Business Problem Solving and Recommendations Questions

Frameworks and skills for taking ambiguous business questions through analysis to clear, actionable recommendations. Includes decomposing complex problems into analyzable components, identifying key drivers, selecting focused analyses, synthesizing data backed findings, and articulating specific next steps and implementation considerations. Emphasizes communicating recommendations in business terms, estimating potential impact when possible, acknowledging trade offs and limitations, prioritizing among multiple actions, and tailoring communication to different stakeholders. Covers translating research or analytic results into feasible product or operational changes and defending choices with evidence.

MediumTechnical

0 practiced

Compare approaches to implement row-level security (RLS) and parameterized filtering for sales dashboards in Looker versus Tableau. Discuss maintenance burden, performance implications, auditability, and which approach you would choose for a company with 500 sales users across regions.

MediumTechnical

0 practiced

Propose a practical process and recommended toolset for documenting metric definitions, owners, canonical SQL logic, and change history so the company maintains a single source of truth for business metrics. Include how you would onboard teams, enforce compliance, and publish the catalog for discoverability.

HardTechnical

0 practiced

Discuss the trade-offs between precision and speed in BI analysis when leadership needs a rapid decision. Propose a policy that specifies acceptable levels of precision, confidence, and time-to-deliver for three decision categories (operational, tactical, strategic). Provide concrete examples or thresholds for each category.

HardSystem Design

0 practiced

Design a near-real-time analytics pipeline to support dashboards with under 1-minute latency for 100M events/day. Describe ingestion (streaming vs micro-batch), stream processing framework choices, stateful aggregations, storage/OLAP options for fast reads, caching strategy for dashboards, monitoring, and key cost-performance trade-offs.

EasyTechnical

0 practiced

An executive asks simply: 'Improve retention.' Describe step-by-step how you would convert this ambiguous request into a clear analytics brief. Include clarifying questions you would ask, hypothesis generation, the minimal data required, prioritized analyses, proposed deliverables, and estimated timelines for quick wins vs deeper studies.

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