Business Systems Engineering service

Data Strategy, Governance & Engineering

For organisations that need data to become a trusted working part of the business system rather than a separate technical programme.

Discuss a system challenge
01 · Problems

When this capability matters

  • 01The same business concept has different meanings.
  • 02Ownership and accountability are unclear.
  • 03Data arrives late or is corrected manually.
  • 04Quality measures are disconnected from business risk.
  • 05A platform exists but adoption and value do not follow.
  • 06AI initiatives do not have a trusted foundation.
  • 07Migrations lose semantics or provenance.
02 · MTera

How MTera works on the system

01

Connect data strategy to explicit business decisions and outcomes.

02

Define domains, ownership and decision rights.

03

Shape conceptual and logical data architecture.

04

Design data flows and integration patterns.

05

Connect quality controls to material business use.

06

Define metadata, lineage and context requirements.

07

Plan analytical and operational use together.

08

Assess and prepare data foundations for AI.

09

Plan platform change and migration without losing semantics.

10

Establish a sustainable data operating model.

03 · Deliverables

A target state that can be acted on

  • Data strategy
  • Domain and ownership model
  • Data architecture
  • Critical data element map
  • Quality control design
  • Lineage and metadata requirements
  • Migration and integration plan
  • Analytics and AI readiness roadmap
  • Prioritised use-case portfolio
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Discuss a system challenge

Build what comes next without losing what must remain true.

Discuss a system challenge
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