Update: We have since released a more in-depth version of this article in our 'Complete Guide to Power BI Visuals + Custom Visuals' handbook.
Visuals are the most important part of any Power BI report.
In this article, we have chosen the top 10 visuals to best showcase your data and how to use them.
Choosing the right visual enables your users to simply and easily identify and understand the patterns in your data. It will also help you drive better insights effortlessly to unlock new opportunities.
For reference, all the Power BI visuals used in this article were built using the Numerro Toolkit, allowing for an effortless build/design process whilst ensuring we met design best practice standards.
The card visual is the simplest, containing only a single number.
However, the number you choose to represent in this visual should be of importance such as the number of opportunities in the pipeline or the amount of closed business.
The table visual is used for quantitative comparisons, enabling you to see and compare detailed data and exact values.
For example, using a table to show last year's sales and this year's sales side by side, and adding conditional formatting to see whether there were increases or decreases in the sales.
The matrix visual is similar to a table and acts much like that of a pivot table.
The matrix visual can be a powerful tool when cross-highlighting one field of data with another to determine totals and subtotals.
For example, using the matrix to cross-highlight the sales by business segment and product category.
The map visual helps you to answer questions about locations and distances, helping you to understand the distribution of the data.
The map is great to use when you want to interact with the data and quickly compare, such as looking at sales forecasts across the US for computers to drill down into which states are missing their targets.
The line chart is a simple chart that shows changes over time by using data points represented by dots that are connected by a straight line.
Line charts can be a good way to show revenue per month for 2019 with revenue per month with 2020 to see the comparison in the data.
The area chart is similar to the line chart but is used to show the magnitude of change between 2 or more data points, with the area between the axis and the line filled with colors; showing the volume of values.
Area charts are a great way to show the volume of a trend across time such as sales by month.
The donut visual is used to show how different values contribute to the total value, with the size of each piece in the donut representing the proportion of each category.
Donuts are best used when visualizing the split of data, such as calculating the split or orders between product category.
The donut provides both a visual representation of this split, but also supports with additional value and percentage figures.
The slicer is a visual filter, where you choose the data type and the sheet automatically filters the visuals accordingly.
Filters can be great for grabbing quick snapshots of data relating to a specific field. For example, using a year filter alongside a line chart to allow users to quickly move between different time stamps of their data.
The column chart is one of the most popular choices of visual.
The chart is used to compare several items in a specific range of values, with each column representing a category and the height of the column being proportional to the value it represents.
Column charts are great for visualizing data such as revenue by region, as it's easy for the audience to compare column lengths to understand the data.
The multi-row card builds on from the standard card visual and allows users to combine several singular cards into one visual.
Similar to the card, the multi-row card is best used to represent a number of KPI's or high-level metrics.
For example, to highlight the total sales for each product category, demonstrating both the category name and it's corresponding value in a slick and compact format.
Now you can begin to piece together the different visuals to build your own report, reassured in the knowledge that you're using the correct visuals.
Putting this into practice will help your users to better understand the information presented and unlock new insights.
See the below template for how you can apply different visuals to create powerful insights.
We hope you enjoyed this article and that you use it's guidance to support you when using Power BI visuals to build your own well-designed reports that drive clear data insights for you and your organization.
Additionally, if you're looking for an easier and faster way to build great looking reports that reap the benefits of design best practice, you may be interested in leveraging a design toolkit and the benefits it brings.
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