Introduction to Advanced Power BI Visuals

Course: Microsoft Power BI Training

Topic: Introduction to Advanced Power BI Visuals

Course Link: Microsoft Power BI Training at JustAcademy

Demo Link: Register for a Course Demo

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1. Introduction to Advanced Power BI Visuals

Microsoft Power BI is a business intelligence and data visualization platform that transforms raw data into meaningful reports and interactive dashboards. Visuals are the building blocks of Power BI reports. They help users understand business performance, identify trends, compare categories, analyze relationships, and communicate insights clearly.

Basic visuals such as bar charts, column charts, pie charts, and tables are useful for everyday reporting. However, complex business questions often require more advanced visualizations. Advanced Power BI visuals include decomposition trees, key influencers, waterfall charts, scatter charts, maps, KPI visuals, gauges, bullet charts, custom visuals, and analytical visuals that support deeper exploration.

Power BI provides built-in visuals and supports additional visuals from Microsoft AppSource and custom-developed visual packages. The best choice depends on the business question, data structure, audience, and level of interactivity required.

1.1 What Are Advanced Power BI Visuals?

Advanced Power BI visuals are visual components that help users analyze complex data, understand relationships, investigate changes, identify contributing factors, and monitor business objectives.

For example, a sales manager may use a waterfall chart to understand how different factors contribute to a profit change, a decomposition tree to investigate declining sales, and a KPI visual to monitor progress toward a sales target.

1.2 Why Are Advanced Visuals Important?

• They help explain complex business problems.
• They reveal patterns, trends, correlations, and outliers.
• They allow users to explore data interactively.
• They improve KPI monitoring and performance analysis.
• They support more effective business decision-making.
• They make reports more informative without relying only on tables.
• They help communicate findings to technical and non-technical audiences.

1.3 Learning Objectives

After completing this topic, learners should be able to:

• Understand advanced visualization concepts in Power BI.
• Differentiate built-in, custom, and analytical visuals.
• Select appropriate visuals for different business questions.
• Create KPI, gauge, waterfall, scatter, and decomposition tree visuals.
• Understand key influencers, maps, and advanced chart types.
• Use slicers, drill-down, cross-filtering, and tooltips.
• Apply conditional formatting and consistent visual design.
• Recognize the limitations and security considerations of custom visuals.
• Develop an interactive report using advanced visualizations.

2. Understanding the Types of Power BI Visuals

Power BI visuals can be organized into several categories according to their purpose and functionality.

3. Built-In Visuals vs. Custom Visuals

3.1 Built-In Visuals

Built-in visuals are supplied with Power BI and are available through the visualization interface. They cover common reporting requirements such as comparisons, trends, data distributions, geographic analysis, and KPI monitoring.

Examples include:

• Bar and column charts.
• Line and area charts.
• Pie and donut charts.
• Scatter charts.
• Tables and matrix visuals.
• Cards and KPI visuals.
• Waterfall charts.
• Decomposition trees and key influencers.
• Map visuals supported by the Power BI environment.

3.2 Custom Visuals

Custom visuals are additional visualization components created by Microsoft, third-party developers, or organizations. They can be imported from Microsoft AppSource or loaded from a trusted visual package when organizational policies permit.

Examples include specialized bullet charts, advanced timeline visualizations, network diagrams, and industry-specific charts.

3.3 Comparison Between Built-In and Custom Visuals

Custom visuals can offer additional functionality, but their availability, features, and licensing can vary. Review the publisher's documentation and organizational policies before using one in a production report.

4. Preparing Data for Advanced Visualizations

Advanced visuals depend on accurate data, suitable data types, correct relationships, and meaningful calculations. Before creating a visual, check that the data model supports the intended analysis.

4.1 Example Sales Dataset

Consider a sales dataset with the following fields:

This dataset can be used to compare revenue, evaluate profit, monitor targets, and analyze performance across categories and regions.

4.2 Create Essential DAX Measures

Assume the dataset is loaded into a table named SalesData. Create the following measures using the Power BI Modeling menu.

Total Sales =
SUM(SalesData[Sales])

Total Cost =
SUM(SalesData[Cost])

Total Profit =
[Total Sales] - [Total Cost]

Sales Target =
SUM(SalesData[Target])

Target Variance =
[Total Sales] - [Sales Target]

Target Achievement % =
DIVIDE(
    [Total Sales],
    [Sales Target],
    0
)

Profit Margin % =
DIVIDE(
    [Total Profit],
    [Total Sales],
    0
)

Order Count =
DISTINCTCOUNT(SalesData[Order ID])

Format currency measures as currency and percentage measures as percentages. The measures will respond to applicable filters and relationships in the report.

4.3 Why Measures Are Important

• They provide reusable business calculations.
• They respond to filter context.
• They help compare actual performance with targets.
• They reduce repeated calculations across visuals.
• They make reports easier to maintain and validate.

5. KPI Visuals

A Key Performance Indicator (KPI) visual measures progress toward an important business objective. It typically combines an indicator value with a target and may display a trend over time.

5.1 Common KPI Examples

• Monthly sales against target.
• Profit margin against a required threshold.
• Customer satisfaction against a goal.
• Orders completed within a deadline.
• Production output against planned production.

5.2 Creating a KPI Visual

1. Open the Power BI report.
2. Select the KPI visual from the visualization pane.
3. Add a suitable date or time field to the trend axis where required.
4. Add a measure such as Total Sales to the indicator field.
5. Add a measure such as Sales Target to the target field.
6. Format the visual title, indicator, trend, and other available properties.
7. Validate the results against the underlying data.

5.3 Interpreting KPI Results

A KPI visual can help answer whether a business is meeting its target, whether performance is improving over time, and where management attention may be needed.

For example, if total sales are 145,000 and the target is 151,000, the report should show that sales are below the target. The precise status indicators and trend behavior depend on the visual configuration.

6. Gauge Charts

A gauge chart displays a value within a defined range. It is often used to show progress toward a target or threshold.

6.1 Business Applications

• Sales target achievement.
• Budget utilization.
• Production capacity.
• Customer satisfaction scores.
• Service-level performance.

6.2 Creating a Gauge

1. Select the Gauge visual.
2. Add a measure such as Total Sales to the Value field.
3. Add Sales Target to the Target value field if appropriate.
4. Set the minimum and maximum values where supported and required.
5. Format the gauge and verify the displayed value and target.

6.3 Gauge Example

If the current sales value is 75,000 and the target is 100,000, the gauge communicates that 75% of the target has been achieved.

Target Achievement % =
DIVIDE(
    [Total Sales],
    [Sales Target],
    0
)

A gauge is most useful when a single value and its position within a meaningful range are important. Avoid using too many gauges on one page because they can consume considerable space.

7. Waterfall Charts

A waterfall chart explains how a starting value changes through a sequence of positive and negative contributions to reach an ending value. It is particularly useful for financial and operational analysis.

7.1 Business Applications

• Explaining changes in profit.
• Analyzing budget differences.
• Understanding revenue growth or decline.
• Tracking changes in operating expenses.
• Explaining year-over-year financial performance.

7.2 Example

A business starts with an operating profit of 100,000. Increased sales contribute 25,000, higher material costs reduce profit by 12,000, and additional operating expenses reduce profit by 8,000.

7.3 Creating a Waterfall Chart

1. Prepare a table containing business factors and their numeric impact.
2. Insert a Waterfall chart.
3. Place the factor field in the Category field well.
4. Place the impact measure in the Y-axis or value field well.
5. Arrange the categories in the required business sequence.
6. Identify the starting and ending totals as total columns when the visual supports that option.
7. Format increases, decreases, totals, labels, and tooltips.

A waterfall chart is useful when the audience needs to understand the contribution of individual factors to an overall change.

8. Decomposition Tree

The decomposition tree is an analytical visual that helps users investigate a metric by breaking it down across different dimensions. It supports interactive exploration and can help identify factors associated with a high or low value.

8.1 Example

A sales manager notices that total sales have declined. The manager can analyze sales by region, then by category, and then by product to investigate where the decline is concentrated.

8.2 Creating a Decomposition Tree

1. Select the Decomposition Tree visual.
2. Add a measure such as Total Sales to the Analyze field.
3. Add dimensions such as Region, Category, and Product to the Explain by field.
4. Expand the tree using the available dimensions.
5. Use supported AI splits when helpful to investigate high or low values.
6. Compare the resulting branches and validate the findings with other visuals.

8.3 Benefits

• Supports multi-dimensional analysis.
• Allows users to choose the order of exploration.
• Helps investigate contributing factors.
• Can reveal useful breakdowns that are difficult to see in a simple chart.

Important: A decomposition tree shows how a metric breaks down across selected dimensions. It does not, by itself, prove that a dimension causes a business result.

9. Key Influencers Visual

The Key Influencers visual helps users explore which factors are associated with a selected outcome. It can analyze a numeric or categorical result and present factors that appear to influence that outcome in the dataset.

9.1 Business Applications

• Exploring factors associated with customer churn.
• Investigating drivers of high sales.
• Understanding factors associated with customer satisfaction.
• Examining variables related to delayed deliveries.
• Identifying patterns associated with employee performance.

9.2 Example

A subscription business wants to investigate customer churn. Its dataset includes churn status, subscription plan, customer tenure, support calls, and monthly charges. The Key Influencers visual can help explore which available factors are associated with customers who churn.

9.3 Creating a Key Influencers Visual

1. Select the Key Influencers visual.
2. Add the outcome field to the Analyze field well.
3. Add potential explanatory fields to the Explain by field well.
4. Allow the visual to analyze the available data.
5. Review the factors and their reported associations.
6. Validate the findings with business knowledge and additional analysis.

The results depend on data quality, the selected fields, and the visual's analytical method. Associations should not be interpreted automatically as causal relationships.

10. Scatter Charts and Bubble Charts

Scatter charts display data points according to two numerical values. They help users understand relationships, identify clusters, and locate unusual observations. Bubble charts add a third numeric dimension through bubble size.

10.1 Example

A company wants to examine whether marketing expenditure is associated with sales revenue across product categories. A scatter chart can display marketing expenditure on the X-axis and sales on the Y-axis. Bubble size may represent the number of orders.

10.2 Creating a Scatter Chart

1. Select the Scatter chart visual.
2. Add a numerical measure to the X-axis.
3. Add another numerical measure to the Y-axis.
4. Add a category or entity field to the Details field where available.
5. Optionally add a numerical measure to Size.
6. Use tooltips to show additional fields.
7. Inspect the points for patterns, clusters, and outliers.

10.3 Interpretation

• Positive relationship: Higher values of one variable tend to occur with higher values of another.
• Negative relationship: Higher values of one variable tend to occur with lower values of another.
• No clear relationship: The points do not show an obvious pattern.
• Clusters: Groups of points appear in similar regions.
• Outliers: Points are unusually distant from the main distribution.

A scatter chart can suggest a relationship but does not establish causation. Consider the underlying data, sample size, and other relevant factors before drawing conclusions.

11. Map Visualizations

Map visuals present information according to geographic location. They help businesses understand regional performance, identify geographic patterns, and compare markets.

11.1 Common Applications

• Sales by city, state, or country.
• Customer distribution.
• Store and warehouse locations.
• Regional service performance.
• Delivery volumes by geographic area.

11.2 Preparing Geographic Data

Ensure that geographic fields contain clear and consistent location information. If possible, use separate columns for City, State, Country, Postal Code, Latitude, and Longitude as appropriate. Set geographic data categories correctly when available.

11.3 Creating a Map Visual

1. Choose a map visual supported by your Power BI environment.
2. Add the relevant location field or latitude and longitude fields.
3. Add a measure such as Total Sales to the visual's size, color, or value field where supported.
4. Format labels, colors, legends, and tooltips.
5. Verify that locations are placed correctly.

Map visual availability and configuration can vary by Power BI version, tenant settings, and organizational policy. Use approved mapping services and review data-sharing requirements before publishing geographic reports.

12. Treemap Visuals

A treemap represents hierarchical categories using nested rectangles. Rectangle size represents a measure, while color can represent another value or category.

12.1 Example

A retailer wants to compare sales across product categories and individual products. A treemap can show the overall contribution of each category, with product-level rectangles nested within each category where the data structure supports it.

12.2 Creating a Treemap

1. Select the Treemap visual.
2. Add the category field to the category or grouping field well.
3. Add a subcategory or product field to the details field if supported.
4. Add a measure such as Total Sales to the Values field.
5. Configure colors, labels, and tooltips.
6. Check that the categories and relative rectangle sizes are easy to interpret.

Treemaps work best for comparing relative contributions across hierarchical categories. They are less suitable when users need to compare many nearly equal values precisely.

13. Small Multiples

Small multiples divide a visualization into several smaller charts using a categorical field. Each chart displays a subset of the data, allowing users to compare patterns across groups.

13.1 Example

A business wants to compare monthly sales trends across regions. Instead of displaying every region as a line in one chart, it can use small multiples to show a separate chart for each region.

13.2 Creating Small Multiples

1. Create a compatible chart, such as a line chart or column chart.
2. Add a time field to the axis.
3. Add a measure such as Total Sales to the values field.
4. Add Region to the Small multiples field well when supported.
5. Adjust layout, titles, scales, and formatting.
6. Compare the patterns across the resulting charts.

13.3 Benefits

• Reduces clutter in charts containing many categories.
• Makes it easier to compare trends across groups.
• Highlights differences between regions, products, or business units.
• Supports a consistent comparison structure.

14. Bullet Charts and Other Specialized Visuals

A bullet chart compares an actual value with a target and may show performance ranges such as poor, satisfactory, and good. It is commonly used in dashboards that monitor business goals.

Bullet charts are often available through custom visuals rather than as a standard built-in visual in every Power BI installation.

14.1 Example

A sales team has a monthly sales target of 100,000. Its actual sales are 82,000. A bullet chart can display the actual result against the target and optionally show performance ranges.

14.2 Typical Uses

• Sales target monitoring.
• Budget versus actual reporting.
• Operational performance dashboards.
• Service-level comparisons.

14.3 Selecting a Specialized Visual

1. Identify the business requirement that the built-in visuals do not fully address.
2. Search Microsoft AppSource or the approved organizational visual store.
3. Review the visual's description, sample report, licensing, publisher, and security information.
4. Import the visual if it is permitted by your organization's policies.
5. Map the fields and measures to the visual's field wells.
6. Test formatting, filtering, export behavior, and performance.

15. Using Conditional Formatting in Advanced Visuals

Conditional formatting changes the appearance of visual elements based on data values, rules, or color scales. It helps highlight important differences and exceptions.

15.1 Common Applications

• Highlighting products with low profitability.
• Showing sales that are above or below target.
• Identifying high-priority regions.
• Displaying status icons in tables and matrices.
• Applying color scales to emphasize higher or lower values.

15.2 Example DAX Measure for Performance Status

Performance Status =
SWITCH(
    TRUE(),
    [Target Achievement %] >= 1, "On Target",
    [Target Achievement %] >= 0.8, "Near Target",
    "Below Target"
)

This measure categorizes performance into three text labels. Where a visual supports rule-based or field-value formatting, the status can be used to configure colors. Check the supported conditional-formatting options for the particular visual.

15.3 Best Practices

• Use consistent meanings for status colors.
• Provide text labels or icons in addition to color.
• Avoid excessive color variations.
• Make sure that color contrast is sufficient.
• Confirm that conditional formatting responds correctly to filters.

16. Interactivity in Advanced Visuals

Interactivity allows report users to explore data instead of simply viewing static charts. Power BI provides several mechanisms for interacting with visualizations.

16.1 Cross-Filtering and Cross-Highlighting

When a user selects a data point in one visual, other visuals on the page can respond by filtering or highlighting related data. This helps users investigate relationships between categories, regions, and performance metrics.

16.2 Drill-Down

Drill-down lets users move through a hierarchy, such as Year to Quarter to Month, or Category to Subcategory to Product, when the visual and fields are configured to support it.

16.3 Tooltips

Tooltips display extra information when users hover over a data point. A report page tooltip can show supporting charts and KPIs without requiring users to leave the current report page.

16.4 Slicers

Slicers provide on-canvas filters that allow users to narrow the data shown in supported report visuals. Common slicers include date, region, product category, and department.

16.5 Bookmarks and Buttons

Buttons and bookmarks can create guided report navigation, switch between saved views, show or hide visual groups, and improve the report's usability.

17. Choosing the Right Advanced Visual

Choosing a visual should begin with the business question rather than the appearance of the chart. A visually attractive chart is not necessarily the best way to communicate a result.

17.1 Factors to Consider

• Data type: Numeric, categorical, date, or geographic.
• Purpose: Comparison, trend, composition, distribution, or explanation.
• Audience: Executives, analysts, managers, or operational users.
• Data volume: Number of categories, rows, and dimensions.
• Readability: Whether the visual can be understood quickly.
• Interactivity: Whether users need filtering, drilling, or exploration.
• Performance: Whether the visual renders efficiently.
• Security and licensing: Whether a custom visual is approved for use.

18. Performance Optimization for Advanced Visuals

Reports containing many complex visuals can become slow. Performance optimization helps ensure that users can interact with reports efficiently.

18.1 Optimization Techniques

• Use an efficient data model with appropriate relationships.
• Remove unnecessary columns and rows during data preparation.
• Prefer measures that answer clear business questions.
• Avoid placing too many visuals on a single page.
• Limit unnecessary high-cardinality fields in visualizations.
• Use aggregations when appropriate for large datasets.
• Review complex DAX expressions and unnecessary repeated calculations.
• Use Power BI Performance Analyzer to identify slow visuals and queries.
• Test custom visuals with realistic data volumes.
• Reduce unnecessary cross-interactions when they do not serve a business purpose.

18.2 Why Visual Performance Matters

Slow visuals can interrupt analysis, reduce user adoption, and make reports difficult to use. Performance should be checked during development rather than only after a report is published.

19. Security and Governance for Custom Visuals

Custom visuals can extend Power BI's capabilities, but they may introduce licensing, support, and data-handling considerations.

19.1 Recommended Practices

• Use visuals from trusted publishers and approved sources.
• Review whether the visual is certified, where certification is relevant and available.
• Understand that certification does not replace an organization's own security review.
• Review the visual's privacy policy, permissions, and external-service requirements.
• Check license restrictions before distributing reports to other users.
• Follow organizational policies for importing and managing custom visuals.
• Test custom visuals in the intended Power BI environment.

Certified visuals meet specified Microsoft testing requirements, including requirements intended to prevent access to external services or resources. However, certification should not be treated as a guarantee that every aspect of a visual is appropriate for every organization's needs.

20. Common Problems and Troubleshooting

21. Practical Exercises

Exercise 1: Create a KPI Dashboard

Objective: Monitor sales performance against a target.

1. Load the sales dataset.
2. Create Total Sales, Sales Target, and Target Achievement % measures.
3. Add a KPI visual and a gauge.
4. Configure the indicator, target, and time trend where appropriate.
5. Add a region slicer.
6. Test the report with different region selections.

Exercise 2: Analyze Profit Changes with a Waterfall Chart

Objective: Explain the factors responsible for a change in profit.

1. Create a table of starting profit, positive contributions, negative contributions, and ending profit.
2. Insert a Waterfall chart.
3. Map the factor and impact fields.
4. Configure starting and ending totals.
5. Format increases and decreases distinctly.
6. Validate the final result against the calculated profit.

Exercise 3: Explore Sales Using a Decomposition Tree

Objective: Investigate which categories and regions contribute to sales performance.

1. Insert a Decomposition Tree visual.
2. Set Total Sales as the Analyze measure.
3. Add Region, Category, and Product as explanatory fields.
4. Explore different branches of the tree.
5. Record the categories with the highest and lowest sales.
6. Verify the findings using a separate chart or table.

Exercise 4: Investigate Relationships with a Scatter Chart

Objective: Examine the relationship between marketing spend and sales.

1. Prepare a dataset containing marketing expenditure and sales by product or region.
2. Create a scatter chart.
3. Place expenditure on the X-axis and sales on the Y-axis.
4. Add a category field to identify individual points.
5. Optionally use bubble size to represent order count.
6. Identify clusters and unusual observations.
7. Explain why a visible relationship does not necessarily establish causation.

Exercise 5: Build an Advanced Power BI Report

Project Requirements:

• Create an executive overview page with KPI cards.
• Add a gauge or KPI visual to monitor target achievement.
• Use a waterfall chart to analyze a financial change.
• Use a decomposition tree to explore a business measure.
• Add a scatter chart to investigate a relationship.
• Include a geographic visual when valid location data is available.
• Add slicers and configure appropriate visual interactions.
• Apply consistent number formats, labels, and conditional formatting.
• Check report performance and validate key results.
• Document the business insights revealed by each visual.

22. Interview Questions and Answers

Q1. What are advanced Power BI visuals?

Answer: Advanced Power BI visuals are visualizations that support deeper analysis, such as KPI monitoring, relationship analysis, geographic exploration, contribution analysis, and investigation of factors associated with business outcomes.

Q2. What is the difference between built-in and custom visuals?

Answer: Built-in visuals are supplied with Power BI. Custom visuals provide additional functionality and can be imported from AppSource, an organizational store, or a trusted visual package.

Q3. What is a KPI visual?

Answer: A KPI visual communicates progress toward a business objective by presenting an indicator, a target, and, where configured, a trend over time.

Q4. What is a gauge chart?

Answer: A gauge chart shows a value within a defined range and is commonly used to display target achievement or capacity utilization.

Q5. What is a waterfall chart?

Answer: A waterfall chart illustrates how positive and negative contributions change a starting value into an ending value. It is useful for financial and operational variance analysis.

Q6. What is a decomposition tree?

Answer: A decomposition tree lets users break down a measure across multiple dimensions to explore how its value varies across categories and identify useful analytical paths.

Q7. What is the Key Influencers visual used for?

Answer: It explores factors associated with a selected outcome, such as customer churn, sales performance, or satisfaction. Its findings should be interpreted as analytical associations rather than automatic proof of causation.

Q8. What is a scatter chart?

Answer: A scatter chart displays two numerical variables as points and helps users explore relationships, clusters, and outliers. Bubble size can encode an additional numeric value.

Q9. When should you use a treemap?

Answer: Use a treemap to display relative contributions across categories or hierarchical groups, especially when the audience needs to see how parts contribute to a whole.

Q10. What are small multiples?

Answer: Small multiples display multiple versions of a compatible chart, each representing a different category. They make it easier to compare trends or patterns across groups.

Q11. Why is conditional formatting useful?

Answer: Conditional formatting highlights important values, differences, and exceptions by changing visual properties based on data values or defined rules.

Q12. What is cross-filtering?

Answer: Cross-filtering allows a selection in one visual to filter related data displayed in other visuals, helping users explore the report interactively.

Q13. How can custom visuals be imported?

Answer: A permitted visual can be added through the Get more visuals or AppSource workflow, or imported from a local package when supported and allowed by organizational policies.

Q14. What should be checked before using a custom visual?

Answer: Review its publisher, source, security characteristics, licensing, compatibility, support arrangements, and organizational approval requirements.

Q15. How can advanced visual performance be improved?

Answer: Optimize the data model and DAX measures, reduce unnecessary visuals and fields, limit excessive detail, review interactions, and use Performance Analyzer to identify bottlenecks.

Q16. How do you choose the right visual for a business question?

Answer: Identify the purpose of the analysis first, such as comparison, trend, relationship, composition, or target tracking. Then choose a visual that communicates the result accurately and clearly to the intended audience.

23. Quick Revision Checklist

• Understand the main categories of Power BI visuals.
• Know the difference between built-in and custom visuals.
• Create appropriate DAX measures before building analytical visuals.
• Use KPI and gauge visuals for target monitoring.
• Use waterfall charts for changes and contributions.
• Use decomposition trees for interactive breakdowns.
• Use Key Influencers to explore factors associated with an outcome.
• Use scatter charts to investigate relationships and outliers.
• Use maps for valid geographic analysis.
• Use treemaps and small multiples for appropriate category comparisons.
• Apply conditional formatting carefully.
• Configure slicers, tooltips, drill-down, and cross-filtering.
• Choose visuals based on business requirements rather than appearance alone.
• Review custom visual security, licensing, and organizational approval.
• Validate results and optimize report performance.

24. Conclusion

Advanced Power BI visuals help users move beyond basic reporting toward deeper business analysis. KPI and gauge visuals support target monitoring, waterfall charts explain changes, decomposition trees break down measures, Key Influencers explore associated factors, and scatter charts reveal relationships and outliers. Maps, treemaps, small multiples, and custom visuals provide additional ways to communicate insights.

Effective visualization requires more than selecting a chart. It involves preparing reliable data, creating accurate DAX measures, selecting an appropriate visual, designing for the intended audience, configuring interactions, and validating the results. By practicing these techniques, learners can build interactive and professional Power BI reports that support informed decision-making.

To continue learning, visit Microsoft Power BI Training at JustAcademy, register through the course demo registration page, or explore the JustAcademy website.

25. Additional Learning Resources

• Microsoft Learn: Overview of Power BI Visualization Types
• Microsoft Learn: Develop Custom Power BI Visuals
• Power BI Visuals: Custom Visuals and Available Sources
• Power BI Custom Visuals: Sample Gallery