Overview
Data visualization fails when chart type is chosen by aesthetics rather than by the question the data answers. A donut chart that shows 12 categories is not a design choice — it is a communication failure. A line chart that shows a single data point is not minimalist — it is the wrong chart type. The chart type must be determined by the data structure and the question being answered, not by what looks good in the mockup.
The Data Visualization Design System Prompt builds a visualization system from the decision layer — defining which chart type answers which question, what color palette communicates data without relying on color alone, and what the states look like when data is loading, empty, or unavailable.
What you get: - Chart type selection framework: the decision tree that maps data structure and question type to chart type - Visualization color palette: the accessible color sequence that works for the three most common forms of color blindness - Axis and label standards: the formatting rules that make charts readable without annotation - Interaction model: the hover, click, and filter interactions that make dashboards explorable - State design: loading, empty, error, and partial-data states for every chart type - Responsive chart behavior: how charts adapt to mobile without losing meaning
Built for: product designers and design engineers designing data dashboards and analytics interfaces.