Analytical Background Questions
The candidate's analytical skills and experience with data driven problem solving, including statistics, data analysis projects, tools and languages used, and examples of insights that influenced product or business decisions. This covers academic projects, internships, or professional analytics work and the end to end approach from hypothesis to measured result.
EasyTechnical
72 practiced
You notice a sudden 25% drop in pageviews for a marketing landing page today. Provide a step-by-step investigative plan to identify the root cause covering data collection, instrumentation, product/UX changes, marketing campaigns, and external factors.
EasyTechnical
74 practiced
Before putting a new revenue table into production, describe a practical validation checklist you would run: include schema checks, row counts, date ranges, null rates, cardinality changes, and at least two SQL queries you would run for sanity checks.
MediumTechnical
68 practiced
A slow query computes monthly revenue by joining transactions and users with multiple filters and aggregations. Describe practical steps to diagnose and optimize the query (indexes, partitioning, pre-aggregation, rewriting), and show an example of a potential rewritten approach.
HardSystem Design
66 practiced
Design a real-time anomaly detection and alerting architecture for hundreds of business metrics (10k metrics) that requires low-latency alerts while minimizing alert fatigue. Include streaming technologies, detection algorithms, thresholding strategies, and operational playbooks.
MediumTechnical
63 practiced
Describe concrete techniques to improve dashboard performance in BI tools (Tableau/Power BI): caching, extracts, parameterized queries, pre-aggregations, reducing widget count, and limiting datasets. Include tradeoffs between freshness and speed.
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