In a recent YouTube video, the channel Guy in a Cube walked viewers through a creative technique that combines SVG and DAX inside Power BI. The presenter demonstrated a dynamic star rating visual built directly in a report, explaining each step and showing the result in real time. As a result, the video highlights how familiar report elements can gain visual polish without external image hosting or custom visuals. Consequently, the approach offers a simple path to more expressive dashboards for many report authors.
The core idea is to have DAX produce an SVG string that Power BI can render as an image when the field's data category is set to "Image URL." The video shows how to build those strings so that attributes like color, fill, or shape change with the data context, giving icons a truly dynamic behavior. To make strings compatible with DAX, the host replaces double quotes with single quotes and prefixes the output with the standard data URI header so Power BI treats it as an image. Thus, the result behaves like a native visual element while being driven entirely by data and logic in the model.
First, SVG images remain sharp at any zoom level, which improves readability across displays and printing, and the video demonstrates how crisp icons stay during navigation. Second, creating icons in DAX removes the need to manage external files, so deployment becomes simpler and reports stay self-contained. Third, the technique enables branded or highly tailored indicators that go beyond Power BI's default palette, which the presenter used to build an on-brand star rating system. Therefore, viewers can use the method to deliver clearer signals and a more polished visual language in their reports.
Despite the benefits, the video responsibly notes tradeoffs, particularly around complexity and maintainability. Building long SVG strings inside DAX can be error prone and hard to debug, especially when replacing quotes and managing many conditional branches. In addition, generating large strings at scale may affect report performance, since DAX measures recalculate under different filter contexts and visuals may demand many render operations. Consequently, authors must weigh the visual improvement against added model complexity and potential slowdowns.
The presenter also calls out practical challenges such as consistency across devices and accessibility. Some visuals and visuals extensions may not render identical behavior on mobile or when embedded in other platforms, so testing across form factors becomes essential. Moreover, relying on rendered images hides semantic information from assistive technologies unless you add accessible alternatives, so teams must plan for screen reader support where needed. For these reasons, organizations should evaluate accessibility and cross-platform needs before adopting wide use of this pattern.
The technique offers great flexibility, but the video recommends patterns to keep solutions maintainable, including reusing parametrized measures and centralizing complex logic. When authors place repeated SVG logic in reusable measures, they reduce duplication and make updates easier when icon designs change. However, this centralization increases the importance of clear documentation and disciplined naming to avoid confusion across report authors. As a result, teams can enjoy both control and clarity when they adopt consistent development practices.
The host mentions that newer product updates, including integration with Microsoft Fabric, broaden opportunities for SVG-driven visuals and community tooling. For example, data flows and centralized repositories can store the parameters that feed DAX, which helps in enterprise scenarios where many reports share the same visual language. At the same time, the video warns that system-level governance remains important, because more powerful visuals can escalate maintenance and compliance work if unmanaged. Thus, combining centralized data engineering with thoughtful governance reduces risk while increasing reuse.
To reduce errors, the presenter suggests starting with simple shapes and progressively adding complexity, and to always test within the report context where the visual will run. He also recommends using tools to export or preview SVG code and to keep shapes compact to limit measure size and speed rendering. Furthermore, the video encourages applying conditional formatting with "Field value" to ensure Power BI interprets the string correctly as an image. By following these steps, authors can mitigate many common pitfalls while still achieving polished results.
The video is candid that SVG + DAX is not always the right tool, especially when interactivity or complex user events are required. If you need click handling, animations, or truly interactive DOM-level behavior, a custom visual or embedded web content may be a better fit despite added deployment overhead. Similarly, for very large datasets or highly dynamic visuals driven by many rows, offloading rendering to a custom visual that handles optimization can perform better. Therefore, the choice depends on the tradeoffs you accept between simplicity, performance, and interactivity.
The video notes growing adoption in the Power BI community, which is producing templates, icon libraries, and step-by-step guides to shorten the learning curve. As a result, report authors can often find starter SVG assets and sample measures to adapt rather than building everything from scratch. Still, the presenter advises validating any community asset for licensing and security before using it in production reports. Consequently, community tools speed adoption while requiring standard governance checks.
Overall, the Guy in a Cube video offers a clear, practical introduction to using SVG with DAX to enhance report visuals in Power BI. It balances excitement for creative visuals with realistic advice about complexity, accessibility, and performance. For teams exploring this approach, the video serves as a hands-on starting point, and subsequent work should include testing across devices, documenting measures, and planning governance. In this way, authors can adopt the technique thoughtfully and improve report communication while managing risks.
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