13 Power BI Visualizations

Key takeaways

• Visualizations you can create with Power BI include scatter diagrams, gauge charts, line charts, pie charts, decomposition trees, and more.

• Power BI data visualizations are interactive representations of the data you collect, enabling you to create more engaging presentations and help your team make more informed business decisions.

• You can use Power BI Desktop to create visualizations, as well as its mobile application or software version.

Tableau is an alternative to Power BI for those who have more advanced data analytics skills. Explore 13 different Power BI visualizations, learn when to use each, and discover who benefits from data visualizations. If you’re ready to enhance your Power BI skill set, enroll in the Microsoft Power BI Data Analyst Professional Certificate, where, in as little as five months, you can learn about advanced analytics, SQL, business intelligence, database design, and more.

What is Microsoft Power BI?

Microsoft Power BI is a business analytics tool that enables you to create dashboards, reports, and visualizations, allowing you to share insights derived from 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.

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.

13 ways to use Power BI for data visualization

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. Take a look at 13 different types of Power BI charts and visualizations, plus guidance on when to use each.

1. Bar charts

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

2. Line charts

Line charts consist of one or more lines and often illustrate change over time within quantitative variables. However, it’s important not to use an excessive number 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 combine both bar charts and line charts into a single visual. This allows you to represent different data within one chart to efficiently compare them and highlight the differences. Consider using combo charts when creating line and bar charts that share an x-axis or when seeking to highlight a correlation.

4. Donut 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 a donut chart gives you the ability to place a label within the chart. It’s advantageous to use a donut chart if you have a limited number of categories within the chart, with each category representing a part of the donut 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 at that point in time. Use ribbon charts when seeking to identify the largest value or the highest rank.

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 whether the two correlate based on how closely the data points appear to lie on a line or curve. Use scatter diagrams to identify correlations in paired numerical data and to search for the root cause of a problem.

8. Matrix

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

9. Pie charts

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

Read more: What Is a Pie Chart? Data Visualization in Action

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 multiple rows, with each containing data points. Use card charts to highlight key data points, such as sales numbers.

11. Shape maps

Shape maps allow you 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 key performance indicator (KPI) or progress toward a defined goal.

13. Decomposition tree

Decomposition trees are an artificial intelligence visualization that makes 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 data 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.

Is Tableau or Power BI better?

Tableau offers an alternative to Power BI. The superiority of one over the other, however, is determined by your specific work needs. If you’re already using Microsoft tools like Excel or SharePoint, Power BI is a natural fit as it integrates seamlessly within that ecosystem. Third-party support is mostly limited to cloud services.

Tableau offers more flexibility, allowing you to connect to both on-premises and cloud data sources, as well as a wider range of third-party applications. It’s also worth noting that Power BI is aimed at beginners and mid-level users, while Tableau is better suited for advanced users working with complex data and visualizations.

Keep up with trends and job opportunities in Power BI and data analysis

Join Career Chat on LinkedIn to stay current on trends and job opportunities in your career field. Explore these other free resources as well:

• Watch on YouTube: The Power BI Tools You’ll Learn in the Microsoft Power BI Data Analyst Professional Certificate

• Hear from an expert: 6 Questions with a Microsoft Data Analytics Leader

• Learn the terminology: Power BI Terms and Definitions

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