Legacy feeds data warehouse — incremental, auditable, no big bang
ERP, spreadsheet, and old system become continuous flow to BI and AI — incremental load with trail, not heroic weekend migration.
Report and AI model stop depending on manual legacy export on board eve. An incremental pipeline extracts data from ERP, legacy database, and critical spreadsheets, transforms with agreed business rule, and delivers to data warehouse or lakehouse — with watermark, retry, and log per batch. BI and copilot operate on updated data; IT evolves source without rewriting core at once.
What blocks you today
BI shows yesterday's number because someone forgot to run export. Legacy blocks any analytics project. Full migration becomes fear — and data stays trapped in old system. Nobody trusts dashboard in leadership meeting.
What changes in practice
- Legacy source mapping — ERP, database, spreadsheet, API — with owner and criticality
- Incremental pipeline with watermark, deduplication, and idempotent load
- Transformation and modeling in warehouse per agreed business rule
- Failure, delay, and volume monitoring per source
- Lineage documentation — from source table to BI indicator
Business outcome
Leadership and operations decide with trustworthy, updated data. Analytical or AI project doesn't wait for full legacy migration. IT delivers incremental value — source by source — with clear trail of what entered warehouse.
Where it usually fits
- Companies with legacy ERP and BI outdated by manual export
- Post-acquisition groups with multiple operational data sources
- Operations wanting copilot or AI on history still trapped in silo
- Industry and distribution with critical spreadsheet coexisting with ERP
- IT needing to prove data ROI before replacing legacy system
How it evolves next
With incrementally fed warehouse, you can connect natural language reports, master data, and event layer.
- Natural language reports on warehouse KPIs
- Single registry and deduplication feeding analytical dimensions
- Event bus for new channels to consume data without touching legacy
- Semantic search and copilot on indexed documents and history
- Proactive monitoring when pipeline delays or source diverges
BI shows yesterday's number because someone forgot to run export?
Legacy blocks any analytics project? Tell us about the integration — we map criticality and path together.