What does a data warehouse cost for an SME? Honest numbers

Google what a data warehouse costs and you'll find two kinds of answers: "it depends" and a form for a free consultation. Both true, both useless when you simply want to know whether this is a ten-, twenty- or hundred-thousand euro investment before you raise it internally.

I work with fixed prices that are simply published on my site, so let me answer the question the same way. With numbers.

What does a data warehouse cost for an SME?

For an SME with a handful of source systems, a serious data warehouse — modelled, tested, with reporting on top, delivered so your own team can carry it — costs roughly €15,000 to €25,000 with a freelancer. An agency typically adds 50 to 100% on top. If you see offers well under €10,000, you're usually not buying a warehouse but a dashboard with some connectors — which can be exactly the right choice; more on that below.

For comparison, from public Dutch market research:

Scenario	Indicative price
Serious Power BI dashboard, without a warehouse underneath	around €5,000
Two dashboards, three sources and a data warehouse	around €17,500
Data warehouse with a freelancer (modelled, tested, transferable)	€15,000 – €25,000
The same project with an agency	+50 to 100%
Freelance data engineer, hourly rate	€80 – €130
BI consultant, day rate	€600 – €1,000+

What you're paying for (hint: not the technology)

The software is not the problem. The engines I build warehouses on are open source or cost tens of euros per month. What you're buying is work, and that work sits in four places:

1. Definitions. What counts as a customer? When does an order count — at ordering, delivery or payment? Every figure your departments currently disagree about is a definition someone has to pin down. This is the hardest and most valuable part of the engagement, and it has nothing to do with technology.
2. Modelling. Translating those definitions into a data model that still holds next year, when a source gets added or the organisation changes.
3. Testing. The difference between "the report ran this morning" and "the report is right this morning". Checks at every step, so a problem in the source is caught before the monthly meeting finds it.
4. Handover. Documentation and a handover session, so your team can carry on without being chained to the builder.

You don't buy a warehouse because you have data. You buy one because you have arguments — and you don't want to have them again every month.

What pushes the price up or down

• The number of sources. Every connection is work: extracting, cleaning, testing. Three sources is a different project than ten.
• The state of your definitions. If they're settled, the build starts immediately. If they still have to be fought out, that's the first week.
• History. "How did this look last quarter?" sounds innocent, but reporting correctly across reorganisations is an explicit design choice that takes time.
• The reporting layer. One management dashboard is not fifteen reports for three audiences.
• Who will maintain it. Delivering it transferable to your own team is one-off work; ongoing operation is a subscription — mine is called Reporting on autopilot.

What you can do yourself to keep it cheap

You can do this part without hiring anyone, and it genuinely saves money:

• Pin down the definitions before the build starts. One working session with the departments involved, writing down what each core figure means, saves a week of mid-project debate.
• Start with the figures decisions actually run on. Not "everything we have", but the five to ten KPIs the monthly conversation is really about. You can always extend; starting too big always backfires.
• Don't buy tooling yet. The licence choice follows from the model, not the other way around. Organisations that buy a platform first and then work out what goes on it pay twice.

When you should not buy a warehouse

Honesty sells poorly but works well, so: there are situations where I advise against it.

• One source, one report. Then a good dashboard straight on that source is faster and a fraction of the price. A warehouse becomes worthwhile once figures from multiple systems have to agree with each other.
• The organisation changes every quarter. A warehouse anchors definitions; if those still shift weekly, it's too early.
• Nobody owns reporting. Without an owner, every warehouse decays into exactly the situation it was built to fix. Sort the ownership first, then the technology.

What I charge

My package Your data warehouse costs from €15,000 and takes three to four weeks. For that you get the smallest honest version: pipelines on a bounded set of sources, a layered and tested data model, one definition per figure, a Power BI dashboard on the KPIs, and documentation plus handover so your team can carry it. More sources or more complex history push the price up — you hear that up front, not afterwards.

Do the maths yourself: four weeks of senior work at the hourly rates above quickly reaches €16,000 on an hourly basis — with no fixed scope and no fixed price. The fixed price isn't a discount; it's the same money with the risk on my side of the table instead of yours.

The cheapest way to start, by the way, is not the warehouse itself but the Data scan: it delivers the target model that serves as the blueprint for the build — the first build week gets shorter, and you know where you stand before committing.

What such a warehouse looks like when it's done — star schema, tests, documentation — is something I show in the open-data warehouse I built in public.

Recognise the arguments about whose number is right? Book an intro call — I'll gladly help you place your situation on the ladder, no strings attached.