The Challenges
Farm Credit Canada relied on legacy ETL workflows built in Informatica, which presented growing challenges in cost, maintenance, and agility. They needed a solution that could:
- Eliminate vendor lock-in.
- Support evolving data logic for financial calculations.
- Scale dynamically with future business needs.
- Maintain zero disruption to critical financial reporting.
Business Impact
- 40% reduction in end-to-end ETL processing time.
- 55% lower annual ETL cost by removing proprietary tools.
- 99.99% system uptime during migration window.
- 100% data fidelity across all migrated transformations.
- 2M+ daily transactions handled with sub-2s latency.
Our Solution
We executed a full-scale migration of ETL processes from Informatica to Python, replacing all core transformations and logic with open-source, maintainable, and scalable code.
ETL Translation
Rebuilt over 280+ Informatica mappings into modular Python scripts.100% logic parity, enhancing transparency and traceability.
Custom Ratio Engine
Engineered a high-performance Python-based calculation engine that processes over 2 million records per day <1.5 second latency per batch.
Scalability by Design
Achieved 40% faster data processing times post-migration And ensured the solution could scale linearly with future data growth.
Reduced Operational Overhead
Cut annual ETL licensing and infrastructure costs by over 55%,Enabling reinvestment in analytics initiatives.
Uptime Assurance
Maintained 99.99% job execution success rate during and after the migration, ensuring uninterrupted financial operations.
Technologies Used
Python 3.x
Pandas, NumPy
Custom ETL Framework
Scheduled executions with Airflow
Git-based CI/CD pipeline
Client Feedback
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“Yotta Data’s migration approach was both structured and forward-thinking. The custom Python engine exceeded our expectations in performance and adaptability. They helped us modernize without compromising data integrity.”