What would likely require a heat map for effective analysis?

A heat map is particularly effective for visualizing data distributions across different regions or categories, which is why representing demographic data distributions makes the most sense in this context. Heat maps can show varying intensity levels or concentrations of data points, allowing analysts to easily identify trends or patterns. For instance, demographic distributions may include information such as population density, income levels, or age groups across different geographic areas, and a heat map provides a clear visual representation that highlights these variations effectively.

In contrast, while analyzing individual survey responses might involve some form of data visualization, the granularity of the data would not benefit from the aggregated view that a heat map offers. Similarly, assessing project timelines typically requires Gantt charts or similar tools that can better represent tasks over a period rather than spatial distribution. Lastly, plotting geographical routes generally involves mapping techniques that focus on pathfinding and spatial relationships rather than density or distribution, which is outside the optimal use for heat maps.