There is no doubt that Power BI is a powerful analytics tool. It allows anyone to get a 360-degree overview of their data in seconds, share insights with colleagues and get notified when things change. What can be confusing are the options for presenting your data. Microsoft offers more than 20 visualisations for use in Power BI dashboards and reports, plus the ability to import custom ones. Today we’re covering 10 of the most popular visualisations available on the Power BI platform.
An area chart is essentially a line chart with the area between the axis and the line filled in to indicate volume.
Area charts are great for showing change over time as well as highlighting the total value. For example, an area chart could be used to compare this year’s sales with those of last year, showing how sales changed over the course of the year as well as how total sales compared to last year.
A combo chart is a combination of a column chart and a line chart with one or two Y axes. Combining these visualisations as one helps you to quickly compare data sets.
For example, you might want to analyse how a change in the number of stores affected overall sales over the course of a year. Combining these two charts with the same X-axis allows you to compare much faster than looking at two individual visualisations. It also helps to clearly demonstrate the correlation between the two factors.
Sometimes you won’t have time to look at charts and reports to find the figure you need. You need to be able to glance down and instantly see a running total of your sales or profit or number of stores. The cards visualisation is perfect for this. You can even use multi-row cards to display something more complex, such as today’s best selling product and its average unit price.
Tree maps are made up of coloured rectangles with their size adjusted according to value. The largest rectangle always appears at the top left and they become smaller as you move down and right. Rectangles can also be nested inside one another to represent hierarchy—in this case, the main rectangles are referred to as “branches” and the nested ones as “leaves”.
For example, you might want a visual overview of your sales by category. You could set your top-level categories such as womenswear and menswear as branches and subcategories like occasionwear and workwear as leaves. This quickly gives you an overview of the most popular product categories in real time and helps you spot patterns in large amounts of data.
Doughnut charts can be used in the same way as Pie charts to show the relationship of parts to a whole. In a doughnut chart, the blank centre leaves space for a label or icon.
There are many datasets that would be well-represented in a Doughnut chart, but Sales by Category is a good example. In this scenario, using a doughnut chart helps you to quickly see the contribution of departments to overall sales rather than in competition with one another.
Funnel charts represent stages of a process and the flow of items following that process. This could be your sales process, with the stages being leads, qualified leads, opportunities, and customers. With this visualisation as part of your dashboard, you’ll easily be able to assess the health of your pipeline and performance and identify any bottlenecks in the process.
Gauge charts help you visualise your progress towards a given goal. This can help you track your KPIs and quickly understand whether or not you are on track to hit your targets by a deadline. Your goal is shown by the grey needle and your progress towards that goal is represented by the shading. Goals you could track include monthly sales, conversion rate, and customer satisfaction.
Similarly, KPI visuals show progress towards a goal. In the example above, the goal is for this year’s sales to exceed sales from last year. The business is currently 20% away from achieving their goal. The red shading in the background depicts the number of units sold each month, giving a more detailed view of how the goal is being completed.
Bubble charts are great for depicting data with numerical values along both the horizontal and vertical axes. The bubbles are placed at the intersection of these values with the size of the bubble representing a third dimension of the data. This can be helpful when looking for patterns in large data sets—the distribution of the bubbles makes it easy to pick out trends and outliers. Bubble charts are often used to visualise financial data and quadrants.
Map charts use Power BI’s integration with Bing Maps to plot your data on a map. This is helpful when analysing both categorical and quantitative data that is related to physical locations. For example, you might want to view this year’s sales by region to get an idea of the cities where your products are most popular. In this case, you might use the size of the bubbles to understand the total revenue of each region and how they compare to one another.
This post gave an overview of 10 of the most common visualisations in Power BI but there are many, many more. To learn more about how Power BI works and explore more visualisations, get started for free.
This post is part of #12DaysOfNAV, our challenge to share a new blog post every day from 1st-12th December.