Important things to know
Data is everywhere. Businesses collect information about their customers, sales, employees, operations, finances, marketing activities, and almost every other part of their organisation. But having a lot of data does not automatically mean that an organisation understands what is happening.
The real challenge is making sense of that information and communicating it in a way that people can understand. This is where data storytelling becomes important. A Power BI dashboard should not simply be a collection of charts, numbers, colours, and filters. A good dashboard should guide the person looking at it through the information and help them understand what the data is saying. The goal of a dashboard is not to show everything you know. It is to help people understand what matters.
Start With the Story, Not the Dashboard
One of the easiest mistakes to make when creating a Power BI dashboard is to open Power BI and immediately start adding visualisations. You find a chart you like, add another one, create a few cards, change some colours, add filters, and before long you have a dashboard filled with information but there is a problem. You may have created a dashboard without first deciding what story you want the data to tell.
Before building anything, take a step back and understand the question behind the analysis. What does the organisation want to know? What problem are you trying to understand? What decision will the dashboard support?
For example, if you are analysing sales performance, the story may be about declining revenue, changing customer behaviour, or the performance of different products. Once you understand the story, you can decide which information deserves attention.
This simple change in approach can make a significant difference.
Understand Your Audience
A dashboard is created for someone. Before deciding what to display, it is important to understand who that person is and what they need. A senior executive may want a quick overview of performance and the most important changes. A sales manager may need to investigate individual regions, products, or sales representatives. An operations team may require more detailed information to identify problems.
These users may be looking at the same underlying data, but they do not necessarily need the same dashboard experience. That is why a good dashboard should answer the questions that matter to its intended audience rather than simply displaying every available metric.
Give Your Dashboard a Clear Starting Point
When someone opens your Power BI dashboard, they should immediately understand what they are looking at.
The first screen should provide context rather than forcing the user to search through multiple visuals before understanding the purpose of the report. A clear title, relevant date period, key performance indicators, and a few important visuals can provide that initial context.
For example, a sales dashboard might immediately show total revenue, total orders, profit, and the overall trend in performance. The user can then move deeper into the report to understand what is driving those numbers.
Think of the first page as the beginning of the conversation.
It should answer the question: “What is happening?”
The deeper pages can then help answer: “Why is it happening?”
Choose Visuals That Support the Message
Power BI provides many visualisation options, but having access to many charts does not mean you need to use all of them. Every visual should have a purpose. A line chart can help communicate a trend over time. A bar chart can make comparisons between categories easier. Cards can highlight important figures, while tables can provide detailed information when users need to examine specific values.
The important thing is to choose the visual that makes the message easiest to understand. Sometimes, a simple chart communicates an insight much better than a complicated visual with multiple dimensions. Good dashboard design is often about knowing what to leave out.
Don't Overload the Dashboard
One of the biggest challenges when creating dashboards is deciding what not to include.
When you have access to a large dataset, there can be a temptation to put everything on the screen. After all, the information is available, so why not show it? Because more information does not necessarily create more understanding.
Too many charts, numbers, colours, filters, and visual elements can make a dashboard difficult to read. Instead of guiding the user toward an insight, the dashboard forces them to figure everything out themselves.
A good dashboard should create a clear visual hierarchy. The most important information should receive the most attention, while supporting information should remain secondary. If everything looks important, nothing looks important.
Use Colours With Purpose
Colour is another important part of data storytelling. It can help draw attention to an important value, distinguish between categories, or highlight a change that requires action. However, colour should not be used simply because it makes the dashboard look attractive. Using too many colours can make a dashboard confusing. Instead, establish a consistent visual language.
For example, you might use one colour for normal performance and another to highlight an area that requires attention. The exact colours are less important than using them consistently.
When users understand what your colours mean, they can interpret the dashboard more quickly.
Show Trends, Not Just Numbers
A single number can tell you what is happening at one point in time. A trend can tell you how the situation is changing. This is why time-based analysis is often an important part of data storytelling. Imagine that a business generated $500,000 in revenue this month. On its own, that number may sound positive but what if revenue was $700,000 last month? Suddenly, the story is different. This is why dashboards should provide context. Comparisons with previous periods, targets, averages, or other relevant benchmarks can help users understand whether a number represents good, poor, or expected performance. The number itself is only part of the story. The context gives it meaning.
Highlight the Insight, Not Just the Data
A dashboard should make important insights easier to find.
If your analysis reveals that one region is significantly underperforming, the user should not have to examine twenty different charts before discovering it. This is where thoughtful design becomes important. Use visual hierarchy, appropriate comparisons, clear labels, and meaningful titles to guide the user's attention toward important findings. Instead of simply naming a chart “Sales by Region,” you might use a more informative title that communicates the key message, such as “Northern Region Recorded the Largest Decline in Sales.” The second title immediately tells the reader why the visual matters.
Make Interactivity Useful
One of the strengths of Power BI is its ability to allow users to interact with data. Filters, slicers, drill-through pages, tooltips, and other interactive features can help users explore information from different perspectives.
However, interactivity should serve a purpose. Adding a dozen slicers does not automatically make a dashboard better. Too many controls can make the experience confusing and distract from the main story. Instead, ask whether an interactive feature helps the user answer an important question. If it does, include it and if it does not, it may not need to be there.
Build a Narrative Across Your Dashboard
The strongest dashboards often have a logical flow. Instead of presenting unrelated visuals, think about how the user should move through the information. A simple structure might begin with an overall performance summary, followed by trends and comparisons, and then move into detailed analysis that explains the reasons behind the results.
For example, a sales dashboard could begin by showing overall revenue and profit. The next section might show how performance has changed over time. Another section could examine products and regions, helping the user identify what is driving the overall result. This creates a narrative. The dashboard is no longer just showing information. It is taking the user from the big picture to the details.
Remember That Data Storytelling is About Decisions
Ultimately, the purpose of data storytelling is not simply to create beautiful dashboards. It is to help people make better decisions. A dashboard may reveal that sales are declining, customer retention is falling, or operational costs are increasing but the real value comes when those insights lead to action. When designing a Power BI dashboard, think beyond the question of “What does the data show?” Also consider: “What should the person viewing this dashboard understand, and what could they do differently because of that understanding?” That is where analytics begins to create real business value.
Creating a Power BI dashboard is relatively easy once you understand the technology. Creating a dashboard that communicates a meaningful story is a different challenge. The best dashboards are not necessarily the ones with the most visualisations or the most sophisticated designs. They are the ones that make important information clear, provide context, guide the user's attention, and support better decisions. When creating your next dashboard, resist the temptation to start with charts. Start with the question. Understand your audience. Identify the story hidden within the data. Decide which information matters most, choose visuals that communicate that information clearly, and remove anything that creates unnecessary noise. Most importantly, remember that the dashboard is not the story itself. The data contains the story. Your job is to help people see it.
