As part of a program to integrate the aviation applications of various entities, the project aims to migrate a new entity to flight tracking software. Over 100,000 pieces of data, covering various categories such as accounts, contacts, flight logs and settings, need to be migrated with precision.
1 – Challenges
Data quality was a major challenge in this project:
- Input data files were voluminous, requiring efficient management.
- Data quality did not meet the standards defined for the various types of data, requiring additional effort to process and integrate them correctly into the new system.
Data collection presented several challenges:
- The data was collected outside the project iterations, resulting in delays.
- Input files were often received late.
- Data quality was very poor, requiring extra work during development sprints to clean it up and prepare it for integration into the new system.
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The main problems encountered were as follows:
- Limited resources: The Agile team consisted of a limited number of members, which posed challenges in terms of workload and task allocation. What’s more, publication dates were strict and inflexible, putting added pressure on the team to meet deadlines.
- Technical dependencies: The project relied heavily on a third-party development team to integrate new features, which could lead to delays or complications in the process. In addition, there was an incompatibility between the database schema of the target system and the user interface rules, requiring close coordination between teams to resolve these issues.
2 – Solutions adopted
The success of this project was fostered by close collaboration between the tester, the business analyst and the developer, ensuring continuous support throughout the process. Our methodical approach included :
- Data quality tests at every stage, guaranteeing data integrity and reliability.
- Rigorous checks on components and data loading via the Salesforce API, ensuring seamless migration.
- Targeted acceptance testing to validate customer-critical use cases, ensuring compliance with functional requirements.
Results obtained :
The migration was a success in several respects:
- Development and testing were completed ahead of schedule, enabling a smooth transition.
- Automation covered all API and UI-based tests, guaranteeing exhaustive verification.
- Critical and major defects were identified early and corrected quickly, minimizing potential risks.
- The transition to production went smoothly, with no unexpected incidents, ensuring the successful commissioning of the new system.
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This case study demonstrates the effectiveness of a methodical, collaborative approach to overcoming the challenges encountered during data migration, guaranteeing the project’s success on time and with optimum quality.
