How a robust data quality strategy accelerated core system migration in LatAm

A global leader in transactional services - with a presence in 46 countries, more than 50 million users and 2 million affiliated merchants - undertook one of the most ambitious transformations in its history: to implement a new core system for all its operations in Latin America.

Although the new system promised agility and scalability, the obstacle was not technological, but informational: millions of records distributed in legacy systems, with no governance or quality control. The internal team detected formatting errors, duplicates, empty fields and inconsistent data, which jeopardized the stability of the new system. In addition, the business teams did not have the time or resources to support the cleanup process.

The solution: a modular, automated, self-sustaining data quality factory

From the initial diagnosis, our team of specialists in Data Quality and Data Governance understood that the success of the project depended on:

• Reduce dependence on internal IT equipment
• Establish automated rules to validate, clean and homologate the information.
• Adapting the solution to strict release windows and parallel processes in several countries

We design a comprehensive data quality service in "factory" mode (Data Quality Factory) on demand, based on:

• Automatic data profiling with Azure and Snowflake compatible tools
• Identification and correction of content errors, formatting and invalid structures
• Business rules aligned with regional operations
• Reusable components and modular deliverables
• A flexible batch execution model, no hidden costs for reuse

In addition, we enabled the client to run validation processes autonomously in future iterations, eliminating total vendor lock-in.

Results: 90 % data cleanup and significant cost and risk reduction

This approach not only allowed meeting the release times of the new core system in multiple countries, but also enabled tangible benefits from the first iteration:

• 90 % of data quality achieved before final loading
• 40 % decrease in validation timethanks to the automation of rules
• Significant operational savingsby avoiding the procurement of external data quality tools
• Full traceability of the entire migration process
• Zero interruptions in customer operations during deployment

The client now has a reliable and standardized database for future integrations, audits or regional expansions. More importantly, the successful migration of the core eliminated historical bottlenecks, improved decision making, and allowed moving towards a modern data-centric architecture.