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

The question we are asked most often by Sion 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 Sion, Microsoft Fabric, Azure Synapse, Data Factory and the lakehouse patterns underneath them, with the local economy taken seriously. Sion's base in renewables, tourism, hospitality and events, and agriculture and agribusiness 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 hydropower generation and energy research and alpine tourism.

Does a Sion 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 Sion

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. Source systems typically include property management system, booking channels and OTAs, revenue management system, EPOS and CRM.

For a platform design, the consequence is specific. Gross booking value from online travel agents is compared with direct booking revenue, making the most expensive channel look like the best one. So the architecture has to make the raw grain replayable rather than aggregating at ingestion, and the first serving model should be a stay-grain model joining rooms, ancillary spend and channel cost, which is where true channel profitability becomes visible.

Public sector

Case and service data locked inside line-of-business systems with restrictive reporting modules, feeding statutory returns with precisely defined rules. Returns are assembled by hand each cycle by a small number of experienced staff, concentrating risk in individuals.

Systems to plan for: case management systems, finance and ERP, HR and payroll, GIS and gazetteers and grant management. Freedom of information and transparency duties mean published figures must be reproducible, and disclosure control has to be applied in the pipeline.

Renewables

High-frequency turbine or inverter telemetry, weather data, curtailment records and power purchase agreement settlement, across assets in several jurisdictions. Turbine-level telemetry is aggregated at ingestion to save storage, after which underperformance of individual assets cannot be investigated. Guarantee-of-origin and subsidy reporting require auditable generation data, and grid operators impose their own data submission formats.

A medallion layout for a tourism, hospitality and events 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 Sion client in tourism, hospitality and events.

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

The appeal of Direct Lake is that nothing is copied and nothing is refreshed. The risk is the fallback: one unsupported construct and the model quietly behaves like DirectQuery instead. 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 tourism, hospitality and events workloads often are, while import still wins on smaller models with heavy DAX.

Migrating from what you have now

Few Sion 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. Neither requires switching everything at once, which is the approach behind most of the failed migrations we are asked to rescue. The reference pipeline we build first is usually the system that hurts most, which here is normally property management system.

Residency, latency and the Switzerland question

Switzerland North and Switzerland West give in-country residency, which matters more here than almost anywhere else in Europe: banking secrecy, professional secrecy obligations and client expectation all push Swiss data to stay Swiss. Verify per service, because not every Azure or Fabric feature is available in both Swiss regions.

For Sion specifically, Switzerland North (Zurich) is the normal primary with Switzerland West (Geneva) as the pair. Latency from Sion 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.

• The revFADP brought Swiss law closer to the GDPR but not identical to it: records of processing, impact assessments and breach notification follow Swiss rules, and an EU-shaped compliance pack needs adapting rather than copying.
• FINMA outsourcing expectations require documented control over cloud providers, including the right to audit and a tested exit plan.
• Article 321 of the Criminal Code and sectoral secrecy duties restrict who may see client-identifying data, which has direct consequences for row-level security design.

Where to go next

If you are weighing a platform decision for a Sion 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 Switzerland and deliver into neighbouring markets regularly. Nearby pages worth reading if your group has sites elsewhere: Chur, Bern, Lausanne, Lucerne, Lugano and Thun.

Frequently asked questions