How do you select an appropriate chart type for data visualization in a UI dashboard?

• A. Aesthetics alone should drive the choice.
• B. Visual balance and decoration are the primary criteria.
• C. Consider data relationships, audience, the story, and accessibility; avoid clutter and choose simple charts.
• D. Use charts only for decorative purposes.

Answer: (C)

Choosing a chart type should be driven by how the data relate to each other and the story you want to tell, not by aesthetics alone. Start by identifying the question the chart should answer: are you showing a trend over time, comparing values across categories, showing how parts combine into a whole, or illustrating distribution? Different answers call for different visuals: line charts for trends, bar charts for comparisons, pie or stacked charts for proportions (used sparingly), and scatter plots for relationships. Keep it simple and legible, because dashboards are read quickly.

Also consider the audience and accessibility. Use clear labels, meaningful legends, and high-contrast colors; avoid color cues that rely on color alone for meaning. Ensure the chart works for users with varying levels of data literacy and on devices with limited space. Avoid clutter by limiting the number of series, removing unnecessary gridlines, and steering clear of 3D effects.

In a UI dashboard, this approach helps the viewer grasp the intended insight at a glance and supports quick decisions rather than decoration. Relying on aesthetics or decoration to drive the choice can obscure meaning, and using charts purely for decoration ignores the data’s purpose and usefulness.