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Leadership needed one reconcilable thread from manufacturing and distribution operations through to management reporting—without standing up another copy of the ERP or running heavy analytical workloads against transactional cores.

What leadership was trying to fix

Reporting without overloading transactional cores

Finance and operations often pulled slightly different cuts of orders, inventory, and revenue because reporting had grown through departmental extracts and ad hoc queries against SAP and Oracle. Digital and analytics initiatives competed for the same operational systems, and every new dashboard risked another bespoke join path. The ERP remained the system of record, but it was never designed to serve broad analytical concurrency or cross-domain grain.

Friction in the data estate

Overlapping extracts and misaligned keys

Batch extracts overlapped in time and definition; keys for plants, products, and customers did not always match between finance close packs and supply views. Teams that needed fresher signals still defaulted to what was easiest to query in the moment rather than what was published for enterprise use. Promoting data to a trusted layer was manual, and lineage back to source transactions was hard to explain in audits or steering forums.

Design of the response

Medallion paths from CDC and controlled batch

We anchored the program on a medallion layout on the client’s cloud lakehouse: Bronze for immutable landing from agreed ERP interfaces—CDC where change capture was viable, and controlled batch where it was not; Silver for conformed keys across finance and supply, shared dimensions, and tests at promotion; Gold for subject-friendly marts and certified metrics consumed by BI and planning tools.

The goal was operational truth derived from the ERP, not a second ERP-shaped database. Heavy aggregates and cross-domain reporting run in the lakehouse; the cores stay focused on transactions and integrity.

How we ran delivery

Vertical slices with owner sign-off

We sequenced vertical slices: one critical source family at a time, end-to-end from landing through a thin Gold cut and one downstream consumer. Data owners signed off on grains and definitions before additional consumers were onboarded. Platform engineers owned pipelines, observability, and runbooks; governance forums reviewed semantic changes that touched certified metrics.

This pattern—contracts first, tests at promotion, explicit ownership—is how we repeat similar foundations without turning every engagement into a custom science project.

Impact

Trust in promoted datasets, less load on the ERP

Management reporting and operational analytics increasingly draw from promoted datasets and shared definitions instead of competing extracts. Analytical load shifts off the ERP cores toward the lakehouse path the business can scale. Internal teams operate steady-state pipelines with documentation and escalation paths transferred during the program.

Identifying details are omitted under client confidentiality.