DAA-C01 Question 257
Single answer4.3 Given a use case, incorporate visualizations for dashboards and reports.A retail analytics team is building an executive dashboard in Snowsight to monitor sales performance. Executives want to review monthly revenue trends across regions, quickly identify which product categories contribute most to total revenue, and compare actual revenue against target for the current quarter. The dashboard must be easy to interpret at a glance and should minimize the risk of misleading visual comparisons. Which combination of visualizations should the data analyst choose?
- A
Use a line chart for monthly revenue trends by region, a treemap for product category contribution to total revenue, and a bullet chart for actual versus target revenue.
- B
Use a pie chart for monthly revenue trends by region, a scatter plot for product category contribution to total revenue, and a table for actual versus target revenue.
- C
Use a heatmap for monthly revenue trends by region, a line chart for product category contribution to total revenue, and a pie chart for actual versus target revenue.
- D
Use a stacked area chart for monthly revenue trends by region, a gauge chart for product category contribution to total revenue, and a scatter plot for actual versus target revenue.
Show answer and explanation
Correct answer: A
Explanation
This question tests the ability to match visualization types to business requirements in dashboards and reports, a key expectation for SnowPro Advanced: Data Analyst candidates working with Snowsight dashboards. In general, best practice is to align the chart to the analytical task: line charts for trends over time, treemaps or similar composition charts for part-to-whole analysis when there are many categories, and bullet charts or comparable KPI visuals for actual-versus-target comparison. Effective dashboards should emphasize readability, rapid interpretation, and reduced cognitive load for decision-makers. Snowflake Snowsight supports building dashboards from worksheet results and selecting visualization types that fit the intended message. Choosing the right chart is essential not just for aesthetics, but for accurate communication of business performance.
- A. Correct.
Correct. A line chart is appropriate for showing trends over time, such as monthly revenue, and supports comparison across regions. A treemap is well suited for showing part-to-whole relationships across product categories, helping executives quickly see which categories contribute the most revenue. A bullet chart is a strong choice for comparing actual performance against a target because it provides a compact, business-focused view of progress toward a benchmark. This combination matches common dashboard design best practices: use trend visuals for time series, composition visuals for contribution analysis, and target-comparison visuals for KPI tracking.
- B. Incorrect.
Incorrect. Pie charts are a poor choice for monthly trends because they do not show change over time effectively. Scatter plots are intended for showing relationships between two quantitative variables, not part-to-whole category contribution. A table can show actual and target values, but it is less effective than a bullet chart for quick executive interpretation in a dashboard context. This option reflects the misconception that any visualization can be used if the data is technically displayable.
- C. Incorrect.
Incorrect. A heatmap can sometimes be used for time-based comparisons, but for executives reviewing monthly revenue trends by region, a line chart is generally clearer for understanding directional change over time. A line chart is not the best choice for product category contribution to total revenue because it implies continuity or sequence rather than composition. A pie chart is also not a strong choice for comparing actual versus target because it does not clearly communicate performance against a benchmark. This option mixes valid chart types with mismatched use cases.
- D. Incorrect.
Incorrect. A stacked area chart can show trends over time, but it can make comparison between multiple regions more difficult, especially for non-baseline series, and may reduce clarity for executive dashboards. A gauge chart is not appropriate for showing contribution of multiple product categories to total revenue; it is designed for single-metric status displays. A scatter plot is also not suitable for direct actual-versus-target comparison unless there are multiple dimensions being compared. This option reflects a common mistake of choosing visually impressive charts over analytically appropriate ones.