Relative Distribution Heatmap

A Relative Distribution Heatmap is a data visualization that displays the relative intensity, concentration, or magnitude of values across two variables using color gradients. It is typically presented as a grid (matrix) or spatial surface, where each cell represents the aggregated value of a specific variable combination (e.g., region × revenue, time × filings, sector × risk score).

Color intensity encodes magnitude: warmer or darker tones indicate higher relative concentration, while cooler or lighter tones indicate lower concentration. This allows users to quickly identify structural patterns, clusters, concentration effects, and outliers within large or complex datasets.

Unlike charts that emphasize precise numeric values, a relative distribution heatmap focuses on comparative relationships and distributional structure. It is particularly useful for detecting concentration risks, regional dominance, market fragmentation, temporal shifts, or disproportional exposure within a dataset.

In North Data’s Company Intelligence, relative distribution heatmaps are used to visualize concentration patterns and comparative distributions across key business indicators, supporting structured analysis and data-driven decision-making.