Petabyte ingestion for a global 3PL
Re-architecting a legacy batch estate into a streaming lakehouse that delivered fresher operational data with lower infrastructure cost.
Re-architecting a legacy batch estate into a streaming lakehouse that delivered fresher operational data with lower infrastructure cost.
When overnight data is already late
A global logistics network was relying on a large collection of nightly batch jobs. As shipment volume grew, processing windows overlapped with the next business day and operational teams made decisions using stale inventory and movement data.
The platform also carried years of tightly coupled transformations, so a direct rewrite would have created unacceptable migration risk.
Migrating by business flow
We introduced event-driven ingestion and a lakehouse architecture incrementally, moving one business flow at a time behind consistent contracts. Data quality checks, lineage, replay capability, and cost telemetry were treated as platform features rather than follow-up work.
Old and new pipelines ran in parallel until reconciliation met agreed thresholds. This allowed operations teams to validate freshness and accuracy without a high-risk cutover weekend.
Faster and less expensive
The redesigned pipelines ran up to fourteen times faster and reduced cloud spend by 62%. Operational datasets that had arrived the next morning became available throughout the day.
The biggest gain was not a single technology choice. It was the combination of decoupled data contracts, observable pipelines, and a migration plan designed around business continuity.
