Derive Insights from DoorDash Order Database

Q: How do I practice SQL interview questions?

PracHub provides an interactive SQL console where you can write and test queries against real database schemas. Get instant feedback and compare your solution with the expected output.

Q: What difficulty level is this coding question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Technical Screen rounds at DoorDash.

Q: What role is this question designed for?

This question is commonly asked for Data Scientist candidates at DoorDash during technical interviews.

Question

Orders

user_id | order_id | merchant_id | order_value | order_date

1       | 1001     | 501         | 45.00       | 2023-07-01

2       | 1002     | 502         | 12.50       | 2023-07-02

1       | 1003     | 501         | 30.00       | 2023-07-05

3       | 1004     | 503         | 85.00       | 2023-07-05

4       | 1005     | 502         | 15.00       | 2023-07-06

##### Scenario

DoorDash order database; need to derive user and merchant insights during SQL interview.

##### Question

Write a query to calculate the percentage of high-frequency users (e.g., users whose order count exceeds a defined threshold) over total users. 2. Excluding high-frequency users, compute the monthly total order value. 3. Identify the customer with the single highest order value. 4. Given an existing query that returns bottom-quantile-revenue merchants, modify it per a new prompt from the interviewer (e.g., change quantile or add date filter).

##### Hints

Use GROUP BY, COUNT/DISTINCT, window functions or percentile logic; handle date truncation for monthly rollups; join/CTE chain is acceptable.

PracHub · Accepted Answer

This question evaluates SQL and Python data-manipulation skills, specifically aggregation, filtering, window functions, quantile analysis, and the ability to derive user- and merchant-level metrics; it belongs to the Data Manipulation (SQL/Python) domain and emphasizes practical query-writing and data-wrangling competency.

Quick Overview

Quick Overview