data anomaly Interview Questions
The most frequently asked data anomaly questions across all roles and companies, ranked by real interview frequency. Updated daily.
Identify multi-day streaks of anomalous email sending activity for a specific user using PostgreSQL window functions.
TessianCalculate trailing 30-day device usage rates and flag rates outside each device's expected range.
AppleUse window functions and conditional aggregation to flag completed transactions that may duplicate one another within five minutes.
RevolutIdentify every user row associated with an email address appearing more than once.
Expleo GroupIdentify every row whose three-column combination occurs more than once, including the original row identifier.
JefferiesAudit transaction records for missing references, invalid values, duplicate user emails, and unusable dates before analysis.
Keystone
PaytmIdentify duplicate rows by key columns and return each duplicated group with its count.
MicrosoftUse date-filtered aggregations to identify Stripe users whose recent transaction frequency is below half their historical baseline.
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