Feature Quality by Source

A medium SQL mock interview question on DataDriven, with an AI interviewer who asks follow-up questions and a hire or no-hire decision at the end.

Domain

SQL

Difficulty

medium

Seniority

L4

Interview Prompt

We're auditing the ML feature store by source, ignoring features with no source attached. Zero in on the sources that carry more high-null features than a typical source, and for each one report how many features are high-null, how many are clean, and how many of its feature names also run clean under a different source.

Summary

Quality varies by source.

How This Interview Works

1. Read the vague prompt (just like a real interview)
2. Ask clarifying questions to the AI interviewer
3. Write and run your SQL against a real database
4. Answer the interviewer's follow-up questions, then get a hire or no-hire decision