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Data & analytics services

Design, integrate and operationalise trusted data environments that support insight, performance management and strategic decision-making.

The problem

What usually brings organisations to us

Inconsistent data across systems and business units

Every function has its own version of the truth, and reconciliation happens in spreadsheets at month end.

Legacy platforms that cannot support real-time or AI-driven analytics

The architecture was built for batch reporting and will not carry what is now being asked of it.

Manual reporting and delayed insight

By the time a number reaches a decision-maker, the window it described has closed.

Rising regulatory, security and audit requirements

Evidence has to be produced on demand, with lineage, and the current setup cannot show its working.

Capability

End-to-end data and analytics services

We define data vision, operating model and architectural foundations that align information capability with business strategy, regulatory requirements and long-term transformation goals — so every data initiative is built for scale, trust and sustained value.

Data strategy & operating model

Enterprise data strategies and governance models that align data initiatives with organisational goals and digital transformation priorities.

Enterprise data architecture

Logical and physical data architectures supporting analytics, master data management, real-time processing and enterprise-wide reporting.

By sector

Analytics shaped around the decisions each sector actually makes

Trusted asset, tenant and compliance insight supporting regulatory reporting, operational assurance and service improvement.

  • Property, tenant and compliance data consolidation
  • Repairs, maintenance and contractor performance dashboards
  • Regulatory reporting and audit evidence automation
  • Risk, safety and service performance analytics

Capabilities

What we build

Data platform modernisation

Re-architect legacy environments into scalable, cloud-ready platforms supporting real-time analytics, AI workloads and secure enterprise reporting.

Enterprise data modelling

Standardise and harmonise data models across domains for consistent reporting, master data alignment and enterprise-wide analytics.

Machine learning and decision systems

Predictive models, ML pipelines and intelligent decision systems that drive automation, forecasting and optimisation.

Governance, lineage and controls

Operationalise governance, lineage, access controls and quality frameworks to ensure integrity, security and regulatory readiness.

Data pipeline engineering

Automated pipelines that ingest, transform, validate and deliver trusted data across business systems and analytics platforms.

BI and self-service reporting

Interactive dashboards, self-service reporting and advanced visualisation providing operational, financial and commercial insight.

Real-time architecture

Streaming architectures delivering low-latency insight for operational monitoring and event-driven workflows.

Generative AI in the data estate

Generative AI integrated across analytics, reporting and data platforms to enhance insight discovery, automation and decision support.

FAQ

Frequently asked questions

Almost never. We start where the pain is measurable — usually one reporting domain — and prove the model, the governance and the pipeline there. That first domain then becomes the pattern the rest of the estate follows.

Start your data and analytics transformation.

Bring us the report nobody trusts. It is usually the fastest way to find what the architecture is missing.