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Calibration Data
Management System
Streamlining upload flows and metadata handling across high-volume calibration files.
UX Architecture | Workflow Optimisation | Interaction Design
🔒 Details in this project are limited due to confidentiality. Let’s connect to explore the story behind the work.
Overview
The platform was created to solve one of the most pressing issues for large enterprises: fragmented and unreliable data. Millions of records were stored across different systems, often inconsistent or duplicated, making it hard to maintain accuracy and trust. The goal was to design a solution that would streamline data validation, reconciliation, and governance while remaining usable for both technical and non-technical stakeholders.
Challenge
Large enterprises often manage millions of data records across fragmented systems. Inconsistent formats, duplicate entries, and lack of ownership reduced data quality and trust. Teams spent hours reconciling mismatched records instead of focusing on analysis and decision-making. The objective was to design a scalable data governance tool that improves trust, consistency, and usability across enterprise datasets.
My Role
UX Lead (Strategy and Interaction Design)
1. Mapped data governance workflows to identify gaps in validation, ownership, and reporting.
2. Led interviews and usability tests with calibration engineers, data scientists, and product managers to uncover priorities.
3. Prototyped and validated solutions for data lineage, record reconciliation, and user access controls.
4. Balanced compliance requirements with user-friendly interaction patterns, ensuring adoption across technical and
non-technical users.
Impact
1. 25–35% reduction in time spent on manual record reconciliation.
2. Improved data accuracy, with automated validation catching errors before records entered downstream systems.
3. Higher compliance confidence, reducing audit risks and ensuring traceability across all records.
4. Faster onboarding of datasets, enabling new business units to integrate into the platform in days instead of weeks.
Reflection
This project reinforced the value of approaching data governance as a human problem, not just a technical one. While automation and validation were central to improving data accuracy, adoption depended on creating a user experience that felt intuitive and trustworthy. The biggest learning was how to balance strict compliance requirements with simple interaction patterns that encouraged everyday use. In future iterations, I would explore expanding the platform’s analytics capabilities to give stakeholders not only clean data but also proactive insights into governance risks.
Thanks for reading 🤓
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