Data and Analysis In-company Training
OEM provides fully customised in-company data and analysis training for your organisation. From Microsoft Power BI for business analysts to DP-600 Microsoft Fabric and DP-900 Azure Data Fundamentals for data professionals. At your location or in Almere, maximum 12 participants per group.
SLIM subsidy for in-company data training
As a Dutch SME, you may be eligible for the SLIM subsidy for ICT training. The Dutch government reimburses 60% of your training costs, up to a maximum of €24,999. Data and analysis training courses are fully eligible for subsidy. The second 2026 application period opens on 10 August.
Microsoft Power BI In-company
- Microsoft Power BI Basic | In-company Training — Power BI basic training on location for your team. From loading data to your first dashboard. €1,499 excl. VAT.
- Microsoft Power BI Advanced | In-company Training — DAX formulas, data modelling and advanced visualisations. €1,499 excl. VAT.
- PL-300: Microsoft Power BI Data Analyst | In-company Training — Preparation for the PL-300 exam. €4,797 excl. VAT.
Microsoft Fabric and Azure Data In-company
- DP-900: Microsoft Azure Data Fundamentals | In-company Training — Entry-level Azure Data for IT professionals and business users. €1,679 excl. VAT.
- DP-600: Microsoft Fabric Analytics Engineer | In-company Training — End-to-end analytics solutions in Microsoft Fabric. €6,396 excl. VAT.
- DP-700: Microsoft Fabric Data Engineer | In-company Training — Building data pipelines and lakehouses in Microsoft Fabric. €6,396 excl. VAT.
Every in-company training includes
- A free intake consultation in advance to determine the level and learning objectives
- Training at your location or in Almere, maximum 12 participants per group
- Multiple groups on the same day possible for larger teams
- Certificate of participation in PDF for each participant
- Evaluation afterwards
Request a quote directly via our quote page. Don't forget the SLIM subsidy — as a Dutch SME the government reimburses 60% of your training costs.
