Data Foundation
Every dashboard, model and agent you ever build will stand on this layer. We design and build data foundations from the enterprise systems outward — a canonical model that reconciles ERP, HCM, SCM and finance data into one trusted, AI-ready foundation, populated and proven with DMOne™.
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Why a Data Foundation
Copying enterprise data into a lake does not make it usable — it makes it a lake of the same inconsistencies. The same employee, supplier or cost centre exists differently in every system, and until those meanings are reconciled into one canonical model, every analytics and AI initiative re-fights the same battle privately.
One agreed definition of your core entities — people, organisations, suppliers, items, accounts — that every source maps to.
DMOne™ migration and reconciliation controls evidence that what landed in the foundation matches what left the source.
Ownership, survivorship and stewardship for master and reference data designed into the foundation, not bolted on.
Role and access design applied at the foundation layer, so downstream analytics and AI inherit control rather than bypass it.
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Design and build, from architecture to populated, reconciled data.
Every engagement is scoped around a defined set of deliverables agreed at the outset.
AI and analytics are only as good as the enterprise data beneath them. That data is our home ground.
Scoped to your estate — typically a first increment lands in eight to twelve weeks.
Profile in-scope enterprise systems with DMOne™ to establish real data condition, volumes and overlap before any design is fixed.
Canonical model, platform architecture, master data and security design agreed with business and technical owners together.
Foundation platform built, source mappings implemented, quality and reconciliation controls configured.
Data consolidated through DMOne™ with reconciliation evidence per source — then handed over with documentation and runbooks.
Data Foundation connects naturally with these services across our Data & AI portfolio.
