Part of Data & AI
Data platforms
Design and build data platforms that bring scattered sources together, reliably and at a cost you can sustain.
Data platforms fail when they are designed around tools rather than workloads, budgets and local constraints. We design for your connectivity, skills and regulatory context, and build something your team can run without us.
When to call us. Signs it’s time for this work.
- Analysts spend most of their week extracting and reconciling spreadsheets.
- Core systems cannot share data without manual exports.
- Your current warehouse is slow, expensive or no longer supported.
- Data residency rules limit where your data can be hosted.
What’s included. Scoped to your context, delivered end to end.
- 01
Architecture and platform selection
Cloud, on-premise or hybrid options weighed against cost, data residency, connectivity and the skills you have in-house.
- 02
Data integration pipelines
Reliable ingestion from ERP, core banking, billing and field systems, with monitoring and clear error handling.
- 03
Warehouse and lakehouse build
Structured, documented data models that analysts and applications can query with confidence.
- 04
Platform operations and FinOps
Run-books, access controls, cost monitoring and backup routines that keep the platform healthy after go-live.
How we work. Four phases, with value at every step.
- 1
2–3 weeks
Assess
Map sources, volumes, current costs and constraints, including bandwidth, hosting options and residency rules.
- 2
3–4 weeks
Design
Target architecture, technology choice and a phased build plan with a realistic total cost of ownership.
- 3
8–16 weeks
Build
Deliver in increments, each bringing a priority data domain into production for real users.
- 4
4–6 weeks
Transfer
Pair with your engineers, hand over documentation and step back once your team runs it confidently.
What you walk away with
- Target data architecture
- Platform selection and cost model
- Production data pipelines
- Documented data models
- Operations run-book
What changes
- Less time preparing data, more time analysing it.
- One reliable source feeding reports and applications.
- Predictable, controlled platform running costs.
Where we do this work. Sectors where this service matters most.
Common questions.
Should we choose cloud or on-premise?
It depends on residency rules, connectivity, cost and skills, and hybrid is often the answer. As an independent firm, we recommend what fits, not what we resell.
Can you work with our existing systems?
Yes. A good platform sits alongside legacy systems rather than replacing them. We connect to what you have and plan retirement only where it makes sense.
How long before we see results?
The first data domain reaches users at the end of the first build increment, within weeks. We avoid long programmes that deliver nothing until the end.
More in Data & AI. Offerings that often run together.
- Data strategy & governanceDecide which data matters, who owns it and how it is managed, so decisions rest on figures people trust.
- Applied AI & automationPut machine learning and automation to work on specific operational problems, with measurable value and people kept in control.
- Analytics & business intelligenceTurn data into dashboards, reports and analysis that leaders read and act on, rather than simply receive.
Discuss Data platforms
Tell us where you are. We’ll tell you honestly whether and how we can help.