BigData / Tableau Interview Questions
What is a heat map in Tableau?
A heat map encodes a measure's value using color intensity across a grid of two dimensions, letting you spot patterns, hotspots, and outliers at a glance across a large number of categories without reading individual numbers.
Rows: [Sub-Category] Columns: [Region] Marks: Square, Color = SUM([Sales])
- Two dimensions define the grid's rows and columns (e.g. Sub-Category by Region).
- A measure is dropped onto Color, and a diverging or sequential color palette shows low vs high values.
- Mark type is usually Square or Circle, sized uniformly, so color alone carries the message rather than mark size.
Heat maps scale well to far more categories than a typical bar chart could display legibly — a grid of 20 sub-categories by 10 regions (200 cells) is easy to scan visually for color patterns, while the same data as 200 individual bars would be unreadable.
What visual property does a heat map primarily use to encode a measure's value?
Why do heat maps scale better than bar charts for many categories?
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