Building Dashboards with Power BI & Grafana

The dashboard that nobody reads

Walk into almost any company and you will find a dashboard that nobody reads. It was built with care. It has dozens of charts, every filter you could want, a gradient header, and a number for everything. And it sits ignored, because it answers no question anyone is actually asking.

The failure is rarely technical. It is a failure of purpose. A dashboard is not a place to put data; it is a tool for a specific person to make a specific decision, fast. Once you internalize that, the rest of the craft - including the choice between Power BI and Grafana - falls into place.

Two tools, two worlds

Power BI and Grafana are both called “dashboard tools,” which obscures how different they are. They were built for different people answering different questions, and that difference should drive almost everything about how you use them.

Power BI is for business intelligence. Its natural question is “How is the business doing?” Its audience is analysts and managers. Its data is relational and modeled - sales, customers, products, regions - imported and refreshed on a schedule. You shape it into a star schema, write a few DAX measures to turn raw sums into comparisons against last year and against target, and build interactive visuals that a manager can slice by region and quarter. The magic is the interactivity: click one bar and the whole report cross-filters.

Grafana is for observability. Its natural question is “Is the system healthy right now?” Its audience is engineers and on-call responders. Its data is live time-series metrics streaming from infrastructure and applications. Grafana does not even store the data; it queries external sources like Prometheus on every load, renders panels, and - crucially - fires alerts when something crosses a threshold. It is the always-on window into a running system, the thing on the wall display at 3 a.m. when the pager goes off.

Neither is better. They are not competitors. Asking “Power BI or Grafana?” without knowing the question is like asking “hammer or screwdriver?” without knowing the fastener.

The question picks the tool

So the first move is always to identify the question, the audience, and the cadence.

If stakeholders need to understand business performance over time - comparing actual revenue to target, drilling into which customer segment is slipping, reviewing a quarter - you are in Power BI’s world. The data is modeled, the refresh is periodic, the interactivity is rich, and you can enforce row-level security so each regional manager sees only their numbers.

If engineers need to know that p95 latency just spiked or that a disk is filling up - in real time, with an alert that pages someone - you are in Grafana’s world. The data is live, the time window is seconds to hours, and alerting is a first-class citizen rather than an afterthought.

Many organizations run both, and that is exactly right. The finance team lives in Power BI; the platform team lives in Grafana. Each tool is excellent at its job and awkward at the other’s. Trying to monitor real-time infrastructure in Power BI, or to model quarterly financials in Grafana, is the kind of mismatch that produces those unread dashboards.

What carries across both

Here is the part that surprises people: once you have picked the right tool, the design principles are identical. They come from the same data-visualization tradition - Stephen Few, Edward Tufte, Cole Nussbaumer Knaflic - and they apply whether you are writing DAX or PromQL.

Put the single most important number top-left and make it the largest thing on the screen. Keep the visual count low - roughly five to nine - and split the rest into other pages. Choose the chart type from the question, not from what looks impressive: bars for comparison, lines for time, a big number for a single tracked metric, and a pie almost never. Use one or two accent colors against a field of gray, keep those colors consistent across every chart, and never rely on red and green alone, because some of your readers cannot distinguish them. Strip the chartjunk: no 3D, no drop shadows, no dual axes, no decorative gridlines. And apply the five-second test - if your intended reader cannot answer their core question in about five seconds, you have asked them to do work the design should have done.

These rules are not aesthetic preferences. They are concessions to the reader’s limited attention, and they are exactly as true in a Grafana panel as in a Power BI card.

Treat the dashboard as a product

The last shift in thinking is the most important. A dashboard is not a one-time artifact you build and forget. It is a product with users, and it needs to be operated. Right-size the refresh or query interval to the decision - daily sales do not need second-by-second updates, and a five-second auto-refresh on an expensive Grafana query will punish your data source. Set permissions deliberately. Keep queries lean and models clean, because slow dashboards get abandoned. Above all, agree on what each metric means - what exactly counts as an “active user” or as “uptime” - and document it, because inconsistent definitions destroy trust faster than any bug.

Get the purpose right, pick the tool the question demands, apply the same disciplined design to both, and operate it like a product. Do that, and you will build the rarest thing in any company: a dashboard people actually use.