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Dashboard and Data Visualization Design Questions

Principles and practices for designing, prototyping, and implementing visual artifacts and interactive dashboards that surface insights and support decision making. Topics include information architecture and layout, chart and visual encoding selection for comparisons trends distributions and relationships, annotation and labeling, effective use of color and white space, and trade offs between overview and detail. The topic covers interactive patterns such as filters drill downs tooltips and bookmarks and decision frameworks for when interactivity adds user value versus complexity. It also encompasses translating analytic questions into metrics grouping related measures, wireframing and prototyping, performance and data latency considerations for large data sets, accessibility and mobile responsiveness, data integrity and maintenance, and how statistical concepts such as statistical significance confidence intervals and effect sizes influence visualization choices.

HardTechnical
0 practiced
Explain how effect sizes and confidence intervals should influence choices in visual encoding when presenting experimental results on a dashboard. Provide specific examples of misleading encodings to avoid.
EasyTechnical
1 practiced
List five visualization types you would consider for showing (a) time trends, (b) category comparisons, (c) distributions, and (d) relationships between two continuous variables. For each type, give a one-sentence rationale.
MediumTechnical
0 practiced
You need to design a dashboard that remains responsive on mobile devices. What layout strategies, visualization adjustments, and interaction changes would you apply specifically for mobile users?
MediumTechnical
0 practiced
Design a dashboard metric definition document for 'Monthly Active Users (MAU)'. Include definition, data sources, SQL pseudocode for calculation, edge cases, expected freshness, and monitoring checks.
MediumTechnical
1 practiced
Describe how you would implement tooltips and drilldowns to reveal detailed data without cluttering the main dashboard. Provide rules for when to use each pattern and an example interaction flow for a sales chart.

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