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Enterprise and Data Architecture

Architecture decisions that keep options open and costs under control.

Architecture is where strategy becomes concrete: which platforms, which patterns, which standards, and in which order. Good architecture decisions are reversible where possible and deliberate where not.

We work at two levels: enterprise architecture to connect business capabilities, applications and data, and data architecture to design the platforms, models and integration that analytics and AI depend on.

What is included

Service offerings

03.1

Target data architecture

Warehouse, lakehouse, mesh or hybrid, designed for your workloads.

  • Current-state assessment
  • Target architecture
  • Transition roadmap

03.2

Enterprise architecture

Capability maps, application and data landscapes aligned with TOGAF.

  • Capability map
  • Application and data portfolio
  • Architecture principles

03.3

Data modelling

Conceptual, logical and physical models for domains and data products.

  • Enterprise data model
  • Domain models
  • Modelling standards

03.4

AI and knowledge architecture

Retrieval, vector, graph and model-serving layers designed as shared services.

  • Reference architecture
  • Pattern catalogue
  • Security design

03.5

Architecture governance

Standards, design authority and decision records that keep delivery aligned.

  • Design authority
  • Architecture decision records
  • Standards catalogue

When to call us

Signs you need this

  • A platform decision is due and the options are unclear.
  • Data is duplicated across many systems with no clear source of truth.
  • AI initiatives each build their own infrastructure.
  • Integration has grown into point-to-point complexity.

Approach

How we work

  1. 01Understand

    Business capabilities, workloads, constraints and current estate.

  2. 02Options

    Compare architecture options with explicit trade-offs and costs.

  3. 03Design

    Target state, standards and a transition roadmap in deliverable steps.

  4. 04Govern

    Keep delivery aligned through a light design authority.

Standards and frameworks

Aligned with recognised practice

  • TOGAF Standard
  • ArchiMate
  • Data mesh and data product principles

Solutions

Where this service is applied

Data foundations

Modern Data Platforms

One governed platform for analytics and AI, designed for your scale and your region.

View solution Applied AI

Knowledge and Retrieval Systems

Make the organisation's knowledge findable, citable and usable by AI.

View solution Decision intelligence

Decision Intelligence Platforms

Connect the data, the analysis and the action behind your most important decisions.

View solution Applied AI

Enterprise AI Assistants

Secure assistants that know your business and act within your rules.

View solution

Technology

Platforms we work with

Vendor-neutral: examples of platforms commonly used in this service. Names identify technologies only and do not imply a partnership.

  • Databricks
  • Snowflake
  • Microsoft Fabric
  • Google BigQuery
  • Apache Iceberg
  • Delta Lake
  • Neo4j
  • Apache Kafka
See the full technology ecosystem →

Insights

Further reading

Data Architecture Decides AI Success

Leading models now score within a few points of each other. What an AI system can reach, how fresh it is, whose permissions it obeys and whether its answer can be traced are architecture decisions, and they now decide the outcome.

Read →

TOGAF, EA and the AI Data Foundation

AI programs fail on data and integration, which is exactly what enterprise architecture is meant to govern. The fix is not more framework. It is a handful of living artifacts that make data and AI decisions explicit, traceable and reusable.

Read →

Warehouse, Lake, Lakehouse or Mesh?

The question is usually framed as a choice between four architectures. It is really two separate decisions: where data is stored and processed, and who owns and governs it. Most enterprises need an answer to both.

Read →

Data Products as Business Assets

A data product is not a dataset with a new label. It is a promise to consumers, written down as a contract, owned by a named person and measured in public. Without the promise, nothing has changed.

Read →

Talk to us about Enterprise and Data Architecture

Engage this service on its own or as part of a solution. We will agree scope, outcomes and the right team with you.

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Reliable, tested data pipelines that analytics and AI can depend on.

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