Microsoft Fabric and Azure data platforms in Waterford: 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 Waterford organisations find themselves in when they call us.

This page is about building a data platform for an organisation in Waterford, Microsoft Fabric, Azure Synapse, Data Factory and the lakehouse patterns underneath them, with the local economy taken seriously. Waterford's base in pharmaceuticals and biotech, medical devices, and ports, terminals and maritime 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 pharmaceutical and medical device manufacturing and a deep-water port at Belview.

Does a Waterford organisation actually need Fabric?

Look for a cluster rather than a single trigger: import refreshes that are getting uncomfortable, demand for SQL and notebooks against one copy, self-service across more than one team, retention that rules out a desktop model, or an existing Premium commitment. 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 Waterford

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.

Pharmaceuticals and biotech

Regulated data across research, clinical, manufacturing and commercial domains, with validation requirements that make casual changes to a pipeline expensive. Commercial and safety data share a workspace, which creates a compliance exposure that is painful to unwind once reports exist.

Systems to plan for: CTMS and EDC, LIMS, MES, SAP ERP, pharmacovigilance systems and licensed market data. GxP data integrity expectations (attributable, legible, contemporaneous, original, accurate) apply to analytics pipelines handling regulated data.

Food and drink manufacturing

Short shelf life, high SKU churn, promotional volatility and retailer scorecards that measure you on their definitions rather than yours. Internal service levels read green while the retailer scorecard reads amber, because the two measure different events. HACCP and traceability obligations mean batch records must be retrievable quickly enough to support a withdrawal within hours.

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 Waterford 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.

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 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 medical devices workloads often are, while import still wins on smaller models with heavy DAX.

Migrating from what you have now

Few Waterford 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 Waterford specifically, North Europe (Dublin) is the normal choice. Latency from Waterford 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 Waterford 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: Cork, Galway, Dundalk, Tralee, Limerick and Drogheda.

Frequently asked questions