AWS Analytics Data Detection
Learn how to detect analytics data in AWS environments. Follow step-by-step guidance for GDPR compliance.
Why It Matters
The core goal is to identify every location where analytics data is stored within your AWS environment, so you can remediate unintended exposures before they become breaches. Scanning for analytics data in AWS is a priority for organizations subject to GDPR, as it helps you prove you've discovered and accounted for all sensitive analytical datasets—mitigating the risk of shadow data proliferating across your infrastructure.
A thorough scan delivers immediate visibility, laying the foundation for automated policy enforcement and ongoing compliance.
Prerequisites
Permissions & Roles
- AWS admin or IAM role with sufficient privileges
- s3:GetObject, s3:ListBucket permissions
- Access to AWS CLI or CloudFormation
External Tools
- AWS CLI
- Cyera DSPM account
- API credentials
Prior Setup
- AWS account configured
- S3 buckets with analytics data
- CLI authenticated
- Cross-account roles 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 techniques including Named Entity Recognition (NER) and machine learning models, Cyera automatically detects analytics datasets containing personal identifiers, behavioral patterns, and business metrics in your AWS environment—ensuring comprehensive visibility into shadow data that could impact GDPR compliance.
Step-by-Step Guide
Ensure proper IAM roles and policies are in place for cross-account access. Create a service role with minimum required permissions for S3, Redshift, and other analytics services.
In the Cyera portal, navigate to Integrations → DSPM → Add new. Select AWS, provide your account ID and cross-account role ARN, then define the scan scope to include S3, Redshift, Athena, and other analytics services.
Configure webhooks or streaming exports to push scan results into your SIEM or Security Hub. Link findings to existing ticketing systems like Jira or ServiceNow for automated remediation workflows.
Review the initial detection report, prioritize buckets and datasets with large volumes of analytics data, and adjust detection rules to reduce false positives. Schedule recurring scans to maintain visibility across dynamic analytics workloads.
Architecture & Workflow
AWS Analytics Services
S3, Redshift, Athena, QuickSight data sources
Cyera Connector
Pulls metadata and samples data for classification
Cyera AI Engine
Applies NER and ML models for analytics data detection
Reporting & Remediation
Dashboards, alerts, and automated playbooks
Data Flow Summary
Best Practices & Tips
Performance Considerations
- Start with incremental or region-scoped scans
- Use intelligent sampling for large datasets
- Schedule scans during off-peak hours
Tuning Detection Rules
- Maintain allowlists for test analytics environments
- Adjust confidence thresholds per data type
- Configure custom patterns for business-specific metrics
Common Pitfalls
- Missing analytics data in Lambda functions
- Over-scanning temporary EMR clusters
- Neglecting to rotate cross-account role credentials