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

Microsoft Fabric is a genuine step forward and a genuine way to spend money quickly, and which one you get depends almost entirely on decisions made in the first fortnight.

This page is about building a data platform for an organisation in Dundalk, Microsoft Fabric, Azure Synapse, Data Factory and the lakehouse patterns underneath them, with the local economy taken seriously. Dundalk's base in software and technology, logistics and freight, and medical devices 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 technology and shared-services operations and cross-border logistics with Northern Ireland.

Does a Dundalk organisation actually need Fabric?

The case for Fabric gets strong when more than one of these holds: import models under strain, the same data needed through both SQL and notebooks, governed self-service for several teams, retention that a desktop model cannot carry, or a Premium capacity already on the bill. 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 Dundalk

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.

Medical devices

Device history records, complaint and vigilance data, and post-market surveillance obligations that require linking field events back to manufacturing batches. Distributor-held data breaks traceability at exactly the point where a field action needs it.

Systems to plan for: ERP, QMS, complaint handling systems, PLM and distributor reporting. EU MDR post-market surveillance and vigilance reporting require a reproducible data trail from field event back to production batch.

Higher education and research

Student lifecycle, research grant and estates data in separate systems, with statutory returns and league-table submissions on fixed annual cycles. Statutory returns and internal management reporting are produced through separate routes, so published figures and internal figures disagree. Student data is personal data with additional duties around special-category attributes, and research data may carry funder-specific restrictions.

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 Dundalk 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.

We size capacity by measuring rather than estimating: each workload profiled for compute shape, background refresh against interactive query, concurrency and peak hours, then validated on a short-lived trial capacity with your real 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 reads Delta files in OneLake with no import refresh and no DirectQuery round trip, but unsupported constructs trigger fallback and performance then depends on the SQL endpoint. 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 Dundalk 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 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 Dundalk specifically, North Europe (Dublin) is the normal choice. Latency from Dundalk 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 Dundalk 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: Athlone, Limerick, Galway, Waterford, Tralee and Letterkenny.

Frequently asked questions