Analyze Oculus App Engagement with SQL Queries

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 Onsite rounds at Meta.

Q: What role is this question designed for?

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

Question

AppUsage

+---------+--------+-----------+--------------+------------+
| user_id | app_id | category  | minutes_spent| usage_date |
+---------+--------+-----------+--------------+------------+
| 101     | 12     | Social    | 45           | 2023-04-15 |
| 102     | 17     | Game      | 30           | 2023-04-16 |
| 101     | 17     | Game      | 20           | 2023-04-17 |
| 103     | 22     | Fitness   | 25           | 2023-04-17 |
| 104     | 12     | Social    | 60           | 2023-04-18 |
+---------+--------+-----------+--------------+------------+

##### Scenario

Analyzing Oculus app engagement over the last 30 days

##### Question

Write SQL to find the most used app (total minutes) in the past 30 days. Write SQL to compute the percentage of time spent in each app category in the past 30 days. How would you test the hypothesis that users of the "Social" category are more regularly engaged than "Game" users?

##### Hints

Use date filters, aggregates, window functions; propose a statistical test.

PracHub · Accepted Answer

This question evaluates proficiency in SQL-based data manipulation and aggregation, time-window filtering, percentage calculations, and the application of basic statistical hypothesis testing for comparing user engagement across categories.

Quick Overview

Quick Overview