Unified Student Analytics Platform for a Multi-Campus University
CYVERRA designed and deployed a centralised cloud data warehouse and analytics platform to consolidate fragmented student lifecycle data across four campuses. The modernised data foundation enabled proactive academic support interventions and near real-time operational reporting.
Multi-campus UK higher education institution
- -85%
- Reporting cycle time
- +24%
- At-risk student intervention rate
- -32%
- Infrastructure TCO
- 4.5x
- Data pipeline throughput
The Challenge
The institution operated across four distributed campuses serving over 28,000 students, with core academic, operational, and financial data fragmented across disparate systems. Student information records, learning management system (LMS) logs, library access metrics, and admissions databases resided in isolated on-premise silos, making comprehensive student journey analysis virtually impossible. Institutional reporting relied heavily on manual batch extractions and spreadsheet consolidation, resulting in a three-week lag for key performance indicators. This latency prevented faculty advisors from identifying early indicators of student disengagement, directly impacting first-year retention rates. Additionally, legacy database infrastructure struggled to manage peak concurrent query loads during registration and exam periods, driving up administrative overhead and maintenance costs while presenting compliance challenges under regional data protection standards.
Our Approach
CYVERRA engineered an enterprise cloud lakehouse architecture using Snowflake and AWS, orchestrated via dbt and Apache Airflow to standardise and automate ingestion pipelines from over twelve disparate campus data sources. The architecture established clear raw, staging, and curated data layers with continuous data quality validation. To address governance and compliance, our team implemented automated role-based access control (RBAC), column-level masking for personally identifiable information (PII), and an end-to-end audit logging framework aligned with GDPR and institutional research ethics standards. All infrastructure was provisioned using Terraform to guarantee reproducible, secure environments. In collaboration with faculty stakeholders, CYVERRA developed a modular semantic layer and self-service Power BI reporting suites. This included a predictive early-warning model that identified students exhibiting patterns associated with course withdrawal, enabling automated alert triggers for academic personal tutors.
The Outcome
The deployment transformed the institution's data maturity, eliminating manual extract processes and reducing institutional reporting cycle times from three weeks to automated daily updates. Faculty advisors gained access to longitudinal student engagement dashboards, enabling early interventions that measurably improved retention metrics across undergraduate cohorts. From an operational perspective, transitioning to a scalable cloud data platform lowered infrastructure total cost of ownership by eliminating legacy server maintenance contracts. The university now possesses an extensible data foundation capable of supporting advanced research analytics, predictive enrollment modeling, and enterprise-wide strategic planning.
Technology used
- AWS
- Snowflake
- dbt
- Apache Airflow
- Power BI
- Python
- Terraform
Consolidating our academic and administrative data into a secure cloud foundation transformed our ability to support at-risk students before critical assessment periods.