Commercial Bank
Incremental Modernization of Legacy Data Warehouse with Data Vault Methodology
The project was commissioned by one of Europe's largest commercial banks, serving millions of retail and corporate clients. Their legacy data warehouse, built over 15 years ago, struggled to efficiently process complex banking transactions and adapt to modern financial service demands. Given the complexity and scale of their operations, the client opted against a complete platform migration, and chose to maintain their core data warehouse while strategically modernizing only critical components. Hiflylabs' experts implemented a solution based on the Data Vault methodology, enabling faster data processing and flexible business rule management across their banking operations.
98%
decrease in core payment data processing time (from 4-5 minutes to 10 seconds)
50%
reduction in overall process chain duration (from 15-20 minutes to 8-10 minutes)
1-month
implementation, while maintaining business continuity
Challenge
The client faced the complex challenge of managing diverse banking transaction data streams, particularly in their payment processing systems. Their existing data warehouse, built with a traditional 3NF and snowflake schema approach, struggled to efficiently handle multiple payment types including instant transfers and standing orders. The system pulled data from five different sources and fed it into 25 downstream processes, creating a rigid and time-consuming pipeline that took hours to process daily transactions. The traditional architecture also made it difficult to preserve historical data integrity and adapt to changing banking regulations and business needs. With daily operations processing hundreds of thousands of transactions and tracking various payment statuses, they required a solution that could handle information more efficiently while maintaining data lineage and enabling agile adaptation to evolving financial service requirements.
Solution
Rather than attempting a complete system overhaul, we began by narrowing our focus to two key data sources and three downstream processes from the bank's complex payment processing architecture. This targeted approach allowed us to deliver an optimized solution in just two sprints, or one month. Drawing from the Data Vault methodology, we bridged the legacy system with modern principles. Through fifteen carefully crafted views and a new hub-link-satellite model, our hybrid design dramatically improved processing performance. Core payment data processing decreased from 4-5 minutes to just 10 seconds, while the overall process chain time improved from 15-20 minutes to 8-10 minutes. The new architecture also enables parallel processing of satellite tables, further enhancing system efficiency. For the migration of the historical data into the new model, a reverse ETL process has been created to revert the transformed data back to its original source state as close as possible. A dedicated Business Satellite manages legacy surrogate keys, ensures unchanged downstream processes while enabling future modernization. Our view-based integration strategy for existing tables like contracts and currencies allows for gradual modernization without disrupting daily operations. We also developed an automation toolkit for Data Vault component generation, providing the bank with standardized patterns for continued warehouse evolution. Combined with our loading scripts, this ensures a robust and maintainable system that can adapt to changing business needs and provides a foundation for future modernization.
Services
Data Warehouse Modernization
Partial Data Vault Implementation
Data Process Automation
Architecture Redesign
Industries
Banking
Technologies
Oracle
SQL
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