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

Before deciding on a lakehouse, it is worth establishing whether your data actually outgrew an import model or simply outgrew the person maintaining it.

This page is about building a data platform for an organisation in Crawley, Microsoft Fabric, Azure Synapse, Data Factory and the lakehouse patterns underneath them, with the local economy taken seriously. Crawley's base in aviation and airports, logistics and freight, and pharmaceuticals and biotech 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 major international airport and one of the South East's largest business districts at Manor Royal.

Does a Crawley 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 Crawley

Logistics and freight

Event data from scanners, telematics, EDI and transport management systems, each with its own timestamp semantics and time zone handling. Source systems typically include transport management system, warehouse management system, telematics, EDI messages and customs platforms.

For a platform design, the consequence is specific. Subcontracted volume arrives as spreadsheets, so a third of the network is effectively unmeasured exactly where control is weakest. So the architecture has to make the raw grain replayable rather than aggregating at ingestion, and the first serving model should be a canonical event model with normalised UTC timestamps and documented source precedence, which is the prerequisite for every duration measure.

Industrial machinery and engineering

Project and configuration data as much as production data: engineered-to-order items, long lead times, and service revenue that outlives the original sale. Project margin is only known at completion, so loss-making contracts are discovered when it is far too late to act.

Systems to plan for: ERP, PLM / CAD, project management, field service management and CRM. Export control and dual-use classification data should be modelled explicitly where machinery is shipped outside the EU and UK.

Shared services and business process outsourcing

Transaction and case volumes across multiple client entities, with contractual service levels, workforce data and per-client confidentiality boundaries. One generic service-level calculation is applied to every contract, so reported performance does not match what clients are entitled to measure. Client data segregation is a contractual obligation, and processor duties under GDPR apply to the provider rather than only the client.

A medallion layout for a logistics and freight 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 Crawley client in logistics and freight.

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

Direct Lake removes both the import refresh and the DirectQuery hop by reading Delta in place. It also carries a condition most teams discover late: unsupported constructs silently fall back, and the model then performs like DirectQuery. 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 logistics and freight workloads often are, while import still wins on smaller models with heavy DAX.

Migrating from what you have now

Few Crawley 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. Both avoid a big-bang cutover, which is the pattern that produces the rollbacks we get called in to repair. The reference pipeline we build first is usually the system that hurts most, which here is normally transport management system.

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 Crawley specifically, UK South (London) is the normal primary with UK West (Cardiff) as the pair. Latency from Crawley 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 Crawley 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: Paisley, Luton, Wrexham, Liverpool, Belfast and Wakefield.

Frequently asked questions