Data Engineering & Data Warehousing
If month-end reporting requires manually reconciling multiple Excel files, the real problem is not the report—it is the data behind it. We integrate your ERP, manufacturing and warehouse systems into a single, trusted data platform so finance, production and sales all work from the same numbers.
Request an assessmentWhen you need this
- Month-end close takes days because somebody reconciles system outputs by hand.
- Two reports answer the same question with different numbers, and nobody can say which is right.
- Your most important report lives in a spreadsheet on one colleague’s laptop.
- Every new report needs an external developer, so people stop asking for new reports.
- You want forecasting or serious analysis, but there is no clean history to build it on.
What you get
The result is one reliable data source that Power BI reports, management dashboards and later predictive analytics can all build on with confidence. Less manual work, a faster month-end close, and better-grounded business decisions.
- A data warehouse in your own cloud or on your own server, with a documented model
- Automated nightly ingestion from ERP, production system and warehouse software
- A business semantic layer, so "waste", "yield" and "stock" mean the same thing in every report
- Power BI reports for both daily operational and month-end management questions
- Data quality tests that alert on a broken load — before the wrong number reaches a report
- Written documentation, code in your repository, and a handover session
How it works
Assessment — 2 weeks, fixed price
We walk your systems and map where data is created, where it breaks, and what still runs by hand. You get a short readable report with a prioritised fix list and effort estimates.
Foundation — 2 to 3 weeks
We stand up the warehouse, write the first ingestion jobs and wire in data quality tests. From this point on there is fresh, checked data every morning.
Modelling and reporting — 2 to 3 weeks
We build the semantic layer and rebuild the reports you currently assemble by hand. This is where month-end close starts getting shorter.
Handover
Documentation, training, access sorted out. From then on the system is yours — including if you later bring in somebody else.
Technologies
Scope & pricing
- Timeline
- 2-week assessment + 4 to 8 weeks of build
- Price
- Assessment: €3,000 · Build: €6,000 – 20,000
All prices are indicative and exclude VAT. A detailed quotation is provided after the assessment, once we understand your systems and requirements.
Frequently asked questions
Do we have to move to the cloud?
No. If the data is sensitive or internal policy rules it out, the same thing can be built on your own server. Cloud is cheaper and needs less operational care, but it is not a precondition.
What if our system is old and has no proper API?
That is the normal case, not the exception. Database-level reads, scheduled exports or file-based handoff — there is almost always a workable route. The assessment settles this before anyone commits.
Does this leave us dependent on an outside person?
That is why documentation and handover are in every quote. The code sits in your repository, we use standard tools, and after training your internal IT or another supplier can pick it up.
How disruptive is it day to day?
Barely. We read data, we do not write back into production systems. Expect roughly 2 to 3 hours a week of your colleagues’ time during the assessment, and less after that.
Related services
- Power BI Reports & Dashboards
If management meetings focus on debating the numbers instead of making decisions, your reporting is not doing its job. We build Power BI dashboards that stay up to date automatically, so management, production and sales all work from the same trusted data.
- Predictive Analytics & Demand Forecasting
We build demand forecasting models based on your own historical sales data, helping you make better-informed production and procurement decisions. Predictive analytics and machine learning help reduce inventory and waste while improving production planning. The model typically requires at least two to three years of well-structured sales data.