Data Migration & Consolidation

We begin with a discovery and profiling phase that maps every source—spreadsheets, on-prem SQL, cloud apps, IoT streams—against the target schema, flagging duplicates, gaps and GDPR-sensitive fields before a single row moves.

Next we build repeatable ETL/ELT pipelines in Python, dbt or Rust for extreme speed, or leverage Kwerio’s import engine as an API gateway; change-data capture keeps sources and target in sync until the final switch. Deduplication, validation tests and rollback plans ensure data integrity, while encryption, masking and detailed logs satisfy NIS-2 and audit demands.

Cutover happens during a planned window with live monitoring, after which we hand over fully documented pipelines and train your team—leaving you with a unified, trusted dataset ready for analytics, AI and cross-partner collaboration.