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Analytics and Dashboarding Questions

Designing, building, and enabling dashboards and spreadsheet based analysis to turn data into actionable insights for different stakeholder audiences. Candidates should be able to define and prioritize key performance indicators and metrics for roles such as sales, marketing, finance, and executives; apply dashboard design principles that present complex data clearly; and enable self service analytics through reusable data models, standardized metrics, documentation, and user training. Practical spreadsheet skills are included: advanced formulas, pivot tables, lookup functions, data cleaning, filtering, charting, sensitivity and what if analysis, and performance optimization. Candidates should also speak to tools and platforms used such as Excel, Google Sheets, business intelligence platforms, visualization tools, and analytics platforms; consider refresh cadence, data validation and governance, interactivity and drill down patterns, and trade offs between standardized reporting and bespoke custom views.

EasyTechnical
0 practiced
In Excel or Google Sheets, write the formula you would use to map product IDs in column A to product names from a products sheet with columns product_id (col A) and product_name (col B). Provide an example using XLOOKUP and an INDEX/MATCH fallback. The lookup should return 'Unknown Product' when missing and should return the first match when duplicates exist.
EasySystem Design
0 practiced
Design a one-page executive dashboard for a monthly business review that must fit on a single monitor view. Requirements: top 5 KPIs (revenue, gross margin, churn rate, growth YoY, cash runway), trend sparklines for each KPI, region/product filters, and a single table showing top anomalies. Sketch the layout (describe regions), choose appropriate visual types, and justify the visual hierarchy and color choices for executive consumption.
MediumTechnical
0 practiced
Describe the components of an effective data and metric documentation system for a BI team: what fields belong in a data dictionary, how to capture data lineage, metric ownership, examples and SQL snippets, and how to embed definitions in dashboards. Explain how to make the documentation accessible to non-technical stakeholders and keep it up-to-date.
MediumTechnical
0 practiced
Explain how you would implement row-level security (RLS) in Tableau and in Power BI for a global sales organization where each salesperson must only see their territory. Discuss static vs dynamic approaches, performance implications, maintainability, and auditability. Provide an example mapping approach using a user-to-territory table.
HardSystem Design
0 practiced
Design an enterprise-grade dashboarding platform architecture serving 10k concurrent users and datasets of 100M+ rows. Include components: data warehouse, ETL/CDC, semantic layer, caching layer, API, auth & RBAC, catalog, and monitoring. Discuss design choices for latency (interactive vs scheduled), materialization strategies, multi-region deployment, and governance trade-offs between cost and freshness.

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