume of findings in the early stages requires careful prioritization to avoid alert fatigue.
Our Take
We think Varonis fits organizations where overexposed data and stale permissions are the primary risk. The automated remediation is a genuine differentiator; most platforms tell you what’s wrong but leave you to fix it manually. The MDDR service adds a managed layer for organizations without 24/7 security operations. If reducing your data blast radius is the priority, Varonis is a very strong option.
Strengths
- Access graph maps true data blast radius across permissions and sharing
- Automated remediation removes stale permissions without manual effort
- 30-minute SLA ransomware detection through managed DDR service
- AI trust management governs how models access sensitive data
Cautions
- Users report initial scanning across large environments takes significant time
- Reviews mention early-stage finding volume requires careful prioritization
Wiz
Wiz provides DSPM within a unified cloud security platform that connects data risk to identity, misconfiguration, workload posture, and real attack paths. Following its $32 billion acquisition by Google, completed in March 2026, Wiz operates within Google Cloud while maintaining its multi-cloud commitment. We think it fits cloud-native organizations that want data security integrated with their broader cloud security posture rather than bolted on as a separate tool.
Wiz Key Features
The security graph is the core differentiator; it connects sensitive data findings to identity risks, misconfigurations, and exploitable attack paths so you can prioritize based on real exposure rather than classification severity alone. Agentless scanning discovers and classifies sensitive data including PCI, PII, PHI, and secrets across storage buckets, databases, serverless functions, data warehouses, and third-party platforms like Snowflake and OpenAI. No agents means new data stores are discovered automatically as your cloud environment changes. Wiz has expanded into DSPM for AI, covering training datasets, vector databases, embedding stores, and inference pipelines, which is good to see for organizations building AI workloads.
What Customers Say
Customers highlight the speed of deployment and the clarity of the security graph for prioritizing data risks. The agentless architecture and multi-cloud coverage get consistently strong feedback. Something to be aware of is that some users report the DSPM capabilities are still maturing compared to the core cloud security features, and granular policy customization for data classification rules has room for improvement.
Our Take
We think Wiz fits cloud-native organizations that want DSPM embedded within their cloud security platform rather than operating as a standalone data security tool. The attack path context is a real advantage; knowing data is sensitive is useful, but knowing it’s sensitive and reachable through a misconfigured identity is actionable. If your data security needs are cloud-first and you want unified visibility, Wiz is well worth evaluating.
Strengths
- Security graph connects data risk to attack paths and identity exposure
- Agentless scanning across storage, databases, serverless, and AI platforms
- DSPM for AI covers training data, vector databases, and inference pipelines
- Multi-cloud support maintained post-Google acquisition
Cautions
- Reviews mention DSPM features are still maturing compared to core cloud security
- Users report granular data classification policy customization has room for improvement
What To Look For: Data-Centric Security Checklist
When evaluating data-centric security platforms, we’ve identified six core criteria that determine whether a tool helps you prioritize real exposure or just generates more alerts.
- Automated Discovery and Classification: Can the platform discover sensitive data across your infrastructure without manual tagging? Does it classify PII, PHI, PCI accurately without extensive tuning? Can it handle both structured databases and unstructured file systems? Does it discover shadow data in systems you didn’t know existed?
- Access Control and Permission Visibility: Can it show who has access to sensitive data and whether those permissions are appropriate? Does it surface permission misconfiguration and orphaned access? Can it map effective permissions across complex environments? Does it highlight overexposed data?
- Attack Path Analysis: Can it show you how an attacker could move from initial compromise to your sensitive data? Does it factor in misconfigurations, vulnerabilities, and access controls together? Can it prioritize exposure based on realistic attack paths rather than theoretical risk?
- Remediation Capabilities: Can the platform help you fix exposure automatically, or does it leave remediation entirely to you? Does it integrate with your ticketing systems to drive action? Can it track remediation progress and verify fixes were actually applied? For tools with automation, how reliable is it?
- Real-Time Monitoring: Does it provide continuous monitoring of data access and unusual behavior, or just point-in-time scanning? Can it detect exfiltration or ransomware activity in real time? Does monitoring work across cloud, hybrid, and on-premises infrastructure? How quickly does it alert on suspicious patterns?
- Integration and Deployment: Does it require agents on every system, or can it scan agentless? How deeply does it integrate with your existing security stack (SIEM, SOAR, DLP)? How long does deployment take in complex environments? Can you start seeing value immediately or do you need months of configuration?
Weight these criteria based on your environment. If you have significant legacy infrastructure with permission sprawl, remediation capabilities matter most. If you’re multi-cloud with fast-moving workloads, real-time monitoring and agentless deployment are critical. If you’re audit-focused, compliance automation and evidence generation matter. If you lack dedicated security staff, ease of deployment and vendor support quality are worth premium pricing.
How We Compared The Best Data-Centric Security Software
Expert Insights independently researches, tests, and reviews B2B security and data protection solutions. Editorial assessments reflect product quality and operational usability. Vendor relationships do not influence our evaluations.
We evaluated 9 data-centric security platforms across discovery accuracy, classification precision, access control visibility, attack path analysis, remediation capabilities, and real-time monitoring. Each platform was deployed in test environments simulating enterprise data scenarios spanning cloud and hybrid, plus on-premises infrastructure with mixed data types, permission models, and threat contexts. We assessed discovery false positive rates, classification accuracy, alongside remediation effectiveness and whether platforms actually reduced data exposure or just created more work.
Beyond hands-on testing, we conducted market research across the data security market and collected customer feedback to validate vendor claims against operational reality. We spoke with security operations teams about their actual workflows and which capabilities they relied on versus which features they ignored. Our editorial and commercial teams remain independent throughout.
This guide is updated quarterly with fresh testing and customer interviews. For our complete testing methodology details, visit our How We Test & Review Products.
The Bottom Line
Data-centric security succeeds when tools reduce noise and drive actual remediation.
For multi-cloud environments where you need agentless deployment and attack path context, Wiz DSPM delivers the fastest time-to-value. The Security Graph integration shows realistic exposure, not theoretical risk.
If you need threat detection alongside posture management, Dig Security adds real-time DDR to DSPM capabilities. The multi-cloud support and executive reporting reduce alert fatigue.
If your organization has unstructured data sprawl and permission debt, Varonis automates remediation at scale. The managed detection service adds analyst coverage without hiring.
For enterprises with legacy database footprints transitioning to cloud, Imperva Data Security handles 65+ repository types that pure-cloud tools cannot reach. BigID Data Security Platform handles petabyte-scale classification. Concentric AI cuts false positives through semantic classification. Securiti Data Security Posture Management unifies DSPM with privacy automation. Splunk Enterprise Security provides SIEM flexibility for mature security operations. Aikido Security consolidates AppSec scanning for dev teams.
Read the detailed reviews above for implementation complexity, deployment timelines, pricing, and specific capabilities that matter for your data environment and team maturity.
FAQs
Everything You Need To Know About Data-Centric Security (DCS) Software (FAQs)
Data-Centric Security (DCS) is there term used to describe a specific data storage philosophy. It prioritizes securing, protecting, and managing data at a granular level, rather than focusing on the systems and networks where data is held. Where cybersecurity is often likened to a castle with a firewall or EDR solution being the outer perimeter, DCS looks to secure the people (data) within the bounds directly.
The approach makes sense. Focus on protecting the thing that you’re trying to protect: data.
One of the benefits of this approach is that a network or device breach does not directly put information at risk. Equally, if an attacker is able to decrypt a piece of data, they will only have access to that one piece. You do not have to worry about all of the information stored on that device being at risk.
Data-centric security works by securing data at the earliest point possible, at its most fundamental level. This results in effective security that is fully integrated with the data lifecycle, rather than being applied at a later point.
Data-centric security solutions incorporate multiple techniques and processes to ensure that your data is managed effectively and kept secure. Common features of a DCS solution include data encryption, access controls, data classification and auditing, data governance, and data loss prevention. Together, these solutions bring an effective and robust level of security, effectively securing your important information at its most fundamental level.
- Data Encryption – By encrypting data you can ensure that it is only readable by users with the means to decrypt it. This makes it virtually impossible for unauthorised users to make sense of your data. One of the most secure encryption standards is AES-256.
- Access Controls – You can secure data by ensuring that specific, pre-approved users are able to access the data. This is often controlled by a Privileged Access Management (PAM) solution which enforces multi-factor authentication, role-based access, and passwords.
- Data Classification and Auditing – This means that you data is accurately classified and searchable. In doing this, you can ensure that all data is treated effectively and has the appropriate level of controls applied.
- Data Governance – By setting and enforcing standards across your organization, you can ensure that data is always handled, accessed, and managed appropriately, thereby reducing the chances of a breach.
- Data Loss Prevention (DLP) – This puts measures into place to prevent data from being lost or stolen and gives you a means of recovering it this does happen (either intentionally or maliciously).
Data-Centric-Security solutions are technically advanced and complex solutions. As such, it can be difficult to understand which features to look for when selecting a solution. In this section we’ll highlight some of the key features that you should look for when choosing a data-centric security solution.
- Effective Data Discovery – As DCS solution work by focusing on securing data rather than the device, it is essential that your platform can discover and identify all data within your network. If a platform is unable to do this, there could well be large amounts of data that have no form of encryption or security protecting them.
- Accurate Data Tagging – Organizations will have different types of data that are used for different purposes and have different security requirements. To help facilitate this, your solution needs to accurately tag data to ensure it has the right security controls applied.
- Range Of Capabilities – While this isn’t exactly a single feature, it is worth looking for. Your platform should offer a range of capabilities to allow for data to be managed in an effective way. These capabilities should include data encryption, access controls, data classification, auditing, data governance, and data loss prevention.
- Encryption At Rest And Transit – Data is often particularly vulnerable to being targeted whilst in transit. For this reason, it is important that your solution automatically encrypts data at rest and when in transit, thereby reducing the opportunities for attackers to gain access.
- Consistent Monitoring – A security platform that monitors and analyses information access and user behavior can improve processes to ensure that they are as secure and effective as possible. Consistent monitoring also eases the compliance and auditing process, ensuring that you have evidence of your secure practices for relevant parties.
This is not an exhaustive list of the features that a DCS platform can deliver, rather it is a starting point, highlighting some of the most useful features. It is worth taking the time to assess your organization’s own unique use-case and needs, before selecting a solution.
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Written By
Alex is an experienced journalist and content editor. He researches, writes, factchecks and edits articles relating to B2B cyber security and technology solutions, working alongside software experts.
Alex was awarded a First Class MA (Hons) in English and Scottish Literature by the University of Edinburgh.
Technical Review
Laura Iannini is a Cybersecurity Analyst at Expert Insights. With deep cybersecurity knowledge and strong research skills, she leads Expert Insights’ product testing team, conducting thorough tests of product features and in-depth industry analysis to ensure that Expert Insights’ product reviews are definitive and insightful.
Laura also carries out wider analysis of vendor landscapes and industry trends to inform Expert Insights’ enterprise cybersecurity buyers’ guides, covering topics such as security awareness training, cloud backup and recovery, email security, and network monitoring. Prior to working at Expert Insights, Laura worked as a Senior Information Security Engineer at Constant Edge, where she tested cybersecurity solutions, carried out product demos, and provided high-quality ongoing technical support.
Laura holds a Bachelor’s degree in Cybersecurity from the University of West Florida.