Managing Ambiguity, Assumptions, and Data Gaps Questions
Practice working with incomplete requirements, missing data, and ambiguous scenarios. Develop frameworks for identifying gaps, making reasonable assumptions, sanity-checking your assumptions against business logic, and adjusting assumptions when new information emerges. Learn to communicate assumptions clearly to stakeholders and discuss confidence in your modeling.
MediumTechnical
53 practiced
A stakeholder complains a dashboard metric changed overnight and they can't tell why. Describe a process for metric versioning and an audit trail: how to store metric definitions over time, expose change logs to stakeholders, and provide a way to compute and display a side-by-side comparison of old vs new metric definitions for a sample period.
HardTechnical
42 practiced
An upstream vendor announces deprecation of a field used in a critical KPI in three months. Propose a migration plan that includes impact analysis (which dashboards and owners are affected), mapping to alternative fields or fallbacks, interim reporting strategies, stakeholder notifications and timelines, metrics to track during transition, and a rollback plan if the replacement proves insufficient.
MediumTechnical
42 practiced
Your product telemetry experienced a 12-hour outage that caused missing transactions. The business asks for estimated daily revenue numbers for the impacted day to support planning. Describe a backfill estimation approach: list data sources to combine, estimation techniques (for example: historic same-day patterns, traffic-based scaling), how you'd estimate confidence ranges, and how you'd label the reported numbers in dashboards.
MediumTechnical
28 practiced
Given events(user_id int, event_type varchar, occurred_at timestamp), write a SQL (ANSI/Postgres) query that identifies users who were active historically (had events between 90 and 31 days ago) but have zero events in the past 30 days (possible data gap or churn). Explain how your query distinguishes churn from missing data and state any assumptions about timezones or event lateness.
MediumTechnical
38 practiced
You have incomplete sample sizes in several A/B experiments due to tracking gaps. How would you evaluate whether experiment results are still reliable? Describe steps to check balance between variants, statistical adjustments you might consider (for example: weighting, censoring), how to document assumptions, and how to recommend next steps to product stakeholders.
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