Microsoft Fabric and Azure data platforms in Nottingham: architecture, capacity and cost

A Fabric capacity bought before anyone has profiled the workloads is an expense in search of a benefit. That is the position several Nottingham organisations find themselves in when they call us.

This page is about building a data platform for an organisation in Nottingham, Microsoft Fabric, Azure Synapse, Data Factory and the lakehouse patterns underneath them, with the local economy taken seriously. Nottingham's base in retail, insurance and reinsurance, and healthcare provision determines the data volumes, the latency requirements and the retention obligations, and those three things decide the architecture. The client population here is shaped by a long-established retail and consumer health presence and financial services and insurance operations.

Does a Nottingham organisation actually need Fabric?

Fabric starts to earn its keep when several of the following are true at once: volumes that strain an import model, a genuine need for both SQL and notebook access to the same data, several teams requiring governed self-service, retention obligations that make a desktop model impossible, or an existing Premium capacity. One analyst maintaining three import models that refresh in twenty minutes does not need a capacity, and buying one will not improve anything.

What the data actually looks like in Nottingham

Insurance and reinsurance

Policy, premium and claims data where the same risk is represented differently in underwriting, finance and claims systems, and where development over time is the whole point. Source systems typically include policy administration, claims management, actuarial reserving models, reinsurance systems and broker feeds.

For a platform design, the consequence is specific. Actuarial results land as spreadsheets with no lineage, so the reported reserve movement cannot be tied back to the model run that produced it. So the architecture has to make the raw grain replayable rather than aggregating at ingestion, and the first serving model should be a policy and claim fact at the grain actuarial and finance both recognise, with an accident period dimension built in from the start.

Healthcare provision

Patient-level activity data of the highest sensitivity, with cohort and pathway definitions that must be stable and clinically defensible. Two reports on the same pathway include different patients, and clinical confidence collapses the first time the difference surfaces in a meeting.

Systems to plan for: electronic patient record, patient administration system, theatre scheduling, LIMS and e-rostering. Health data attracts the stricter GDPR special-category conditions, and small-number suppression must be enforced in measures including drill-through.

Professional and legal services

Time, billing and pipeline data where almost every meaningful figure is an allocation, and where confidentiality obligations constrain who may see matter-level detail. Four definitions of utilisation circulate simultaneously, so partner behaviour responds to whichever figure appears in the meeting they attend. Matter confidentiality and information barriers must be inherited by analytics through row-level security, not re-implemented loosely.

A medallion layout for an insurance and reinsurance business

The medallion pattern is not complicated, and it is routinely implemented badly: a bronze layer that has already lost fidelity, a silver layer with no testable rules, and a gold layer that is really just the silver layer with different names. Here is how we would lay it out for a Nottingham client in insurance and reinsurance.

Capacity sizing and what it really costs

Fabric capacity is billed by capacity unit. An F2 is roughly US$0.36 per hour pay-as-you-go, about US$260 a month, with around 40 per cent off for a one-year reservation. An F64, the smallest SKU at which report consumers no longer need an individual Pro licence, is roughly US$8,400 a month pay-as-you-go or around US$5,000 reserved.

The arithmetic that matters: F64 only becomes cheaper than per-user licensing somewhere in the region of 350 to 600 readers, depending on the discount you actually pay and whether you reserve capacity. Below that, Pro or PPU per user is normally the right answer, and buying capacity for prestige is a straightforward waste of money.

Capacity is sized from measurement, not from a spreadsheet. Each workload is profiled for its compute shape, for background refresh against interactive query, for concurrency and for when the peaks actually fall, then the result is checked on a trial capacity running your own data. The output is a sizing model that states expected utilisation at launch, at double the readers, and the specific point at which you would need the next SKU. Always price from the current Microsoft rate card for your region and agreement. Any figure in an article older than a quarter should be treated as an order of magnitude, not a quote.

Direct Lake, import or DirectQuery

With Direct Lake the model reads Delta directly from OneLake, so there is no refresh to schedule and no query round trip. The catch is the condition attached: anything unsupported falls back, and you are then on SQL endpoint performance without having chosen it. We test it against an import model on your own data and choose on the measured result. In practice Direct Lake tends to win on large, frequently landing tables, which insurance and reinsurance workloads often are, while import still wins on smaller models with heavy DAX.

Migrating from what you have now

Few Nottingham organisations start from nothing. The realistic options are a serving-layer-first adoption, where Fabric takes the gold layer and reporting while existing engineering stays in place, or a domain-by-domain migration with the old platform retained until each domain is validated. Neither requires switching everything at once, which is the approach behind most of the failed migrations we are asked to rescue. The reference pipeline we build first is usually the system that hurts most, which here is normally policy administration.

Residency, latency and the United Kingdom question

Azure UK South and UK West give genuine in-country data residency, and Power BI tenants can be provisioned in the United Kingdom region. Note that some workloads, certain preview features and a handful of AI services, still process outside the region, so residency claims should be checked per service rather than assumed tenant-wide.

For Nottingham specifically, UK South (London) is the normal primary with UK West (Cardiff) as the pair. Latency from Nottingham to that region is not usually a constraint for analytical workloads; the constraints that bite are feature availability per region and the processor chain your data protection officer will ask about.

• UK GDPR data-minimisation and storage-limitation duties apply directly to analytics copies of personal data, which is where most estates quietly fail.
• Consumer Duty outcome monitoring has made customer-level analytics a supervisory expectation for regulated firms, not an optional capability.
• SECR energy and carbon reporting requires auditable activity data, which usually means the same lineage discipline as financial reporting.

Where to go next

If you are weighing a platform decision for a Nottingham organisation, a workload assessment will answer it with evidence in two to three weeks, and the written recommendation is yours whatever you decide. Book a technical review.

We work across United Kingdom and deliver into neighbouring markets regularly. Nearby pages worth reading if your group has sites elsewhere: Leeds, Cardiff, Southampton, Stockport, Winchester and London.

Frequently asked questions