Azure Employee Data Detection
Learn how to detect employee data in Azure environments using AI-powered DSPM tools. Follow step-by-step guidance for GDPR compliance.
Why It Matters
The core goal is to identify every location where employee information is stored within your Azure environment, so you can remediate unintended exposures before they become breaches. Scanning for employee data in Azure is a priority for organizations subject to GDPR, as it helps you prove you've discovered and accounted for all sensitive personal data—mitigating the risk of data exposure and potential regulatory fines.
A thorough scan delivers immediate visibility across Azure services, laying the foundation for automated policy enforcement and ongoing compliance with data protection requirements.
Prerequisites
Permissions & Roles
- Azure Global Administrator or Security Administrator
- Reader permissions across subscriptions and resource groups
- Microsoft Purview Data Reader role
External Tools
- Azure CLI or PowerShell
- Cyera DSPM account
- Service principal credentials
Prior Setup
- Azure subscriptions configured
- Microsoft Purview account (optional)
- Resource groups organized
- Network security groups configured
Introducing Cyera
Cyera is a modern Data Security Posture Management (DSPM) platform that discovers, classifies, and continuously monitors your sensitive data across cloud services. By leveraging advanced AI and Named Entity Recognition (NER) technologies, Cyera automatically identifies employee personal information across Azure Storage, SQL databases, and other services, ensuring you stay ahead of data exposure risks and meet GDPR audit requirements in real time.
Step-by-Step Guide
Create a service principal with read permissions across your Azure subscriptions and grant necessary access to storage accounts, databases, and other data repositories.
In the Cyera portal, navigate to Integrations → Cloud Platforms → Add Azure. Provide your tenant ID, client ID, and client secret, then define the scan scope including storage accounts, SQL databases, and Cosmos DB instances.
Set up AI-powered detection rules for employee data patterns including names, employee IDs, social security numbers, and HR-related information. Configure sensitivity thresholds and data classification labels.
Analyze the detection results, prioritize high-risk exposures, and validate findings to reduce false positives. Configure automated alerts for new employee data discoveries and schedule regular compliance scans.
Architecture & Workflow
Azure Resource Manager
Inventory of storage accounts and databases
Cyera AI Scanner
Samples and classifies data using NER models
Classification Engine
Applies ML models and confidence scoring
Compliance Dashboard
GDPR reporting and remediation workflows
Data Flow Summary
Best Practices & Tips
Performance Considerations
- Start with high-priority storage accounts
- Use incremental scanning for large datasets
- Schedule scans during off-peak hours
AI Detection Tuning
- Fine-tune NER models for your organization
- Create custom patterns for employee ID formats
- Adjust confidence thresholds for accuracy
Common Pitfalls
- Missing archived or backup storage accounts
- Overlooking data in Azure Data Lake
- Insufficient permissions for comprehensive scanning