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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.

HardTechnical
0 practiced
You must report daily 95th percentile API latency per endpoint from 500M raw log rows. Describe exact SQL approaches (e.g., PERCENTILE_CONT) and approximate approaches (t-digest, quantile sketches, histograms). Explain how to store and merge sketches (per endpoint per day), query patterns to compute approximate quantiles efficiently, and the trade-offs between accuracy, storage, and compute.
EasyTechnical
0 practiced
Explain considerations for dashboard refresh cadence: compare real-time (sub-second to seconds), near-real-time (minutes), hourly, and daily refresh strategies. Discuss trade-offs in data freshness, cost, load on data systems, complexity of pipelines, and recommended cadences for executive finance dashboards versus operational KPI monitoring.
MediumTechnical
0 practiced
Using Excel, describe how to perform what-if analysis for pricing and volume sensitivity. Explain building a two-variable Data Table or Scenario Manager to compute profit and break-even price given fixed and variable costs. Provide the break-even formula and describe how you'd present results to stakeholders for decision-making.
HardTechnical
0 practiced
In Power BI using DAX, implement a measure that ranks products by revenue but ignores all page-level filters except the product_category filter (i.e., ranking should be global within the selected category). Break ties by the most recent sale date. Provide the DAX expression (pseudocode acceptable), explain context modifiers used (ALL, ALLEXCEPT), and discuss performance considerations on large models.
MediumBehavioral
0 practiced
Describe a time you found and fixed a data quality problem that impacted reporting. Explain how you discovered the issue, performed root cause analysis, implemented technical fixes (ETL, validation), communicated with stakeholders, and measured improvements in reporting accuracy and trust.

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