Getting a Power BI dashboard built usually costs between €1,500 and €10,000, and the first working version is ready within one to two weeks. Where you land in that range depends on your data sources and how complex your data model needs to be, but mostly on something most quotes skip entirely: whether anyone has actually decided which decision that dashboard needs to improve.
Skip that question, and the pattern is predictable: a sleek dashboard, a great first impression at the kickoff meeting, and a few weeks later nobody logs in to look anymore. Sound familiar? Not because the dashboard is technically bad, but because nobody defined upfront what was supposed to change because of those numbers.
What exactly is a Power BI dashboard?
A Power BI dashboard is an interactive screen that automatically pulls data from your source systems, think accounting software, CRM, webshop or Excel, and turns it into charts, tables and kpi tiles. Each chart or tile on that screen is called a visualization in Power BI. The difference with an Excel report is fundamental: that is a snapshot made by hand, and by the time it is finished the numbers are outdated. A dashboard refreshes itself.
What is Power BI itself? Microsoft Power BI is software for business intelligence, often shortened to PBI.
How does Power BI work? In three steps: it pulls data from your sources, records in a data model how that data relates, and shows the result in reports and dashboards. The advantages of Power BI sit mainly in that second step, the data model, and in how it plugs into Excel and Microsoft 365, which many businesses already use.
So what is a dashboard, without the brand name? The same idea minus Microsoft. A data dashboard is one screen that keeps itself up to date and shows how things stand, whether the numbers come from accounting software, a webshop or your own database. Other data visualization tools, such as Tableau or Google’s Data Studio, call the same thing an analytics dashboard; the principle is no different.
A dashboard is also not a report. A Power BI report explains what happened and why, often across several pages. A dashboard shows at a glance how things stand right now. You need both, they just answer a different question. If a report has to fit exactly on paper or in a PDF, an invoice overview for example, you build it in Power BI Report Builder, with the same technology as the reports from SQL Server Reporting Services.
Precisely because a dashboard has to work at a glance, it sometimes literally hangs on the wall: on a big screen in the canteen, the warehouse or on the shop floor. What is narrowcasting? Exactly that: showing information to a fixed group in a fixed place, rather than to everyone at once. Technically the dashboard then runs full screen in a browser or in narrowcasting software, under its own account. Never use “Publish to web” for this, because according to Microsoft anyone with the link can then see your report and even the underlying data in your model.
The word you will meet in quotes for the craft around it is dashboarding, or Power BI dashboarding when it is about this platform. What is dashboarding exactly? It is the whole of opening up sources, building a data model, defining kpis and keeping all of that running. The dashboard is the visible end product, dashboarding is the work underneath it. That distinction is not wordplay, because you pay for the second and judge the first. Dashboarding for a business is rarely about the charts, and almost always about the agreements and the model behind them.
What does it cost to get a Power BI dashboard built?
Having a dashboard developed is not a fixed price. It ranges from around €1,500 for a simple dashboard with one data source to €10,000 or more for a custom-built dashboard with multiple systems and permissions per department. Three things determine where you land in that range:
- Number and type of data sources. Connecting one Excel export is an hour’s work. A connection to AFAS, Exact or a CRM system needs a stable, repeatable link.
- Complexity of the data model. A dashboard that only shows monthly revenue is simple. Tying revenue, margin and stock together needs a well thought-out data model: work you never see on screen, but that decides whether the dashboard is correct.
- Number of users and roles. One report for the board is a different job than a dashboard where twelve locations each see their own numbers, with the right access per user.
The comparison that counts is not only what the build costs, but what it costs afterwards: billing every change separately adds up, and the Power BI licensing costs per user land on top of that.
What goes on a KPI dashboard?
A KPI dashboard is not a different product from the dashboard above, it is how you fill it in: the five to eight figures a decision hangs on, each with its target beside it. Without that target you are reading a position rather than a signal.
Search for data visualization examples and you mostly find screens that impress. Here is a dashboard example that also works, for a wholesaler with one location:
- Four tiles at the top. Revenue against budget, gross margin as a percentage, outstanding receivables in days, and the share of orders shipped complete. Each with the target beside it and the gap underneath. One Power BI slicer next to them picks the period, and everything on the page filters along.
- Two charts below that. Revenue per month against last year, and margin per product group. This is the layer that answers the question of how that happened, with a drill down from product group to item.
- One table at the bottom. The ten largest customers with their revenue and margin. A drill through takes you from a customer to a separate page with the individual orders.
A first dashboard does not need to be more than that. The temptation is to put everything measurable on it, and that is exactly how you end up with a screen nobody takes anything from. The Power BI dashboard examples you find online show well what is possible, but they assume someone else’s KPIs. Ready-made Power BI templates have the same drawback: the screen is up quickly, the answer to which figures belong on it is not.
Which KPIs it should be in your case depends on the decision that has to get better, which is the next section. The same layout works for any domain, from a sales dashboard to an ESG dashboard with energy use and CO2 emissions. If you first want to see what such KPIs look like per department, with formula, source and target, that is in our piece on KPI examples.
How does a Power BI implementation run?
In four phases, and each phase hands you something concrete. That is the question to ask a Power BI implementation partner: not how long it takes, but what is on the table at the end of each phase.
- Analysis, a few days. Which decision has to get better, which figures determine it, and where they sit today. This produces a list of kpis with a definition and a source for each.
- Foundation, weeks one and two. Connecting sources and building the data model. This produces the first working version, with your own figures in it.
- Expansion, weeks two to six. Extra sources, role-based permissions, and refinement based on actual use. This produces the dashboard as it will keep running.
- Handover. A Power BI training on your own model, so your team can adjust it and build reports themselves. This produces the state where you no longer need us for every change.
So that first version arrives quickly, and not because speed is the goal. A team can only say something useful about a screen it can touch. Our approach is built on that order.
Which systems can you connect?
Power BI connects to almost any system that can export data: accounting software like Exact and AFAS, CRM systems, webshops and Excel. Standard connectors exist for most Dutch accounting and ERP packages; older or specific systems get connected through a custom link. What such a link looks like from the inside is set out step by step in our article on connecting AFAS to Power BI. If you run Exact Online, the three possible routes are in our article on connecting Exact Online to Power BI.
If your organization runs on SAP, there are separate connectors for SAP HANA and SAP Business Warehouse, so you can combine the figures from your existing SAP business intelligence with other sources. If your data already sits in your own SQL database, you read the tables in directly, and a database dashboard like that is often the quickest to build. With very large volumes, such as big data dashboards with millions of rows a day, Power BI does not load everything but queries the figures at the source at the moment you look. That is called DirectQuery.
If you have several systems that each tell part of the story, stock in one package and sales in another, the data model decides whether Power BI ties those sources together correctly or whether you end up with two dashboards that contradict each other.
Once connected, the dashboard refreshes itself. With a Power BI Pro licence that can happen automatically up to eight times a day, without anyone needing to run an export. The official documentation on refreshing data in Power BI goes deeper into the technical side.
Start with the decision, not the dashboard
The first question most projects ask is about form: which colours, which charts, how many pages. We flip that order and ask about the outcome: which decision needs to turn out differently after this dashboard than it does now?
That answer differs by role, by organization, and sometimes by quarter. Which is exactly why you cannot skip it: a generic dashboard answers a generic question, and almost nobody is asking that one.
That is not just a house rule of ours. In its own adoption guidance for Power BI, Microsoft writes that BI solutions only deliver value once they align with the organization’s goals, and describes the organizations stuck at the level where the conversation is about features and tools rather than goals.
Only once that question is sharp do kpis, definitions and data logic follow, and only after that, Power BI. A dashboard that only summarizes yesterday just confirms what you already knew. If the steering is financial, the kpis that go with it are worked out in our article on a financial dashboard.
Build it yourself, have it built, or build it together?
Power BI Desktop is free, and making dashboards yourself works fine with some time. How you build a dashboard that still holds up six months later is a different question entirely. Where it usually goes wrong is not visualizing the data itself (dragging a chart onto a canvas is something anyone learns within a day, and immediately afterwards everyone also thinks they are done), but the data model underneath: which tables relate how, which calculations still hold under a new filter, and why a report shows one person a different number than another.
That is the difference between building a dashboard yourself and having it built. If you want to learn it yourself, a Power BI course is a good first step, and Microsoft Learn also offers free learning paths at your own pace. Making a Power BI dashboard is something you pick up there quickly, pinning down your own KPIs unambiguously is not.
Many businesses have in fact already done that self-building once, in Excel. Building a dashboard in Excel works as long as one person keeps the numbers up to date and the sources stay small. An Excel dashboard gets stuck at the same point as a sloppy data model: manual work every month to refresh the numbers, and nobody who still knows which formula points where. Excel does not have to go, though, because Power BI simply reads those files as a source.
If you choose to have it built, the person you hire goes by a different title at every agency: a Power BI consultant, a BI developer or a BI specialist. The title says little. Ask instead what will be in your own environment once they are done.
Most clients pick the middle road: we build the foundation and the first version, your team builds alongside and takes it over. By the end your own team adds reports independently, and we stay available for Power BI advice on the questions that genuinely matter.
Where it usually goes wrong at handover
Good Power BI dashboard design is not the same as a dashboard you can trust: a screen can look immaculate and still show the wrong figures. Four things go wrong most often, and all four can be checked at handover:
- The figures differ from the source. What is on screen should match your accounting. Nothing undermines trust faster than a dashboard that is “roughly right”.
- The data model is a pile of loose formulas. Tables that do not relate logically and calculations that each work out slightly differently. This is the work nobody sees, but it decides whether a new kpi can be added later in hours or in weeks.
- Nobody owns it. Who may make changes, and where the dashboard lives: in your own tenant under your own licences, or tucked away in an external party’s environment. Pay extra attention to this with Power BI as a service, where the builder is also the administrator and you pay per month.
- It does not refresh by itself. The moment somebody still has to load an export, it is a report in different clothes.
Will this dashboard become something you glance at monthly, or an instrument you steer with weekly? Want to know what a Power BI dashboard would cost and return for your organization? Get in touch, we would rather work through a concrete example than talk in generalities.
Frequently asked questions
Do I need Power BI knowledge myself to work with a dashboard?
No, you do not need to be a Power BI expert. Viewing and filtering a dashboard takes anyone a few minutes to learn. Only if you want to make changes yourself does some knowledge of the data model help, and we build that up in your team during the project, usually with the controller or business intelligence analyst who works with it daily.
What is the difference between a dashboard and a report in Power BI?
A report explains what happened and why, across several pages and levels of detail. A dashboard shows at a glance how things stand right now. Most clients use both alongside each other.
Which systems can be connected to Power BI?
Almost any system with an export or an API: accounting packages like Exact and AFAS, CRM systems, webshops and Excel files. Standard connectors exist for the most widely used Dutch packages.
How long does a Power BI implementation take?
The first working version is usually ready within one to two weeks. Expanding it with extra sources, role-based permissions and refinement based on actual use runs on for several weeks to months after that. The order is deliberate: a team can only say something useful about a screen it can touch.
How often does a Power BI dashboard refresh?
With a Pro licence, automatically up to eight times a day. If you want it more often, a Premium licence or a streaming connection makes real time possible too.
Can I share a dashboard with people outside my organization?
Yes. With the right licence you can share specific reports with external users, an accountant or a client for example, without giving them access to the rest of your environment. Within your own organization the easiest route is a Power BI app: a fixed bundle of reports that colleagues open in the browser or on their phone.
What if we have not defined any KPIs yet?
Then that is where the project starts, and that is the rule rather than the exception. In the analysis phase we record what each KPI means precisely and which source it comes from. Without that list you build a screen that causes an argument in the first meeting.
What happens to the dashboard if we stop working together?
Nothing. It sits in your own environment, under your own licences, and keeps working. By then your team is trained to manage it themselves.
