This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Visualize and analyze the data (25–30%)
--> Enhance reports for usability and storytelling
--> Edit and Configure Interactions Between Visuals
Note that there are 10 practice questions (with answers and explanations) at the end of each topic. Also, there are 2 practice tests with 60 questions each available on the hub below all the exam topics.
Overview
Power BI reports are designed to be interactive by default. When users select data in one visual, other visuals on the page automatically respond. The ability to edit and configure interactions between visuals allows report authors to control how visuals affect one another, improving usability, clarity, and storytelling.
For the PL-300 exam, this topic tests your understanding of why, when, and how to manage visual interactions, not just that they exist.
What Are Visual Interactions?
Visual interactions define how one visual responds when a user interacts with another visual on the same report page.
By default, Power BI applies interactions such as:
- Cross-filtering
- Cross-highlighting
Editing interactions allows you to:
- Enable or disable these behaviors
- Prevent confusing or misleading visual responses
- Guide users through a clearer analytical experience
Types of Visual Interactions
Understanding the difference between interaction types is critical for the exam.
Cross-Filtering
- Filters data in the target visual
- Only relevant data remains visible
- Common with tables, matrices, and charts
Cross-Highlighting
- Highlights the selected portion
- Keeps the full context visible
- Common with bar and column charts
No Interaction
- The target visual does not respond
- Useful when visuals should remain static
On the exam, identifying which interaction is appropriate is often more important than knowing how to enable it.
Why Configure Visual Interactions?
Configuring interactions improves both usability and storytelling.
Common reasons include:
- Preventing irrelevant or confusing filtering
- Keeping KPI visuals constant
- Ensuring charts respond in a meaningful way
- Avoiding misinterpretation of data relationships
If a scenario mentions confusion, misleading insights, or unwanted filtering, visual interaction configuration is usually the correct solution.
Common Use Cases
Protecting Summary or KPI Visuals
KPIs often represent overall performance and should not change when users select individual categories.
➡ Disable interactions for those visuals.
Improving Comparative Analysis
You may want one chart to highlight values instead of filtering them out.
➡ Use cross-highlighting instead of filtering.
Maintaining Context
Some visuals (such as explanatory text or benchmarks) should remain unchanged.
➡ Set interaction to none.
Visual Interactions vs. Filters and Slicers
The PL-300 exam may test your ability to choose the right feature.
Visual Interactions
- Control how visuals affect each other
- Operate at the visual-to-visual level
- Ideal for interaction tuning
Filters and Slicers
- Control what data is shown
- Operate at visual, page, or report level
- Ideal for intentional user-driven filtering
If the goal is to change interaction behavior, not data selection, visual interactions are the correct answer.
Best Practices for Configuring Interactions
From an exam perspective, best practices help identify correct answers.
- Disable interactions that add no analytical value
- Keep KPI and summary visuals stable
- Use highlighting when context matters
- Test interactions from a user’s perspective
- Avoid over-filtering complex pages
Limitations and Considerations
- Visual interactions apply only within the same page
- Not all visuals behave identically
- Over-customization can reduce discoverability
- Interactions do not replace security or data modeling logic
If a scenario requires security, data isolation, or page navigation, another feature is likely more appropriate.
PL-300 Exam Tip
Exam questions often describe unexpected or undesirable behavior between visuals.
Ask yourself:
“Should this visual respond to selections from another visual?”
- Yes, but with context → Highlight
- Yes, by narrowing data → Filter
- No → Disable interaction
Key Takeaways
- Visual interactions control how visuals respond to each other
- You can enable filtering, highlighting, or no interaction
- Proper configuration improves clarity and storytelling
- PL-300 focuses on design intent, not UI steps
Practice Questions
Go to the Practice Exam Questions for this topic.
The Data Community 
One thought on “Edit and Configure Interactions Between Visuals (PL-300 Exam Prep)”