Legacy Platform Migration
Tier-1 Railroad
Use Case
A major North American railroad was operating a large-scale Netezza environment supporting critical reporting, operations, and planning workflows.
Over time, the platform became a bottleneck.
Long-running batch jobs impacting daily operations
High infrastructure and licensing costs
Complex, tightly coupled ETL pipelines
Limited ability to support advanced analytics and AI initiatives
The organization needed to modernize without disrupting mission-critical systems.
KData led the migration to Databricks, starting with a full discovery of data assets, pipelines, and dependencies.
Assessed and prioritized hundreds of tables, SQL workloads, and ETL jobs
Translated and re-engineered Netezza SQL and pipelines into Databricks
Designed and implemented a lakehouse architecture (bronze, silver, gold)
Established data governance and access control using Unity Catalog
Executed a phased migration with parallel validation
The result was not just a migration, but a production-ready Databricks platform.
Improved pipeline performance and reliability
Reduced platform complexity and operational overhead
Enabled a unified foundation for analytics, reporting, and AI
The transition was executed without disrupting core business operations.
A structured, phased framework built from real delivery experience.
This approach reflects best practices from real migration delivery playbooks.
Underestimating SQL and ETL complexity
Ignoring data lineage and dependencies
Treating migration as a tooling exercise instead of a platform rebuild
Lack of production-ready pipelines and data quality controls
We address these directly with a production-first approach.