Describe a past project where you built a dashboard for business or product stakeholders. Explain the business goal, audience, metrics, data-quality work, how the dashboard or analysis helped identify an important problem, how you investigated root cause, what actions you took, and how stakeholder feedback improved the final outcome. ### Constraints & Assumptions - Use STAR structure. - Show both business judgment and implementation depth. - Include metric definitions, validation, data quality, stakeholder feedback, and measurable impact. - Be ready for follow-up questions about tools, tradeoffs, and root-cause analysis. ### Clarifying Questions to Ask - Should the example emphasize business impact, data engineering, stakeholder management, or analytical debugging? - What tools and implementation detail are relevant for the role? - Should the dashboard be internal, executive-facing, operational, or customer-facing? - How much metric detail should be included? ### Part 1 - Define Goal, Audience, And Metrics What dashboard did you build and why? #### What This Part Should Cover - Business context, stakeholder audience, decision supported, core KPIs, drill-down metrics, guardrails, and refresh cadence. ### Part 2 - Ensure Data Accuracy And Usability How did you make sure the dashboard was accurate and useful? #### What This Part Should Cover - Source tables, joins, metric definitions, reconciliation, null handling, freshness checks, filters, segmentation, and visualization design. ### Part 3 - Identify And Solve A Problem How did the dashboard reveal an important issue, and how did you investigate? #### What This Part Should Cover - Anomaly detection, segmentation, upstream data checks, root-cause analysis, partner collaboration, and action taken. ### Part 4 - Handle Feedback And Measure Outcome How did stakeholder feedback change the dashboard, and how did you measure improvement? #### What This Part Should Cover - Feedback intake, prioritization, dashboard iteration, adoption, reduced manual work, faster issue detection, satisfaction, or business impact. ### What a Strong Answer Covers - Connects dashboard work to decisions, not just visuals. - Shows data-quality ownership. - Demonstrates root-cause investigation and action. - Quantifies impact and explains tradeoffs. ### Follow-up Questions - What metric definition was most controversial? - How did you validate the dashboard? - What tool did you choose and why? - What did stakeholders ask you to change? - How did you know the dashboard improved decisions?