OKR and Metric Definition Questions

Covers translating strategic objectives into measurable key results and operational metrics that drive the right behaviors. Topics include writing clear objectives and specific, measurable key results, distinguishing leading and lagging indicators, defining primary metrics versus guardrail metrics, selecting absolute versus relative targets, avoiding perverse incentives, and ensuring metric hygiene through reliable instrumentation and data quality checks. Also addresses setting appropriate targets and time horizons, monitoring cadence, dashboard design and alerting for metric deviations, and using metrics to inform prioritization and continuous improvement without encouraging gaming.

HardTechnical

0 practiced

An A/B test shows a significant uplift in your primary metric but assignment logs reveal sample ratio mismatch. As the Data Analyst, outline the investigation steps to determine bias, quantify its impact, and correct for imbalance if appropriate. Include statistical tests and practical fixes.

MediumTechnical

0 practiced

You wake up to an alert: one key metric dropped 18% overnight. Outline your triage checklist as a Data Analyst to determine whether the issue is instrumentation, ETL/data pipeline, a product regression, or a real business change. Provide proposed quick checks you would run and the expected evidence each check would produce.

HardTechnical

0 practiced

Write a robust SQL query to compute retention where users may have identity merges. Schemas: users(user_id, primary_user_id) where primary_user_id points to canonical id after merges, and events(user_id, event_date). Compute day 7 retention for cohorts by signup_date using primary_user_id to deduplicate merged accounts. Explain handling of nulls and late merges.

MediumTechnical

0 practiced

Write a SQL query to detect potential backfilled or corrected historical event data. Schema: events(event_id, user_id, occurred_at timestamp, processed_at timestamp). Return dates where processed_at is more than 24 hours after occurred_at in significant volume or daily processed count deviates more than 3 sigma from a 30-day baseline. Explain logic and thresholds used.

EasyTechnical

0 practiced

Explain the difference between an Objective, a Key Result, and a KPI. As a Data Analyst working with product and marketing stakeholders, describe how you decide whether a statement should be written as an Objective, a Key Result, or a recurring KPI. Give concrete examples for a marketing acquisition campaign and explain why each example fits its category.

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