DAS-C01 · Question #114
A retail company has 15 stores across 6 cities in the United States. Once a month, the sales team requests a visualization in Amazon QuickSight that provides the ability to easily identify revenue…
The correct answer is C. Heat map. A heat map is the optimal choice because it visualizes data across two categorical dimensions simultaneously - cities (rows) and stores (columns) - using color intensity to represent revenue values. This makes it easy to spot high-revenue and low-revenue patterns across both…
Question
A retail company has 15 stores across 6 cities in the United States. Once a month, the sales team requests a visualization in Amazon QuickSight that provides the ability to easily identify revenue trends across cities and stores. The visualization also helps identify outliers that need to be examined with further analysis. Which visual type in QuickSight meets the sales team's requirements?
Options
- AGeospatial chart
- BLine chart
- CHeat map
- DTree map
How the community answered
(37 responses)- A19% (7)
- B3% (1)
- C70% (26)
- D8% (3)
Explanation
A heat map is the optimal choice because it visualizes data across two categorical dimensions simultaneously - cities (rows) and stores (columns) - using color intensity to represent revenue values. This makes it easy to spot high-revenue and low-revenue patterns across both dimensions at a glance, and outliers stand out as anomalously dark or light cells. A geospatial chart maps data to geographic coordinates and is better for showing location-based density, not categorical store comparisons. A line chart is ideal for time-series trends but does not efficiently compare many categorical groupings side by side. A tree map shows hierarchical proportions (part-to-whole) but uses area rather than color gradients, making subtle outlier detection harder across a two-dimensional category matrix.
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