Data Modelling Made Easy
TXP supported a highly regulated government department whose data modelling workflow tooling had become a bottleneck due to the lack of proper version control, collaboration capability, and impact visibility. This created long delays with frequent freezes to the model to integrate and test changes
The Client
A national regulatory agency within the healthcare sector.
The Challenge
- Existing tooling lacked version control, forcing a freeze the Data Model every sprint and slowing delivery.
- Quality assurance was entirely manual, creating delays, increasing workload, and heightening the risk of missed issues.
- Package‑level locking in existing tooling prevented multiple modellers working on the same area, causing bottlenecks and reducing agility.
- Without branching or merging, conflict resolution was manual and error‑prone, slowing progress and increasing delivery risk.
- The team lacked automated traceability, resulting in poor visibility of change impacts, reduced confidence in model stability.
- Model update delays disrupted sprint cadence and regularly blocked downstream teams reliant on timely model releases.
The Solution
Following a short Discovery, TXP decided on tooling and modern branching to enable parallel modelling. This resulted in a 9-week implementation involving:
- Architectural approval
- Model cleanup
- Licence server activation
- GitHub integration
- VDI configuration
- Training and team enablement
- Golive transition to a new file based version-controlled model
- Integrated continuous integration workflows with version control for model artifacts.
The Benefits
Achieved ~20% efficiency improvement for the data modelling team through:
- Elimination of sprint-based freezes
- Reduced QA effort
- Automated merge conflict resolution
- Faster clarifications turnaround
- Improved auditability and governance of the logical data model
- Enabled scalable, parallel work across multiple data modellers