Power BI Visualization Types: A Comprehensive Guide to Creating Engaging Reports

If you are a Power BI developer, it’s a good idea to save this article for future reference. It will be invaluable whenever you need to create any of these visualizations.

Visualization Types in Power BI

Power BI offers a wide range of visualization types that allow users to create visually appealing and interactive reports and dashboards.

These visualization types in Power BI provide a wide range of options for analyzing and presenting data. By following the step-by-step instructions and understanding their use cases, you can effectively create compelling visualizations that convey insights and drive data-driven decisions.

In this blog post, we will explore popular visualization types in Power BI and provide step-by-step instructions on how to create them. Let’s dive in!

Area Charts: Basic (Layered) and Stacked

Step-by-step: To create an area chart in Power BI, follow these steps:

1. Open Power BI and load your data.
2. Drag and drop the desired field representing the time or X-axis onto the Axis field well.
3. Drag and drop the field(s) representing the values onto the Values field well.
4. Click on the “Visualizations” pane, select the “Area chart” icon, and customize the chart as needed.

Use case: Area charts are useful for showcasing the magnitude of change over time. They are commonly used to display trends, such as profit over time, and emphasize the total value across a trend.

Bar and Column Charts

Step-by-step: To create a bar or column chart in Power BI, follow these steps:

1. Load your data into Power BI.
2. Drag and drop the field representing the categories onto the Axis field well.
3. Drag and drop the field representing the values onto the Values field well.
4. Click on the “Visualizations” pane, select either the “Bar chart” or “Column chart” icon, and customize the chart as desired.

Use case: Bar and column charts are effective for comparing values across different categories. They are commonly used to visualize sales by product, market share by region, or revenue by department.

Cards

Step-by-step: To create a card visualization in Power BI, follow these steps:

1. Import your data into Power BI.
2. Click on the “Visualizations” pane and select the “Card” icon.
3. Drag and drop the desired field onto the “Values” field well in the “Visualizations” pane.
4. Customize the card formatting and style as needed.

Use case: Cards are great for highlighting a single fact or data point. They are commonly used to display total sales, market share, or other important metrics on a dashboard or report.

Combo Charts

Step-by-step: To create a combo chart in Power BI, follow these steps:

1. Load your data into Power BI.
2. Drag and drop the fields representing the categories and values onto the Axis and Values field wells, respectively.
3. Click on the “Visualizations” pane, select the “Combo chart” icon, and customize the chart type and formatting options.
4. If desired, add a secondary Y-axis to compare measures with different value ranges.

Use case: Combo charts are ideal when you want to compare multiple measures with different value ranges, illustrate correlations between measures, or check if one measure meets a target defined by another measure. They conserve canvas space and provide a comprehensive view of the data.

Decomposition Tree

Step-by-step: To create a decomposition tree in Power BI, follow these steps:

1. Import your data into Power BI.
2. Click on the “Visualizations” pane and select the “Decomposition tree” icon.
3. Drag and drop the desired fields into the “Explain by” and “Drill down” sections to define the hierarchy.
4. Customize the tree layout and appearance as needed.
5. Interact with the decomposition tree to explore the data across multiple dimensions.

Use case: The decomposition tree is valuable for visualizing data across multiple dimensions and conducting ad hoc exploration. It allows users to drill down into dimensions in any order and identify factors contributing to a specific result.

Doughnut Charts

Step-by-step: To create a doughnut chart in Power BI, follow these steps:

1. Load your data into Power BI.
2. Click on the “Visualizations” pane and select the “Doughnut chart” icon.
3. Drag and drop the field representing the categories onto the “Legend” field well.
4. Drag and drop the field representing the values onto the “Values” field well.
5. Customize the doughnut chart by adjusting the size, colors, and labels.

Use case: Doughnut charts are suitable for displaying the relationship of parts to a whole. They are often used to visualize market share, distribution of product categories, or composition of a budget.

Funnel Charts

Step-by-step: To create a funnel chart in Power BI, follow these steps:

1. Import your data into Power BI.
2. Click on the “Visualizations” pane and select the “Funnel chart” icon.
3. Drag and drop the field representing the stages onto the “Axis” field well.
4. Drag and drop the field representing the values onto the “Values” field well.
5. Customize the funnel chart appearance, such as colors and labels.

Use case: Funnel charts are effective for visualizing a process with sequential stages, such as a sales pipeline. They provide a clear view of the progression between stages and help identify bottlenecks or areas for improvement.

Gauge Charts

Step-by-step: To create a gauge chart in Power BI, follow these steps:

1. Load your data into Power BI.
2. Click on the “Visualizations” pane and select the “Gauge chart” icon.
3. Drag and drop the field representing the value onto the “Value” field well.
4. Customize the gauge chart by setting the target value, minimum, and maximum.
5. Adjust the appearance, such as colors and labels, to meet your requirements.

Use case: Gauge charts are ideal for visualizing progress toward a goal or representing key performance indicators (KPIs). They provide a visual representation of a single value and are commonly used to monitor sales targets, project completion, or customer satisfaction.

Key Influencers Chart

Step-by-step: To create a key influencers chart in Power BI, follow these steps:

1. Import your data into Power BI.
2. Click on the “Visualizations” pane and select the “Key influencers” icon.
3. Drag and drop the fields representing the outcome and potential influencers onto the appropriate fields.
4. Customize the chart settings, such as the number of influencers to display and filtering options.
5. Explore the chart to identify the major contributors to the selected outcome.

Use case: Key influencers charts help users understand the factors that influence a specific metric or outcome. They are valuable for analyzing customer behavior, identifying reasons behind sales fluctuations, or exploring the drivers of business performance.

KPIs

Step-by-step: To create a KPI visualization in Power BI, follow these steps:

1. Import your data into Power BI.
2. Click on the “Visualizations” pane and select the “KPI” icon.
3. Drag and drop the fields representing the actual value, target value, and any additional indicators onto the appropriate fields.
4. Customize the KPI’s appearance, such as colors and formatting options.

Use case: KPIs provide visual cues to measure progress toward measurable goals. They are commonly used to track performance, display progress, or compare current values to targets.

Line Charts

Step-by-step: To create a line chart in Power BI, follow these steps:

1. Import your data into Power BI.
2. Click on the “Visualizations” pane and select the “Line chart” icon.
3. Drag and drop the field representing the time or X-axis onto the Axis field well.
4. Drag and drop the field(s) representing the values onto the Values field well.
5. Customize the line chart by adjusting the line style, colors, and labels.

Use case: Line charts are effective for showcasing trends and changes over time. They are commonly used to visualize stock prices, temperature variations, or website traffic trends.

Maps

Step-by-step: To create a map visualization in Power BI, follow these steps:

1. Load your data into Power BI, including geographic data (e.g., latitude, longitude, or region).
2. Click on the “Visualizations” pane and select the desired map visualization type (Basic map, ArcGIS map, Azure map, Filled map, or Shape map).
3. Drag and drop the geographic field onto the Location or Legend field well.
4. Drag and drop the field representing the values onto the Values or Color saturation field well.
5. Customize the map appearance, including base maps, colors, and tooltips.

Use case: Maps are useful for associating data with spatial locations. They can be used to display sales by region, analyze customer distribution, or visualize geographical patterns in data.

Matrix

Step-by-step: To create a matrix visualization in Power BI, follow these steps:

1. Import your data into Power BI.
2. Click on the “Visualizations” pane and select the “Matrix” icon.
3. Drag and drop the desired fields onto the Rows and Columns field wells to define the matrix structure.
4. Drag and drop the field(s) representing the values onto the Values field well.
5. Customize the matrix formatting, such as subtotals, sorting, and conditional formatting.

Use case: Matrixes are ideal for displaying data across multiple dimensions. They allow users to compare values by rows and columns, drill down into data, and provide a comprehensive view of the dataset.

Pie Charts

Step-by-step: To create a pie chart in Power BI, follow these steps:

1. Load your data into Power BI.
2. Click on the “Visualizations” pane and select the “Pie chart” icon.
3. Drag and drop the field representing the categories onto the Legend or Details field well.
4. Drag and drop the field representing the values onto the Values field well.
5. Customize the pie chart appearance, including colors, labels, and explode options.

Use case: Pie charts are suitable for showing the relationship of parts to a whole. They are commonly used to visualize market share, budget allocation, or composition of a dataset.

Power Apps Visual

Step-by-step: To add a Power Apps visual to your Power BI report, follow these steps:

1. Create a Power App that includes the desired functionality or visualization.
2. In Power BI Desktop, click on the “Insert” tab and select the “Power Apps” icon.
3. Select the Power App file (.msapp) that you created.
4. Customize the Power Apps visual settings and size to fit your report layout.

Use case: Power Apps visuals allow you to embed interactive Power Apps within your Power BI reports. They can be used to enhance data entry, workflow automation, or custom visualizations within the report.

Q&A Visual

Step-by-step: To enable the Q&A visual in Power BI, follow these steps:

1. Import your data into Power BI.
2. Ensure that the data is properly formatted and includes relevant metadata (e.g., column names, data types).
3. Click on the “Q&A” button in the top menu of Power BI Desktop.
4. Enter natural language queries or questions related to your data.
5. Power BI will generate visualizations based on your queries and display the results.

Use case: The Q&A visual allows users to ask questions about their data using natural language. It is useful for ad hoc data exploration, generating quick insights, or exploring data without writing complex queries.

R Script Visuals

Step-by-step: To create an R Script visual in Power BI, follow these steps:

1. Import your data into Power BI.
2. Click on the “Visualizations” pane and select the “R Script” icon.
3. Write or paste your R code into the R Script editor.
4. Specify the input and output parameters for the R script.
5. Click on the “Run” button to execute the R script and generate the visualization.

Use case: R Script visuals allow advanced data shaping and analytics using the R programming language. They are suitable for performing complex calculations, statistical analysis, and creating custom visualizations beyond the native capabilities of Power BI.

Ribbon Chart

Step-by-step: To create a ribbon chart in Power BI, follow these steps:

1. Import your data into Power BI.
2. Click on the “Visualizations” pane and select the “Ribbon chart” icon.
3. Drag and drop the field representing the categories onto the Axis field well.
4. Drag and drop the field representing the values onto the Values field well.
5. Customize the ribbon chart appearance, including colors, labels, and formatting options.

Use case: Ribbon charts are effective for visualizing ranking or order change over time. They help identify the highest-ranked category in each time period and track rank fluctuations.

Scatter, Bubble, and Dot Plot Charts

Step-by-step: To create a scatter, bubble, or dot plot chart in Power BI, follow these steps:

1. Load your data into Power BI.
2. Click on the “Visualizations” pane and select the desired chart type (Scatter chart, Bubble chart, or Dot plot chart) icon.
3. Drag and drop the fields representing the x-axis, y-axis, and additional parameters (e.g., size, color) onto the appropriate field wells.
4. Customize the chart appearance, including markers, labels, and tooltips.

Use case: Scatter, bubble, and dot plot charts are suitable for visualizing relationships, distributions, or clusters in data. They are commonly used to analyze correlations, identify outliers, or explore patterns in data.

Scatter-High Density

Step-by-step: To create a scatter-high density chart in Power BI, follow these steps:

1. Import your data into Power BI.
2. Click on the “Visualizations” pane and select the “Scatter-high density” icon.
3. Drag and drop the fields representing the x-axis, y-axis, and any additional parameters onto the appropriate field wells.
4. Customize the chart appearance, such as colors and tooltips.

Use case: Scatter-high density charts are used to visualize high-density data. They are particularly useful for large datasets with many overlapping points, providing a responsive and representative view of the data.

Slicers

Step-by-step: To create a slicer in Power BI, follow these steps:

1. Load your data into Power BI.
2. Click on the “Visualizations” pane and select the “Slicer” icon.
3. Drag and drop the field you want to use as a filter onto the “Values” field well of the slicer.
4. Customize the slicer appearance, such as dropdown, list, or range style.
5. Use the slicer to filter data and interactively update other visuals on the report.

Use case: Slicers provide an interactive way to filter data and focus on specific subsets of information. They are commonly used to filter data by categories, time periods, or any other relevant dimensions.

Smart Narrative

Step-by-step: To create a smart narrative in Power BI, follow these steps:

1. Load your data into Power BI.
2. Click on the “Insert” tab and select the “Smart narrative” icon.
3. Define the narrative by selecting the data fields and adding contextual information.
4. Customize the narrative appearance, such as font style, formatting, and language options.

Use case: Smart narratives automatically generate text summaries based on the data and visualizations in your report. They help users understand the data, identify key findings, and provide explanations and context.

Standalone Images

Step-by-step: To add a standalone image to a Power BI report, follow these steps:

1. Click on the “Insert” tab and select the “Image” icon.
2. Browse and select the image file you want to add.
3. Adjust the image size, position, and alignment within the report canvas.
4. Customize the image properties, such as transparency, border, or hyperlink.

Use case: Standalone images allow you to add graphics, logos, icons, or custom images to enhance the visual appeal or branding of your Power BI report.

These visualization types and features in Power BI offer a wide range of options for creating insightful and engaging reports and dashboards. By following the step-by-step instructions, you can leverage these visualizations to analyze data, discover patterns, and communicate findings effectively.

I hope this article has been helpful to you. Thank you for taking the time to read it.

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Who am I? I’m Gabe A, a seasoned data visualization architect and writer with over a decade of experience. My goal is to provide you with easy-to-understand guides and articles on various AI-related topics. With over 150+ articles published across 25+ publications on Medium, I’m a trusted voice in the data science industry.

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