While heatmaps are powerful tools, they come with certain challenges: - Data quality: Inaccurate or incomplete data can lead to misleading visualizations. - Resolution: The granularity of the heatmap depends on the number of data points; insufficient data can result in poor resolution. - Interpretation: Colors can sometimes be misinterpreted, especially if the color scale is not well-chosen or if there is color blindness among users. - Complexity: Highly complex datasets might require multiple heatmaps or additional layers of information to be fully understood.
