Cracking Data Analytics SQL Interviews: Expert-Level Strategy Quiz Quiz

1. Schema and Question Comprehension

   When presented with an unfamiliar table schema in a technical interview, which initial step is MOST critical to ensure accurate solutions, even before asking any clarifying questions?

   1. A. Write out the table schema on paper to memorize it for later
   2. B. Review the question and schema thoroughly to confirm you understand both the task and underlying data
   3. C. Immediately write a base SELECT * query to inspect the raw data output
   4. D. Assume column data types based on their names and start coding
   5. E. Skim the question for key verbs (like COUNT or SUM) and jump to coding

2. Clarifying Interviewer Expectations

   Given an ambiguous question involving potentially nullable columns, what is the BEST approach to clarify expectations before writing any SQL?

   1. A. Ignore NULLs unless they cause an error during query execution
   2. B. Ask if NULL values are to be treated as zeros or excluded, and confirm any assumptions about the column's data
   3. C. Replace all NULLs with a default value like 'unknown' in preliminary queries
   4. D. Assume the interviewer prefers rows with NULLs to be dropped
   5. E. Wait for the interviewer to volunteer clarification without asking

3. Structuring Complex Queries

   If you are required to join multiple tables and compute aggregates such as sums per group, which of the following approaches BEST demonstrates an organized strategy before coding?

   1. A. Decide which columns to aggregate and group by, identify join keys, and communicate your planned query structure to the interviewer
   2. B. Write the entire SQL in one go and debug errors afterward
   3. C. Start with the aggregation and add joins later if the output looks incorrect
   4. D. Assume all tables share a primary key and use NATURAL JOINs by default
   5. E. Use subqueries for every join to separate logic completely

4. Iterative Query Development

   During a live technical interview, what is the MOST effective reason for writing SQL queries iteratively (building up the code step-by-step) instead of all at once?

   1. A. To make the query run faster in the SQL engine
   2. B. To check intermediate outputs and catch logic errors early, explaining your steps to the interviewer as you progress
   3. C. To impress the interviewer with your typing speed
   4. D. To avoid using JOIN clauses altogether
   5. E. To obscure your logic and avoid giving away your approach

5. Communicating Code and Assumptions

   Why is it important to explain your code and state your assumptions while coding SQL solutions during a data analytics interview?

   1. A. Because verbalizing assumptions helps the interviewer understand your problem-solving approach and collaboration skills
   2. B. Because the interviewer cannot read SQL code at all
   3. C. To prove that your code will always be error-free
   4. D. To avoid having to answer follow-up questions after the interview
   5. E. Because restating assumptions is only required in written take-home assignments