Secure Azure Data Platform for Sensitive Analytics Workloads
Designing a fully private Azure data platform for sensitive analytics environments. Network topology, security controls, and deployment pipelines were codified to align with CIS benchmarks and Microsoft security standards.
Legal / Professional Services
~1,900 employees
Cloud & Security Delivery Partner
The Challenge
A professional services firm required hosting sensitive analytics workloads in Azure with stringent security and compliance requirements. The organisation faced constraints prohibiting public network access while needing alignment with established security frameworks from initial deployment. The platform demanded a secure analytics environment that would maintain confidentiality and performance without sacrificing long-term operational sustainability.
The Approach
RCS implemented a fully private Azure data platform leveraging secure-by-design principles.
Key architectural components included:
- Codified network topology using Bicep and Azure DevOps pipelines
- Private connectivity and segmented network architecture
- Infrastructure-as-Code ensuring repeatable deployments across environments
- Alignment to CIS benchmarks and Azure Security Baseline
- Automated policy enforcement and configuration validation
Security controls were engineered into the deployment model rather than applied retroactively.
The Outcome
The organisation deployed a fully private, compliant Azure data platform with embedded security controls:
- Consistent and repeatable deployments across development, test, and production environments
- Improved audit confidence through codified control enforcement
- Significantly reduced manual security intervention
- Secure foundation supporting advanced analytics expansion
Measurable Results
100% Infrastructure-as-Code deployment model
CIS-aligned security baseline across environments
Private connectivity enforced across all data workloads
Reduced configuration drift through automated validation