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.

MediumTechnical

0 practiced

Your dashboard's monthly revenue is 8% lower than finance's official report. Provide a systematic debugging checklist to identify and resolve the discrepancy: include source differences, aggregation logic, joins, timezone and currency issues, duplicate rows, late-arriving data, and cut-off timing. Explain the priority order of checks and quick checks to run first.

HardSystem Design

0 practiced

Design an observability plan for production dashboards: what telemetry to collect (query latency, error rates, cache hit ratio, render times), storage strategy for telemetry, visualization for ops, alerting thresholds, runbooks, and postmortem steps for outages or data-quality incidents.

HardSystem Design

0 practiced

You need to publish aggregated customer metrics publicly while preserving privacy. Compare techniques such as k-anonymity, differential privacy, noise addition, and aggregation thresholds. Propose an approach (including parameter choices or privacy budget) that balances utility and privacy and describe how to integrate it into dashboard queries.

MediumTechnical

0 practiced

Write an optimized ANSI SQL query to return the top 3 orders by amount per product category from orders(order_id, user_id, category, amount, created_at). The table contains 200M rows. Your query should be efficient and include recommendations for indexes or partitions to improve performance.

EasyTechnical

0 practiced

Write an ANSI SQL query to compute daily active users (DAU) for the last 30 days using the events table: events(event_id, user_id, event_type, event_timestamp). Return rows (date, dau) for each date in the 30-day window including dates with zero users. Assume event_timestamp is UTC. Also list indexes or partitions you'd recommend for a table with billions of rows.

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