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

The question we are asked most often by Ennis organisations is whether they need Microsoft Fabric. The answer is frequently no, and saying so has cost us work we did not want.

This page is about building a data platform for an organisation in Ennis, Microsoft Fabric, Azure Synapse, Data Factory and the lakehouse patterns underneath them, with the local economy taken seriously. Ennis's base in medical devices, aviation and airports, and tourism, hospitality and events 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 medical device and engineering manufacturing and proximity to Shannon's aviation cluster.

Does a Ennis 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 Ennis

Medical devices

Device history records, complaint and vigilance data, and post-market surveillance obligations that require linking field events back to manufacturing batches. Source systems typically include ERP, QMS, complaint handling systems, PLM and distributor reporting.

For a platform design, the consequence is specific. Distributor-held data breaks traceability at exactly the point where a field action needs it. So the architecture has to make the raw grain replayable rather than aggregating at ingestion, and the first serving model should be a traceability and complaint model linking batch, shipment, customer and field event, which is the foundation of post-market surveillance reporting.

Tourism, hospitality and events

Booking, channel and rate data with heavy seasonality, plus on-site spend and occupancy that only reconcile once channel commission is accounted for. Gross booking value from online travel agents is compared with direct booking revenue, making the most expensive channel look like the best one.

Systems to plan for: property management system, booking channels and OTAs, revenue management system, EPOS and CRM. Guest data is personal data with cross-border transfer implications when group systems sit outside the region.

Logistics and freight

Event data from scanners, telematics, EDI and transport management systems, each with its own timestamp semantics and time zone handling. Subcontracted volume arrives as spreadsheets, so a third of the network is effectively unmeasured exactly where control is weakest. Drivers' hours records, customs declarations and posting documentation all carry retention obligations and are frequently requested in audit.

A medallion layout for a medical devices 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 Ennis client in medical devices.

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.

Sizing comes from a trial capacity running your real workloads, profiled for compute shape, refresh against query load, concurrency and peak hours. Estimating it from user counts is how organisations end up throttled at month end. 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 medical devices workloads often are, while import still wins on smaller models with heavy DAX.

Migrating from what you have now

Few Ennis 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 ERP.

Residency, latency and the Ireland question

North Europe sits in Dublin, so Irish organisations get in-country residency on the region most of Europe treats as its default. The practical consequence is excellent latency and a short list of residency questions, though cross-border processing still has to be documented where a service falls back to another region.

For Ennis specifically, North Europe (Dublin) is the normal choice. Latency from Ennis 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.

• Ireland hosts the EU establishment of many multinationals, so the DPC is frequently the lead supervisory authority, which raises the bar on analytics documentation well above local headcount.
• The Central Bank's outsourcing and operational resilience expectations apply to cloud analytics platforms used by regulated firms.
• EU-level obligations (DORA, NIS2, CSRD and the AI Act) apply in full, and the Irish implementation timetable is worth tracking per obligation.

Where to go next

If you are weighing a platform decision for a Ennis 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 Ireland and deliver into neighbouring markets regularly. Nearby pages worth reading if your group has sites elsewhere: Tralee, Balbriggan, Athlone, Wexford, Killarney and Castlebar.

Frequently asked questions