Best Data-Centric Security Software
Discover the top data-centric security software with features like data classification, data-at-rest protection, and access controls.
Written by
Alex Zawalnyski
Technical Review by
Laura Iannini
Quick Summary
For security teams running multi-cloud environments, Wiz DSPM tracks sensitive data without agent sprawl while showing attack paths to critical information from one agentless platform.
For development teams shifting left without tool sprawl, Aikido Security consolidates SAST, SCA, IaC, secrets, and container scanning into one place with AI-powered auto-triage.
For organizations managing sensitive data across cloud, hybrid, and on-premises environments, BigID Data Security Platform uses machine learning to identify critical and regulated data at scale.
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 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 Legacy and Hybrid Database Environments: Imperva Data Security: Supports 65+ data repository types across legacy, cloud, and hybrid architectures.
- 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.
Aikido consolidates application security scanning into a single platform built for dev teams who want to shift left without drowning in tool sprawl. It covers SAST, SCA, IaC, secrets, container scanning, and cloud posture in one place.
All Your AppSec Scanning in One Place
The platform pulls together scanning capabilities that would normally require four or five separate tools. We found the auto-triage particularly effective at cutting through noise. Reachability analysis filters out false positives so you focus on vulnerabilities that actually matter in your environment.
Setup is fast. Connect your GitHub repos or domains and scanning starts immediately. The AI AutoFix feature generates remediation code for CVEs and misconfigurations. Read-only repo access means Aikido never touches your actual codebase.
What Customers Are Saying
The UI consistently gets praise for being clean and intuitive. Engineers can identify, prioritize, and remediate issues without security team hand-holding. PR integration catches issues before they merge.
Some customer reviews mention that customers flag pricing concerns, especially smaller teams, however.
Right Fit for Your Team?
We think Aikido works best for startups and dev teams prioritizing speed and simplicity over enterprise security reporting. If you need detailed posture assessments or detailed compliance documentation, you may find the reporting too lightweight.
Strengths
- Unified platform replaces multiple point solutions for SAST, SCA, IaC, and container scanning
- AI-powered auto-triage uses reachability analysis to surface only exploitable vulnerabilities
- Read-only repository access means the platform never modifies your actual code
- Fast iteration cycle addresses feature requests and limitations quickly
Cautions
- Some users report that reporting skews developer-focused and lacks depth for security engineering audit needs
- According to customer feedback, third-party tool integrations remain limited compared to more established platforms
BigID Data Security Platform
BigID tackles data discovery and classification at scale for organizations managing sensitive data across cloud, hybrid, and on-premises environments. The platform uses machine learning to identify critical, alongside regulated and sensitive data types.
ML-Driven Classification That Scales
The classification engine handles massive data volumes without choking. We found the ML models accurate for standard data types like PII and PCI, with customization options to train classifiers for proprietary patterns. Risk scoring ties directly to remediation workflows.
The security suite bundles classification, access intelligence, data labeling, retention management, and breach investigation into one platform. This consolidation matters when you need consistent policy enforcement across fragmented environments.
What Customers Are Saying
Customers praise BigID’s willingness to develop custom features and adapt to changing requirements. The vendor relationship gets consistently positive marks for responsiveness. The BigID University courses help teams ramp up faster.
Some users report that Some users flag integration challenges with SaaS platforms and collaboration tools, however.
Enterprise Data Programs Only
We think BigID fits organizations with serious data sprawl and compliance obligations. If you manage petabytes across multiple environments and need ML-powered classification, this delivers.
Strengths
- ML-driven classification accurately identifies sensitive data across petabytes of information
- Vendor team actively develops custom features and adapts to evolving requirements
- Consolidated suite covers classification, retention, access intelligence, and breach investigation
- Risk scoring connects directly to remediation priorities and policy enforcement
Cautions
- According to some customer reviews, integration gaps with some SaaS platforms and collaboration tools create visibility blind spots
- Some users report that reporting focuses on technical outputs and lacks flexibility for business-level metrics
Concentric AI Semantic Intelligence
Concentric AI takes a semantic approach to data discovery and classification. Instead of relying on regex patterns and rules, it uses deep learning to understand data context and meaning. The platform scans structured and unstructured data across cloud and on-premises repositories.
Context Over Pattern Matching
The semantic classification engine outperforms traditional regex-driven tools in our assessment. When Concentric flags data as sensitive, it explains why. That transparency builds trust with stakeholders and speeds remediation decisions. The MIND deep learning service keeps models current without manual intervention.
Agentless, API-based deployment connects to data repositories without agent sprawl. Risk Distance analysis surfaces files with misaligned permissions or classification, so you focus on actual exposure rather than theoretical risk.
Fast Time to Value
Customers consistently highlight how the platform works as advertised. Implementation is straightforward, classification is precise without extensive tuning, and teams can focus on fixing issues rather than filtering false positives. The vendor team gets strong marks for responsiveness.
Some users report that scanning speed fell short of expectations.
When Semantic Classification Matters
We think Concentric fits organizations drowning in false positives from traditional DLP. If your current tools generate noise that nobody acts on, the semantic approach delivers cleaner signal.
Strengths
- Semantic classification understands data context, cutting false positives versus regex-based tools
- Agentless API deployment connects to repositories without agent management overhead
- Risk Distance analysis identifies files with misaligned permissions and inappropriate sharing
- Platform explains classification decisions, building trust and speeding remediation
Cautions
- Some users report that scanning speed fell short of expectations for some deployments
- Some users note that dashboard and export capabilities need refinement for reporting-heavy workflows
Dig Security Data Detection and Response
Dig combines data security posture management with real-time threat detection across multi-cloud environments. The platform discovers and classifies data, monitors for suspicious activity, and can detect ransomware and exfiltration attempts. Now part of Palo Alto Networks.
Real-Time Detection Across Cloud Providers
The DDR engine monitors data events continuously and raises alerts on security violations. We found the 21 built-in DDR policies effective at catching high-risk vulnerabilities quickly. The platform creates threat models specific to your environment rather than relying on generic signatures.
Risk ranking surfaces what matters first.
What Customers Are Saying
Customers consistently praise quick deployment and an intuitive interface. Support quality is a genuine differentiator.
According to customer feedback, Some users flag missing administrative features like adding comments to findings or managing exceptions without vendor assistance, however.
Multi-Cloud Data Threat Detection
We think Dig fits enterprises with significant multi-cloud data sprawl who need both posture management and active threat detection. The DDR capability sets it apart from pure DSPM tools.
Strengths
- Real-time DDR detects ransomware and exfiltration attempts before damage occurs
- Multi-cloud support covers AWS, Azure, and GCP from a single dashboard
- Risk ranking and executive reporting simplify prioritization and stakeholder communication
- Quick deployment delivers value within minutes of activation
Cautions
- According to customer feedback, administrative features like exception management still require vendor assistance
- Some users report that documentation and knowledge base need significant improvement
Imperva Data Security
Imperva provides enterprise-grade data security across legacy databases, cloud platforms, and hybrid environments. The platform covers discovery, classification and activity monitoring, plus policy enforcement for over 65 datarepository types.
Enterprise Coverage Across 65+ Repositories
The range of data store support stands out. Imperva handles legacy databases alongside modern cloud architectures. We found the automated discovery and classification accurate for identifying sensitive data locations without manual tagging.
Real-time monitoring delivers actionable insights on data access and risk. Data visualization gets strong marks for making complex activity patterns understandable. Centralized control across multiple cloud platforms provides the unified view that distributed security tools struggle to deliver.
What Customers Are Saying
Customers praise the full visibility and confidence the platform provides once operational. You know where sensitive data lives, who accesses it, and whether it faces risk.
Based on customer reviews, Setup complexity is the consistent friction point, however.
Legacy Plus Cloud Environments
We think Imperva fits enterprises with significant legacy database footprints transitioning to cloud. The 65+ repository coverage handles environments that pure-cloud DSPM tools cannot reach.
Strengths
- Supports 65+ data repository types across legacy, cloud, and hybrid architectures
- Real-time monitoring and analytics surface actionable risk insights without noise
- Automated discovery and classification identify sensitive data without manual effort
- Data visualization makes complex activity patterns accessible to security teams
Cautions
- Some customer reviews note that initial setup requires professional services coordination in complex environments
- Some users report that user interface navigation feels less intuitive than expected for some features
Securiti Data Security Posture Management
Securiti positions itself as a unified data command center spanning security, privacy, governance, and compliance. The DSPM solution discovers and catalogs data assets across public clouds, data clouds, alongside SaaS and on-premises systems.
Privacy and Security in One Platform
The platform combines data discovery and classification with privacy automation. DSR fulfillment, consent management, privacy assessments, and breach analysis run alongside misconfiguration detection. We found this integration valuable for organizations juggling both security and privacy obligations.
AI-powered classification handles sensitive data across multiple formats while providing contextual metadata. Risk prioritization based on data sensitivity reduces alert fatigue. Auto-remediation or owner alerts address misconfigurations without manual queue management.
What Customers Are Saying
Customers highlight the privacy center, DSR module, and assessment automation as standout features. Out-of-box classification works well without custom rules. Support responsiveness gets positive marks.
Some customer reviews note that Some users encountered stability issues scanning OneDrive and SharePoint, with pods crashing during discovery, however.
Privacy-First Data Security
We think Securiti fits organizations where privacy compliance drives security investment. If you need DSR automation, consent management, and DSPM in one platform, the integration delivers real efficiency.
Strengths
- Unified platform combines DSPM with privacy automation including DSR and consent management
- AI classification works out-of-box without requiring custom rule creation
- Risk prioritization by data sensitivity reduces alert fatigue and false positives
- Single command center serves security, privacy, governance, and compliance teams
Cautions
- Based on user feedback, OneDrive and SharePoint scanning experienced stability issues requiring weeks to resolve
- Some users note that support timezone differences created coordination challenges for their organizations
Splunk Enterprise Security
Splunk Enterprise Security is the SIEM that security teams either love or love to complain about. The platform ingests data from anywhere, applies ML-powered analytics for threat detection, and delivers the search flexibility that SPL provides.
SPL and Schema-on-Read Change Everything
The Search Processing Language remains Splunk’s defining strength. Schema-on-read means you ingest unstructured data without predefined schemas, then query it however you need. We found this flexibility invaluable for investigations that traditional rigid-schema tools struggle with.
Out-of-box detection coverage is extensive. Over 1,400 detections map to MITRE ATT&CK, NIST, CIS 20, and Kill Chain frameworks. Risk-based alerting helps manage alert fatigue by correlating signals before firing.
Power Comes With Complexity
Real-time analysis of large data volumes works well once configured. The interface shows common values, data types, and statistics that speed up investigation workflows.
Configuration requires specialized knowledge.
When You Need SIEM Flexibility
We think Splunk fits organizations with mature security operations and the expertise to leverage SPL. The search flexibility and detection coverage justify the investment for teams who use it properly.
Strengths
- SPL and schema-on-read enable flexible queries against unstructured data without predefined schemas
- 1,400+ out-of-box detections mapped to MITRE ATT&CK, NIST, and Kill Chain frameworks
- Risk-based alerting correlates signals to reduce alert fatigue and improve true positive rates
- Dashboards translate raw log data into executive-ready visualizations without technical skills
Cautions
- Organizations report that initial configuration and data integration require specialized Splunk expertise
- Some users report that high-volume data ingestion and HEC endpoint optimization present significant challenges
Varonis
Varonis focuses on data security with automated remediation capabilities that competitors often lack. The platform discovers, classifies, and monitors sensitive data while continuously fixing exposure and misconfigurations. What sets it apart: autonomous remediation backed by a global incident response team.
Automated Remediation That Actually Works
Most data security tools detect issues and leave remediation to you. Varonis automates the fix. We found the automation services particularly effective for broken ACL repairs, global group open access remediation, and scheduled risk reporting. These capabilities address large-scale permission problems that manual processes cannot touch.
The platform builds user and device profiles to identify unusual behaviors. Bi-directional cluster analysis and accurate permission removal recommendations reduce human intervention.
Managed Detection With Deployment Friction
Customers praise the peace of mind from having Varonis analysts monitor data alongside their own team. Classification accuracy gets strong marks. The service model helps remediate overexposed files and respond to attacks.
Deployment remains the consistent pain point. Setup timelines exceeded advertised estimates for multiple customers. File-walk duration runs long in large environments. Some users reported support challenges with unfamiliar issues.
When You Need Automated Remediation
We think Varonis fits organizations with significant unstructured data sprawl and permission debt they cannot address manually. The automation capabilities justify the investment if you have exposure at scale.
Strengths
- Automated remediation fixes broken ACLs and open access at scale without manual intervention
- Managed incident response team monitors data and responds to attacks alongside your security staff
- User and device profiling identifies unusual behaviors and potential insider risks
- Classification accuracy benefits from incremental scanning, OCR, and algorithmic verification
Cautions
- According to some user reviews, deployment timelines significantly exceeded advertised setup estimates for some customers
- Some users report that file-walk duration runs long in large environments with extensive unstructured data
Wiz DSPM
Wiz DSPM brings data security posture management into the broader Wiz CNAPP platform. It targets security teams running multi-cloud environments who need to track sensitive data across their infrastructure without deploying additional agents.
Data Discovery Without the Agent Sprawl
The agentless architecture works exactly as advertised. Connect your cloud accounts and scanning starts immediately. We found the built-in classifiers for PII, PCI, and similar data types accurate out of the box. Custom classifiers let you extend coverage to proprietary data formats.
The real differentiator is how DSPM plugs into the Wiz Security Graph. Instead of treating data risks in isolation, you see sensitive data alongside misconfigurations, vulnerabilities, and access paths. We saw this context dramatically reduce triage time for data exposure issues.
What Long-Term Users Report
Customers consistently praise the speed of deployment. Setup takes hours, not weeks. The Jira integration gets frequent mention for simplifying remediation workflows across security and engineering teams.
Should You Consider It?
We think Wiz DSPM makes sense if you already run Wiz or want consolidated cloud security tooling. The compliance automation for PCI DSS, GDPR, and HITRUST saves real time during audit prep.
If your environment is single-cloud or you need deep on-premises data discovery, this may not fit.
Strengths
- Agentless deployment connects to cloud accounts and starts scanning within hours
- Security Graph integration shows attack paths to sensitive data, not just data locations
- Built-in compliance frameworks automate PCI DSS, GDPR, and HITRUST assessments
- Custom classifiers extend discovery beyond standard PII and PCI patterns
Cautions
- Some users have noted that initial alert volume requires policy tuning before actionable signal emerges
- Some users report that autoscaling environments complicate vulnerability tracking when resources appear and disappear
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 11 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.