Data Modernization
Replace fragile data processes while keeping the business running. SAI helps assess a legacy estate, choose the right target architecture and move priority workloads in controlled waves.
The business problem
Legacy warehouses, mainframe extracts and point-to-point feeds often support important reports that few people fully understand. A large migration can break trusted figures or overlook a critical dependency. Modernization should preserve meaning as well as move bytes.
How SAI Technologies approaches the work
Inventory sources, data flows, reports, owners, access rules and hidden dependencies.
Prioritize by business value, risk and migration complexity; agree on a target architecture before moving a workload.
Create parallel runs and reconciliation rules so teams can compare old and new results.
Modernize pipelines, shared definitions, cataloging and quality controls; retire old processes only after acceptance criteria are met.
Transfer monitoring, documentation and support ownership to the client or managed delivery team.
Connected process
Illustrative delivery story
A bank-like enterprise relies on nightly extracts from older systems for risk and service reporting. SAI could document the source logic, move one reporting domain into a governed cloud platform, reconcile results during parallel runs and retire the old batch only after approval.
Measures to agree before work begins
Number of legacy feeds retired; reconciliation pass rate; time to add a new data source; outage and rollback frequency; reporting freshness; support effort.
