10 Unity Software SQL Interview Questions (Updated 2024)
At Unity Software, SQL is used quite frequently to gather insights about the Unity game engine, and when reporting performance metrics for their mobile ads business. They even let game developers explore data via their SQL Data Explorer tool. That's why Unity often asks SQL interview questions during job interviews for Data Analytics, Data Science, and Data Engineering roles.
To help you practice for the Unity Software SQL interview, here’s 10 Unity Software SQL interview questions – can you solve them?
10 Unity Software SQL Interview Questions
SQL Question 1: Calculate Monthly Average Rating for Each Game in Unity Software
Unity Software, a leading platform for creating and operating real-time 3D content, also has an online store where users can buy games. These games can be reviewed and rated by users. Your task is to write a SQL query that calculates the average rating for each game on a monthly basis. The reveiws are stored in a table 'reviews' with the following columns: review_id (the unique identifier for each review), user_id (the unique identifier for the user who submitted the review), submit_date (the date on which the review was submitted), product_id (the unique identifier for each game) and stars (the rating given by the user on a scale of 1 to 5).
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 1 | 123 | 2022-01-01 | 7000 | 4 |
| 2 | 453 | 2022-01-08 | 8000 | 3 |
| 3 | 789 | 2022-01-15 | 9000 | 5 |
| 4 | 984 | 2022-02-01 | 7000 | 3 |
| 5 | 561 | 2022-02-15 | 8000 | 2 |
| 6 | 321 | 2022-02-28 | 9000 | 4 |
| 7 | 258 | 2022-03-01 | 7000 | 2 |
| 8 | 987 | 2022-03-15 | 8000 | 5 |
| 9 | 654 | 2022-03-31 | 9000 | 4 |
Answer:
This SQL query first truncates the submit_date to month and then groups the data by the new month and product_id. It then calculates the average stars for each group and orders the result by month and product_id which are the identifiers for each row in the result table.
Example Output:
| mth | product_id | avg_stars |
|---|---|---|
| 2022-01-01 | 7000 | 4.00 |
| 2022-01-01 | 8000 | 3.00 |
| 2022-01-01 | 9000 | 5.00 |
| 2022-02-01 | 7000 | 3.00 |
| 2022-02-01 | 8000 | 2.00 |
| 2022-02-01 | 9000 | 4.00 |
| 2022-03-01 | 7000 | 2.00 |
| 2022-03-01 | 8000 | 5.00 |
| 2022-03-01 | 9000 | 4.00 |
To solve a similar window function interview problem which uses RANK() on DataLemur's free interactive SQL code editor, try this Amazon SQL question asked in a BI Engineer interview:
SQL Question 2: Filter Customers Based on Subscription Type and In-Game Purchases
Unity Software is a company that provides a real-time 3D development platform, used to create half of the world's games. Given a table where each row represents a record of a Unity user with their corresponding subscription type and in-game purchase information, write a SQL query to filter down the customer records to find the users who have either a "Pro" subscription or have made in-game purchases of more than $50 in the last month.
Example Input:
| user_id | subscription_type | purchase_amount_last_month |
|---|---|---|
| 1 | "Free" | 25 |
| 2 | "Pro" | 15 |
| 3 | "Free" | 75 |
| 4 | "Pro" | 0 |
| 5 | "Plus" | 30 |
Example Output:
| user_id | subscription_type | purchase_amount_last_month |
|---|---|---|
| 2 | "Pro" | 15 |
| 3 | "Free" | 75 |
| 4 | "Pro" | 0 |
Answer:
This query filters the customers table for records where the subscription type is "Pro" or the amount of in-game purchases from the last month exceeds $50. These criteria are useful for Unity Software to identify users who are potentially high-revenue customers, either through subscription fees or in-game purchases.
SQL Question 3: What does the function do, and when would you use it?
The function can take in multiple paramaters, and returns the first input paramater that is not null. If all arguments are null, the COALESCE function will return null too.
Suppose you have a table of Unity Software salespeople and the number of deals they closed. If a salesperson didn't close any deals, the data from the 3rd-party CRM system exports a NULL value.
| sales_person | closed_deals |
|---|---|
| Jason Wright | NULL |
| Drew Jackson | 3 |
| Chris Ho | NULL |
| Adam Cohen | 2 |
| Samantha Perez | 4 |
To change these NULLs to zeros, you can use the function in the following way:
This would result in the following data:
| sales_person | closed_deals |
|---|---|
| Jason Wright | 0 |
| Drew Jackson | 3 |
| Chris Ho | 0 |
| Adam Cohen | 2 |
| Samantha Perez | 4 |
SQL Question 4: Calculate the click-through-to-purchase rate for Unity Asset Store
Unity Software has an Asset Store where developers can sell their assets to other developers. You are given two tables - and .
Sample Input:
| click_id | user_id | asset_id | click_time |
|---|---|---|---|
| 2435 | 1 | 345 | 09/15/2022 16:30:15 |
| 7651 | 2 | 123 | 09/15/2022 17:25:10 |
| 8792 | 3 | 234 | 09/16/2022 10:45:22 |
| 9825 | 1 | 345 | 09/17/2022 08:30:10 |
| 7295 | 3 | 234 | 09/18/2022 11:10:45 |
Sample Input:
| purchase_id | user_id | asset_id | purchase_time |
|---|---|---|---|
| 12934 | 2 | 123 | 09/15/2022 17:28:35 |
| 53826 | 3 | 234 | 09/18/2022 11:14:00 |
Write a query to calculate the click-through-to-purchase (CTP) rate for each asset. The CTP rate is calculated as the total number of unique users who made a purchase for an asset after clicking on it, divided by the total number of unique users who clicked on the asset, expressed as a percentage.
Answer:
In this query, we join the table and the table on the and columns, with the condition that the purchase time must be later than the click time. Then for each asset, we count the number of unique users who made a purchase () and the number of unique users who clicked () respectively, and finally calculate the ratio between the two, which is our CTP rate.
To solve a related SQL interview question on DataLemur's free interactive coding environment, try this Facebook SQL Interview question:
SQL Question 5: What are the differences between an inner and a full outer join?
A full outer join returns all rows from both tables, including any unmatched rows, whereas an inner join only returns rows that match the join condition between the two tables.
For a tangible example, suppose you had a table of Unity Software orders and Unity Software customers.
Here's a SQL inner join using the orders and customers tables:
This query will return rows from the orders and customers tables that have matching values. Only rows with matching values will be included in the results.
Here is an example of a using the orders and customers tables:
This query will return all rows from both the orders and customers tables, including any rows that do not have matching values. Any rows with null values for either table will be included in the results.
SQL Question 6: Average Runtime of Games by Genre on Unity
Unity Software is a platform for creating and operating interactive, real-time 3D content. As a part of our analysis, we are interested in understanding the average runtime of games in each genre. Therefore, our objective is to find the average runtime of games grouped by their genre.
Consider the following table :
Example Input:
We want to find the average runtime for each game genre.
Example Output:
Answer:
The SQL Query to solve the problem will be:
This query first groups the games based on their genre, and then for each group, it calculates the average runtime using the AVG function. The result shows the average game runtime by genre, giving an insight into the time consumption pattern for different types of games on the Unity platform.
SQL Question 7: What is the difference between cross join and natural join?
Imagine you are organizing a party and have two database tables: one table of people you want to invite and another list of food items you want to serve.
A cross join would be like inviting every person on your list to the party and serving them every food item on the menu, regardless of whether they like the food or not. So, if you had 10 people on your invite list and 5 food items on the menu, you would generate all 50 different combinations of people and food (10 x 5 = 50).
On the other hand, a natural join would be like inviting only the people who like the food items on the menu (based on doing a inner/left/right/outer JOIN on a common key like ).
SQL Question 8: Find Users From a Specific Region
Unity Software wants to run a campaign that targets users from a specific region. You have been asked to fetch all the customer records where the user's address contains the word 'New York' in it.
Consider the following Customer Records stored in the table:
Example Input:
| user_id | fullname | address | |
|---|---|---|---|
| 1001 | John Doe | john.doe@email.com | 123 Main Street, New York |
| 1002 | Jane Doe | jane.doe@email.com | 456 Maple Drive, Seattle |
| 1003 | Bob Smith | bob.smith@email.com | 789 Oak Lane, New York |
| 1004 | Alice Johnson | alice.johnson@email.com | 321 Pine Street, Boston |
The output should be as below:
Example Output:
| user_id | fullname | address | |
|---|---|---|---|
| 1001 | John Doe | john.doe@email.com | 123 Main Street, New York |
| 1003 | Bob Smith | bob.smith@email.com | 789 Oak Lane, New York |
Answer:
The SQL query to solve this would be:
This query selects all records from the table where the field contains the string 'New York', case-insensitive. The keyword is used to match patterns in SQL, and the symbols act as wildcards before and after the specified string, allowing for matches regardless of what precedes or follows the string 'New York' in the field. The function is used to convert the field to lowercase to ensure the pattern matching is case-insensitive.
SQL Question 9: Sales Data Analysis with JOIN
Assume Unity Software is in charge of a customer database and relevant sales data. The sales data records each sale of a product to a customer, while the user data records user details.
Given the table, which details information about each customer, and the table, which details all product sales by Unity Software, write a SQL query to find out:
- The total sales amount made by each customer.
- The average sales amount per transaction made by each customer.
For example, output the customer name, the total sales and the average sales per transaction for each customer.
Example Input:
| customer_id | first_name | last_name |
|---|---|---|
| 1 | John | Doe |
| 2 | Jane | Smith |
| 3 | Alex | Johnson |
Example Input:
| transaction_id | customer_id | sales_amount |
|---|---|---|
| 223 | 1 | 50.00 |
| 346 | 1 | 75.00 |
| 789 | 2 | 30.00 |
| 111 | 2 | 120.00 |
| 965 | 3 | 55.00 |
Example Output:
| Customer Name | Total Sales | Average Sales Per Transaction |
|---|---|---|
| John Doe | 125.00 | 62.50 |
| Jane Smith | 150.00 | 75.00 |
| Alex Johnson | 55.00 | 55.00 |
Answer:
This query joins the and tables on the field, then uses the and aggregate functions to calculate the total and average sales per customer, respectively. The output is grouped by customer name.
Since joins come up frequently during SQL interviews, try this interactive Snapchat SQL Interview question using JOINS:
SQL Question 10: Name the different types of joins in SQL. What does each one do?
Using a join in SQL, you can retrieve data from multiple tables and merge the results into a single table.
In SQL, there are four distinct types of JOINs. To demonstrate each kind, Imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.
-
: An INNER JOIN retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.
-
: A LEFT JOIN retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.
-
: A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.
-
: A FULL OUTER JOIN retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.
How To Prepare for the Unity Software SQL Interview
The best way to prepare for a Unity Software SQL interview is to practice, practice, practice.
In addition to solving the earlier Unity Software SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Netflix, Airbnb, and Amazon.
Each DataLemur SQL question has multiple hints, detailed solutions and most importantly, there is an online SQL coding environment so you can instantly run your SQL query answer and have it executed.
To prep for the Unity Software SQL interview it is also useful to practice interview questions from other tech companies like:
In case your SQL query skills are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this DataLemur SQL Tutorial.
This tutorial covers topics including RANK vs. DENSE RANK and handling NULLs in SQL – both of these come up often during Unity Software interviews.
Unity Software Data Science Interview Tips
What Do Unity Software Data Science Interviews Cover?
Besides SQL interview questions, the other types of questions tested in the Unity Software Data Science Interview are:
- Probability & Statistics Questions
- Coding Questions in Python or R
- Product-Sense Questions
- Machine Learning and Predictive Modeling Questions
- Behavioral Based Interview Questions
How To Prepare for Unity Software Data Science Interviews?
To prepare for Unity Software Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from Microsoft, Amazon & startups
- a crash course on SQL, AB Testing & ML
- over 900+ 5-star reviews on Amazon