Data Consulting
Data strategy, governance, and architecture advisory. Build the data foundation your AI ambitions require.
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What This Engagement Covers
Organisations that rush to AI without a data strategy end up with expensive models trained on garbage. We assess your current data landscape — quality, lineage, governance, and architecture — then design the target state that makes AI and analytics actually work at enterprise scale.
Included in scope
- Data maturity assessment
- Data governance framework design
- Data architecture blueprinting (cloud and hybrid)
- Data quality measurement and remediation planning
- Metadata management and data catalogue strategy
- AI/ML data readiness evaluation
When to Engage
Situations We're Built For
"We want to deploy AI but our data is a mess."
Most enterprises are in this position. We assess what you have, identify the gaps that matter for your specific AI use cases, and prioritise the remediation work.
"We've acquired companies and now have three data platforms."
Post-merger data rationalisation is a specific discipline. We map what each platform does, design the target architecture, and plan the consolidation.
"Regulators are asking us to demonstrate data lineage."
We design governance frameworks and metadata management practices that produce the audit trail regulators require.
How We Work
Our Approach
Landscape audit
Inventory of data sources, platforms, consumers, and governance practices. Scored against a maturity model.
Gap analysis
Where are you relative to where you need to be for your AI and analytics goals?
Target architecture
Cloud-native or hybrid data architecture designed for your scale, budget, and regulatory context.
Governance design
Roles, policies, data catalogue, lineage tracking, and quality SLAs.
Roadmap
Phased execution plan with quick wins in the first 90 days.
Technologies
Related Offerings
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