Case Study
When your mainframe retires,
where does the data go?
A global insurer faced a critical deadline: migrate decades of historical data from legacy DB2 mainframes before they went dark, without losing a single record.
The Client
A Global Insurance Leader
Operating across multiple continents, this organisation processes millions of insurance claims annually. Their data isn't just numbers, it represents promises made to policyholders, often during life's most difficult moments.
"Every record in our system represents a customer who trusted us with their security. We couldn't afford to lose even one."
Insurance
Global Operations
Blueprint Two Strategy
The Challenge
Five critical hurdles standing between legacy and modern
Extraction
Identifying critical data points buried in decades-old mainframe systems
Compatibility
Ensuring legacy formats work with modern AWS Redshift architecture
Unstructured Data
Managing complex, non-standard data formats within new systems
Coordination
Aligning 600+ stakeholders across global teams and time zones
Timeline
Reducing project timescales while maintaining absolute data integrity
The Journey
How we made it happen
Map the Landscape
- Deployed data analysts, modelers, and system experts
- Listened deeply to understand legacy system complexities
- Identified and mapped critical data points with honesty
- Built trust through transparent discovery process
Bridge the Gap
- Set clear expectations for migration milestones
- Tailored approach for non-structured data types
- Enabled historical reporting without full migration
- Personalised AWS Redshift architecture to their needs
Accelerate & Align
- Coordinated 600+ stakeholders with minimal friction
- Reduced timelines through best practices
- Resolved data retrieval challenges seamlessly
- Delivered zero records lost with efficient execution
The Transformation
From legacy burden to modern advantage
The Future
Ready for whatever comes next
Through expert data transformation and strategic implementation, Engaging Data successfully transitioned critical legacy data into a modernised architecture, creating a scalable framework ready for future expansion and innovation.