13 Power BI Visualizations

Written by Coursera Staff • Updated on

Learn about Power BI visualizations, including the different types of visualizations you can create and the careers where you can use Power BI visualizations.

[Featured Image] A business analyst sits at a laptop and uses Power BI visualizations to create reports for her colleagues.

Microsoft Power BI is a business analytics tool that gives you the ability to create dashboards, reports, and visualizations so you can share insights found within data. Available as a mobile application, desktop application, and software, Power BI makes it possible for you to utilize and present data from different sources all in one place. Use this guide to learn about 13 different Power BI visuals and when it's appropriate to use each.

Read more: 5 Business Intelligence Tools You Need to Know

What are Power BI visualizations? 

Power BI visualizations are interactive visual representations of data that use business intelligence to help create more engaging presentations. Several options are available so that you can find the right type of visualization for your data.

Read more: Data Visualization: Definition, Benefits, and Examples

13 Power BI visualizations

Power BI allows you to choose from many different types of visualizations. When selecting your visualization type, consider the volume of data you’re working with, the problem you’re solving, your audience, and the type of data you’re working with. Here’s a look at different types of Power BI charts and visualizations, plus when you should use each.

1. Bar charts

Bar charts are a popular choice for observing values across a variety of categories. For example, you could use a bar chart to represent total sales revenue across different months. Best for quantitative data, you can represent data with either horizontal or vertical columns.

2. Line charts

Line charts include one or more lines and often illustrate change over time within quantitative variables. However, it’s important not to use an excessive amount of lines in your chart, as this makes it challenging to see the insights. Use a line chart when the purpose of the visualization is to show data over time.

3. Combo charts

Combo charts take both bar charts and line charts and combine them into one visual. This allows you to represent different data all within one chart to efficiently compare the two and highlight the differences. Consider using combo charts when visualizing line and bar charts that share an x-axis or when seeking to highlight a correlation.

4. Doughnut charts

Donut charts are essentially pie charts with a hole in the middle, where data values are represented by a slice of the doughnut. The hole in the middle of doughnut charts gives you the ability to place a label within the chart. It’s worth using a doughnut chart if you have a limited number of categories within the chart, with each category representing a part of the doughnut ring.

5. Ribbon charts

The ribbons in a ribbon chart allow you to compare the ranking of variables and how they change over time along the x-axis. The larger the thickness of a ribbon, the greater the value during that point of time. Use ribbon charts when seeking to identify the largest value or the highest rank.

Read more: 5 Types of Data Visualization

6. Waterfall charts

Waterfall charts illustrate the impact of intermediate values on the initial value. The scenarios in which you would use a Waterfall chart tend to be similar to those of bar and line charts; however, Waterfall charts are more effective for showing the direct impact of gains and losses over time.

7. Scatter diagrams

Scatter diagrams take a pair of numerical data and seek to identify if the two correlate based on how closely the data points end up appearing on the curve or line. Use scatter diagrams when trying to identify correlations with paired numerical data and when searching for the root cause of a problem.

8. Matrix

Matrix charts are tables that showcase data across multiple dimensions that you can use to analyze and visualize the relationship found between sets of data, as well as the strength of the relationship. Matrix charts can show the relationship between two to four data sets. Use a matrix chart when the goal is to learn more about the relationship data sets share.

9. Pie charts

Pie charts allow you to visualize the significance of variables as part of a whole. Use a pie chart if your data contains between two and five categories and variation exists between the size of the values. Pie charts are effective for demonstrating the relationship between different components, but they aren’t a good choice for directly comparing numbers. 

10. Cards

Card charts are essentially large number tiles that display one or more data points. You can have card charts that contain just a single number or instead have multiple rows, with each containing data points. Use card charts to highlight key data points, such as sales numbers.

11. Shape maps

Shape maps make it possible to compare regions on a map by using various colors to represent data. For example, you could have a map of the United States where each state is colored according to demographic data. Shape maps, however, aren’t used to visualize specific geographical locations within a map.

12. Gauge charts

Gauge charts are great for allowing you to visualize the progress of a certain value toward a goal. The completed portion of the gauge is highlighted by a shaded region, while the target number is a line or needle. Use gauge charts when representing the measurement of a KPI or progress toward a defined goal.

13. Decomposition tree

Decomposition trees are an artificial intelligence visualization that make it possible for you to visualize data throughout numerous dimensions. You can use decomposition trees when performing root cause analysis, with artificial intelligence enabling decomposition trees to find specific criteria in different dimensions.

Who benefits from using Power BI visualizations?

Data visualizations are an important part of many careers. Data analysts, data scientists, data engineers, and business intelligence analysts, for example, all benefit from having data visualization skills. Power BI is one of the most popular data visualization tools and is great for data analysis as well since you can take input data from different sources and choose your own types of visualizations to ultimately produce. You can find organizations across many industries using Power BI, including manufacturing, finance, government, technology, and retail.

How to get started with Power BI visualizations

Microsoft offers Power BI training through Microsoft Learn. You can find learning modules to develop skills in a wide range of areas of Power BI, such as visualizing data and how to design effective reports, with the assistance of step-by-step instructions. 

On Coursera, you can also find courses to learn more about utilizing Power BI for data visualization, such as Data Analysis and Visualization with Power BI from Microsoft. This course is designed to help you learn how to add visualizations to reports and dashboards, as well as how to use visualizations for data analysis.

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