Microsoft Fabric and Azure data platforms in Wavre: 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 Wavre, Microsoft Fabric, Azure Synapse, Data Factory and the lakehouse patterns underneath them, with the local economy taken seriously. Wavre's base in pharmaceuticals and biotech, logistics and freight, and professional and legal services 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 major vaccine and biologics manufacturing in the surrounding area and pharmaceutical supply chain and logistics.

Does a Wavre 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 Wavre

Pharmaceuticals and biotech

Regulated data across research, clinical, manufacturing and commercial domains, with validation requirements that make casual changes to a pipeline expensive. Source systems typically include CTMS and EDC, LIMS, MES, SAP ERP, pharmacovigilance systems and licensed market data.

For a platform design, the consequence is specific. Commercial and safety data share a workspace, which creates a compliance exposure that is painful to unwind once reports exist. So the architecture has to make the raw grain replayable rather than aggregating at ingestion, and the first serving model should be a manufacturing and quality model with deviation and batch release reporting, usually the fastest route to a defensible compliance and cost view.

Software and technology

Product event streams at very high volume alongside subscription, billing and support data that must be joined at account grain to be useful. ARR comes from a finance spreadsheet with manual adjustments, so restating a prior period requires archaeology and diligence becomes painful.

Systems to plan for: billing and subscription platform, CRM, product event pipeline, support platform and finance system. Product telemetry on identifiable users needs a lawful basis and consent handling, and SOC 2 or ISO 27001 evidence often covers the analytics estate.

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 a pharmaceuticals and biotech 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 Wavre client in pharmaceuticals and biotech.

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.

The sizing exercise is empirical: profile each workload, separate background refresh from interactive query, count real concurrency, find the true peak, then prove the number on a short-lived capacity before anything is bought. 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 pharmaceuticals and biotech workloads often are, while import still wins on smaller models with heavy DAX.

Migrating from what you have now

Few Wavre 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 keep the old platform running until each domain is proven. The alternative, moving everything at once, is how migrations end up reversed. The reference pipeline we build first is usually the system that hurts most, which here is normally CTMS and EDC.

Residency, latency and the Belgium question

Most Belgian deployments land in West Europe, which is physically in the Netherlands, or in France Central. Microsoft has announced a Belgian datacentre region, so check current availability before committing to an architecture that assumes in-country residency, and in the meantime document the EU-but-not-Belgian position for your data protection officer.

For Wavre specifically, West Europe (Netherlands) is the normal primary with France Central (Paris) as the pair. Latency from Wavre 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.

• Belgium's federal structure means some reporting obligations sit with the regions (Flanders, Wallonia and Brussels) rather than nationally, which multiplies the datasets a single organisation must produce.
• Language legislation affects employee-facing systems: reporting used in employment contexts may need to be available in the language of the region where staff are employed.
• As the host of the EU institutions, Brussels has an unusual concentration of organisations working to EU-level reporting rules ahead of national implementation.

Where to go next

If you are weighing a platform decision for a Wavre 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 Belgium and deliver into neighbouring markets regularly. Nearby pages worth reading if your group has sites elsewhere: Brussels, Charleroi, Namur, Mons, Mechelen and Louvain-la-Neuve.

Frequently asked questions