Independent technology architecture consultancy
Consulting Services · 09
Create a clear foundation for data, governance and analytics, so the numbers your organisation reports are defined once, owned by someone, and traceable back to a source.
Domains we cover
06Why it matters
Most organisations are not short of data. They are short of agreement about what it means. The same customer, product or measure is defined differently in every system, so reporting becomes negotiation and analytics becomes reconciliation.
Data and information architecture fixes that at the source: a shared model of the domains that matter, clear ownership, and documented flows from where data is created to where it is used. It is the difference between debating which report is right and deciding what to do about the answer.
We work across business and technology stakeholders, and stay independent of platform vendors, so the architecture you get is shaped by your needs rather than a product.
What we deliver
01
A documented view of the data domains, sources, owners and flows you actually have, and a target state that supports where the business is heading. Duplication, shadow data stores and unclear ownership become visible and fixable.
02
Conceptual, logical and physical models with naming, metadata and modelling standards that teams can reuse, so new solutions start from a shared definition instead of a fresh interpretation.
03
Decision rights, stewardship roles, policies and quality rules that fit your operating model. Governance that gets used in delivery, rather than a policy library nobody reads.
04
Integration patterns, interface contracts and pipeline designs for batch, streaming and API-based flows, with lineage documented so you can trace where a number came from and what depends on it.
05
Single sources of truth for customers, products, suppliers and reference sets, with the matching and stewardship rules needed to keep them trustworthy across systems.
06
Warehouse, lakehouse and semantic layer designs that make reporting consistent and repeatable, so analytics teams spend their time on insight instead of reconciling conflicting extracts.
How we work
The work is deliberately incremental. Each step produces something usable on its own, so you can stop after an assessment, continue into modelling, or run the full sequence towards a governed, well-described data landscape.
We interview data owners, architects and business stakeholders, then inventory sources, flows, quality issues and the decisions that data has to support.
We define the data domains, models and standards that describe the business consistently, and test them against real reporting and integration needs.
We agree ownership, decision rights and quality rules with the people who will live with them, then embed them in delivery and change processes.
We hand over models, standards and a sequenced roadmap, and coach your teams so the architecture keeps improving after the engagement ends.
Common questions
As an architecture layer alongside them. Your team knows the systems and the business context; we bring the cross-domain view, the modelling and governance patterns, and the independent challenge that stops the same problem being solved twice in different places.
No. Most of the value comes from agreeing definitions, ownership and flows before any platform decision. Where a platform change is warranted, the architecture work makes that investment decision far easier to justify and far less likely to be reworked.
We trace the issue to its source rather than patching reports. That means agreeing the authoritative source, defining quality rules and owners, and putting controls where data enters the landscape, so trust improves at the cause.
Want to know more?
Talk to us today and see how we can help with your data and information architecture, governance and analytics foundations.
