Azure Analytics Data Detection

Learn how to detect analytics data in Azure environments. Follow step-by-step guidance for PCI-DSS compliance.

shadow data

PCI-DSS

azure

Why It Matters

The core goal is to identify every location where analytics data is stored within your Azure environment, so you can remediate unintended exposures before they become breaches. Scanning for analytics data in Azure is a priority for organizations subject to PCI-DSS, as it helps you prove you've discovered and accounted for all sensitive analytical assets—mitigating the risk of shadow data repositories containing payment card information.

Primary Risk: Shadow data containing sensitive analytics information

Relevant Regulation: PCI-DSS Payment Card Industry Data Security Standard

A thorough scan delivers immediate visibility, laying the foundation for automated policy enforcement and ongoing compliance.

Prerequisites

Permissions & Roles

  • Azure Contributor or Owner role
  • Data Reader permissions on storage accounts
  • Ability to configure Azure CLI or PowerShell

External Tools

  • Azure CLI or PowerShell
  • Cyera DSPM account
  • Service principal credentials

Prior Setup

  • Azure subscription activated
  • Storage accounts provisioned
  • CLI authenticated
  • 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 automating the discovery of analytics data in Azure using advanced AI and natural language processing (NLP) techniques, Cyera ensures you stay ahead of accidental exposures and meet PCI-DSS audit requirements in real time.

Step-by-Step Guide

1
Configure your Azure environment

Ensure your Azure subscription has the necessary permissions and create a service principal with the minimum required privileges for data discovery.

az login && az account set --subscription "your-subscription-id"

2
Enable scanning workflows

In the Cyera portal, navigate to Integrations → DSPM → Add new. Select Azure, provide your subscription ID and service principal details, then define the scan scope including storage accounts, data lakes, and analytics workspaces.

3
Integrate with third-party tools

Configure webhooks or streaming exports to push scan results into your SIEM or Azure Security Center. Link findings to existing ticketing systems like Azure DevOps or ServiceNow.

4
Validate results and tune policies

Review the initial detection report, prioritize storage accounts with large volumes of analytics data, and adjust detection rules to reduce false positives. Schedule recurring scans to maintain visibility.

Architecture & Workflow

Azure Storage & Data Lake

Source of analytics data and metadata

Cyera Connector

Pulls metadata and samples data for classification

Cyera Back-end

Applies AI detection models and risk scoring

Reporting & Remediation

Dashboards, alerts, and playbooks

Data Flow Summary

Enumerate Storage → Send to Cyera → Apply Detection → Route Findings

Best Practices & Tips

Performance Considerations

  • Start with incremental or scoped scans
  • Use sampling for very large data lakes
  • Tune sample rates for speed vs coverage

Tuning Detection Rules

  • Maintain allowlists for synthetic datasets
  • Adjust confidence thresholds
  • Match rules to your risk tolerance

Common Pitfalls

  • Forgetting analytics data in blob storage
  • Over-scanning temporary or development data
  • Neglecting to rotate service principal credentials

References & Further Reading

Next Steps

🔧 Fix: Review and remediate publicly exposed analytics data 🛡️ Prevent: Set up preventive controls for analytics data