One place where all your business data comes together and stays for years.

Management wants to know how the margin per client has developed over five years. The orders from back then are in the old ERP, today's are in the new one, and the costs sit in the accounting package. Someone spends a week building it in Excel, and when the answer arrives, everyone doubts the figures. The same question returns next quarter and the work starts again. A data warehouse is the place where that work happens once and is then done.

Why a spreadsheet is not a data warehouse

Your source systems are built to do today's work. The ERP knows the open orders, the online store knows the current shopping carts, and the accounting package knows this financial year's invoices. What was there last year has been overwritten or archived, and a client called "Janssen BV" in one system is called "Jansen" in another. As long as you look inside a single system, you barely notice. Once you combine sources or look back in time, it gets in your way.

A data warehouse copies the data from all your systems every night, converts it into one shared model, and keeps every version. A client has one number in it, a product one description, and an order one date, wherever it came from. The history stays, even if you switch ERP in three years. A spreadsheet starts over with every export.

Warehouse or lakehouse: which fits you

A classic data warehouse works with tables that you design in advance. That suits administrative data well: orders, invoices, hours, stock levels. Everything has a fixed shape, and the questions are known. For most small and mid-sized companies, this is the right answer, and the cheapest to maintain.

A lakehouse also keeps the raw files: sensor readings from a machine, log files, PDFs, photos, and exports you do not yet know how to model. You store everything first and add structure later. That is useful if you collect measurement data through an IoT data platform, or if you want to train AI on your own documents. We choose this together with you, based on the data you have and the people who will work with it. If a plain data warehouse is enough, we tell you right away and build nothing bigger than needed.

Your first tables filled in ten business days

We do not start with a forty-page architecture document. We pick the two sources that the most important question must come from, usually the ERP and the accounting package, and build a first version with them. Within ten business days, you have a database with real data and a few tables you can look through yourself. You see right away whether the terms are right and whether the figures match what you expect.

We handle the feed with Data pipelines: small, verifiable steps that run every night, check themselves, and send an alert if a source does not respond or a count suddenly halves. From the first version, we connect the other sources, one at a time. Whatever you build on top, whether that is Data and reporting or a model that forecasts your stock, reads from the same tables. That way, you define a term like "revenue" in only one place.

Yours, in the EU, and ready for later

The data warehouse runs in our managed environment in the EU, and you own the database, the data model, and the code that fills it. We use open standards and common database technology, so you are not tied to one vendor or to us. Personal data gets its own place with restricted access, and we record who may read which tables. That also gives you the basis for Data governance and for the agreements that come with GDPR compliance.

Once it is in place, you can manage it yourself or leave it to us. We deliver documentation of the model and the processing, and we walk through it with the people who will look in it every day. A data warehouse is not a project that is ever finished. It is a foundation that grows with every new question. The first step is a free intake, where we look at which questions you cannot answer today.