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Power BI specialist in Eindhoven

For manufacturing companies in Brainport, we bring ERP, machine and maintenance data together in a single Power BI model, as we did when building Power BI dashboards for Ammega’s planning.

Discuss your production figures Read the Ammega case study

Our Power BI dashboards and app helped manufacturer Ammega reduce the number of separate Excel files

Ammega wanted better insight into its business processes and a clearer view of its current situation. Working closely with stakeholders, we built several Power BI dashboards and a Power BI app, tailored to management, planning and finance, among others.

Read the case study

Why do production and maintenance count downtime differently?

The control system logs faults, the ERP system tracks orders, and maintenance keeps its own records. Each department therefore calculates availability differently. A Power BI model puts the sources side by side, with one definition for each metric.

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In Brainport, production, maintenance and planning prefer to work from the same figure

Discuss your production figures

Machine data from your own network

If shop-floor data is stored on a server in your own network, an on-premises data gateway connects that source to the Power BI service.

One definition of downtime

Planned maintenance, breakdowns and waiting for materials each have their own code, so production and maintenance see the same availability figure.

By line or by client project

High-tech suppliers often work on a client-project basis. In the model, you choose whether to view figures by line, machine or project.

Reports for each audience

For management, planning and finance, all based on the same model—as with the bespoke dashboards and Power BI app we built for Ammega.

The model starts on the shop floor, not in the report

  1. Sources and definitions

    Map the ERP, control and maintenance systems, and define what counts as downtime or output for each metric.

  2. Gateway and first model

    Make the data sources securely accessible, then develop the model for one production line or department and validate it on the shop floor.

  3. Roll-out and management

    Other production lines and sites follow the same model. Assign clear ownership for data refreshes and access permissions.

Are ERP and factory control systems enough, or is a dedicated Power BI model worth it?

Talk it through with us

A good fit if

Production, maintenance and planning each rely on their own lists, and you want to see ERP, machine and maintenance data together in one view.

Not a good fit if

Your control system screens and ERP reports already answer your questions. Or departments disagree on what counts as downtime: in that case, agree on definitions first.

What determines the scope

How many production lines, machines and sites are included, whether the data is in the cloud or on the factory floor, how often the figures need updating, and who will manage the model after delivery.

Does machine data need to be real-time?

For a daily start-up meeting or weekly review, refreshing the data beforehand is enough. Real-time data is worth it if someone acts on it during a shift, but it requires more management of the source and the model.

Scheduled import, DirectQuery or a data platform behind your production reporting?

Import with scheduled refresh

Choose this if a few set times each day are enough. We recommend it for most daily kick-offs and weekly meetings: it’s fast, predictable and easy to manage.

DirectQuery

Choose this if the figures need to reflect the source and that source can handle the queries. Power BI then queries the database directly with every click.

A data platform

Choose this if machine data, ERP and maintenance data add up to large volumes or are also used for models. See the data and AI platform.

As a Microsoft Partner for Fabric, we build reporting solutions for manufacturers

Data Science Lab has been building solutions with data and AI since 2016. For Ammega, we created Power BI dashboards and a Power BI app. For Fokker Services Group, we built a KPI dashboard system that provides insights at every level.

Book an introductory meeting

First, we discuss your lines, your sources and the meeting where the figure matters

Stef Stoelwinder

Stef Stoelwinder

Business Development

Stef is your first point of contact. In our first conversation, we’ll discuss your lines, your sources and the meeting where the figure needs to be right.

E-mail info@datasciencelab.nl

Phone +31 (0)20 3636 724

Which production figure is currently counted in three different ways at your factory?

Describe your production lines and the systems the figures come from. We’ll reply by email or suggest going through it in an initial conversation.

Emailinfo@datasciencelab.nl Phone+31 (0)20 3636 724

Enter a valid email address.

Let us know how we can help you.

Frequently asked questions

By working on the model behind the production figures: bringing ERP, machine control and maintenance data into one semantic model, ensuring refreshes finish on time, agreeing one definition for each metric and setting access by role. If you’re looking for a Power BI consultant or Power BI expert in Eindhoven, this is the work they do.

Our approach, regardless of region or sector, is described on the Power BI consultant page. For teams in Utrecht and Amersfoort, see Power BI specialist Utrecht.

According to Microsoft, you can schedule up to eight refreshes a day on shared capacity, or up to 48 on Premium, Premium Per User or Fabric capacity. With DirectQuery, Power BI does not import the data; it queries the source directly.

You can read how we build a dashboard around the decision it supports on the Power BI dashboards page.

Yes, through an on-premises data gateway. It runs on a server in your own network and connects local sources to the Power BI service without the database needing to be accessible from outside.

We prefer to read from a copy or a historian approved by your OT team, rather than directly from a machine’s control system.

Yes. The data-loading step varies by ERP system, but the model does not. For Isah, which is widely used in manufacturing, we describe it on the Isah Power BI dashboard page: production orders, hours, post-calculation and delivery reliability.

If you use a different system, we’ll look at the available options in our first conversation.

A Power BI model shows what has happened: downtime, faults and output by production line. A predictive model estimates what will happen, such as which machine will need maintenance. We build it using the same data.

You can read how we create these models on the data science consultancy Eindhoven page.

No, and we don’t claim it is. According to the case study, Ammega operates in 40 countries; we mention it here as an example of Power BI work for a manufacturing company.

We’re based in Amsterdam and can come to Eindhoven or the surrounding region for a meeting; we can also meet online. Our advisory work for manufacturers in Brainport is described on the AI consultant Eindhoven page.

Yes, with row-level security: roles in the model with a filter for the site or production line, assigned to users or a security group. Microsoft applies that filter only to people with the Viewer role in the workspace.

Suppliers working on client projects use the same mechanism to keep project data separate.

When your control system screens and ERP reports already answer your questions. Or when departments disagree on what counts as downtime: a new screen will do little to help, and you should start with data governance.

If you mainly need extra people in your own BI team, hiring a BI consultant is a better fit than a project with a defined deliverable.

What comes after a production report in Power BI?

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