8 Rover SQL Interview Questions (Updated 2024)
Rover employees write SQL queries often for analyzing pet care trends and optimizing caretaker-client matching algorithms, tailoring to specific pet needs and client preferences. Unsurprisingly this is why Rover typically asks SQL questions during interviews for Data Analyst, Data Science, and BI jobs.
So, to help you prep, we've curated 8 Rover SQL interview questions – how many can you solve?
8 Rover SQL Interview Questions
SQL Question 1: Analyze Rover Power Users
Rover is a company that connects pet owners with pet sitters, dog walkers, and boarding services. For this scenario, you're tasked to generate a query that lists Rover's most frequent users. Your mission is to identify the top 5 users who book the most services within the past year.
Please use the following sample data:
Example Input:
| booking_id | user_id | book_date | service_id | service_price |
|---|---|---|---|---|
| 12345 | 654 | 06/08/2020 00:00:00 | 3509 | 15 |
| 12450 | 721 | 06/10/2020 00:00:00 | 3278 | 20 |
| 18672 | 654 | 06/18/2020 00:00:00 | 1902 | 30 |
| 56321 | 537 | 07/26/2020 00:00:00 | 1486 | 10 |
| 78901 | 721 | 07/05/2020 00:00:00 | 3509 | 15 |
Answer:
This query first identifies bookings within the last year. Then, it groups by user_id, counting the total bookings, and sums the price of each booking per user. This is ordered in descending order of booking frequency and the total amount spent on the services. The 'LIMIT 5' constrains the output to the top 5 power users.
To work on another SQL customer analytics question where you can code right in the browser and have your SQL query instantly graded, try this Walmart Labs SQL Interview Question:
SQL Question 2: Well Paid Employees
Given a table of Rover employee salaries, write a SQL query to find employees who earn more money than their direct manager.
Rover Example Input:
| employee_id | name | salary | department_id | manager_id |
|---|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 | |
| 2 | Daniel Rodriguez | 2230 | 1 | 10 |
| 3 | Olivia Smith | 8000 | 1 | 8 |
| 4 | Noah Johnson | 6800 | 2 | 8 |
| 5 | Sophia Martinez | 1750 | 1 | 10 |
| 8 | William Davis | 7000 | 2 | NULL |
| 10 | James Anderson | 4000 | 1 | NULL |
Example Output:
| employee_id | employee_name |
|---|---|
| 3 | Olivia Smith |
This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.
You can solve this interview question interactively on DataLemur:
Answer:
First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.
If the code above is hard to understand, you can find a step-by-step solution with hints here: Well Paid Employees.
SQL Question 3: What is the purpose of a primary key in a database?
The primary key of a table is a column or set of columns that serves as a unique identifier for each row. It ensures that all rows are distinct and does not allow null values.
For example, say you had stored some Facebook ad campaign data that Rover ran:
The CampaignID column is used to uniquely identify each row in the table, and the constraint ensures that there are no duplicate CampaignID values. This helps to maintain the accuracy of the data by preventing duplicate rows. The primary key is also an important part of the table because it enables you to easily identify and reference specific campaigns in your Facebook Ad data. You can use it to join to other tables in the database, such as a table with data on the results of the campaigns.
SQL Question 4: Analyze User Activity
At Rover, keeping track of user activity - especially the booking of services and the type of pets they have - is very important. For this task, the challenge is to write a SQL query that determines:
- On each date, for each type of service booked, calculate the total number of unique users per pet type.
- The pet types include 'Dog', 'Cat', 'Fish', 'Bird', 'Reptile', 'Others'.
- The service types include 'Dog Boarding', 'House Sitting', 'Drop-In Visits', 'Day Care', 'Dog Walking'.
Example Input:
| user_id | activity_date | service_type | pet_type |
|---|---|---|---|
| 123 | 2022-09-21 | Dog Boarding | Dog |
| 356 | 2022-09-21 | House Sitting | Cat |
| 356 | 2022-09-21 | House Sitting | Dog |
| 589 | 2022-09-22 | Dog Walking | Bird |
| 215 | 2022-09-23 | Drop-In Visits | Reptile |
| 123 | 2022-09-24 | Day Care | Dog |
Example Output:
| activity_date | service_type | pet_type | unique_users |
|---|---|---|---|
| 2022-09-21 | Dog Boarding | Dog | 1 |
| 2022-09-21 | House Sitting | Cat | 1 |
| 2022-09-21 | House Sitting | Dog | 1 |
| 2022-09-22 | Dog Walking | Bird | 1 |
| 2022-09-23 | Drop-In Visits | Reptile | 1 |
| 2022-09-24 | Day Care | Dog | 1 |
Answer:
This query calculates the number of unique users for each combination of activity date, service type, and pet type by grouping these columns and applying the aggregate function to the user_id column. The clause helps partition the data into groups for each date, service, and pet type, enabling the count operation to be performed within each group. The results are then ordered by activity date, service type, and pet type for easy readability.
Pro Tip: Window functions are a frequent SQL interview topic, so practice every window function problem on DataLemur
SQL Question 5: What is denormalization, and in what situations might it be a useful?
Database denormalization is when you add redundancy to a database, and break typical normalization rules (specified by 1st, 2nd, 3rd normal forms). There's a few reasons to denormalize a database:
-
Improved performance: Denormalization often reduces the the number of costly join operations that are needed to retrieve data. This is helpful when the database is being used for OLAP (Online Analytical Processing) use cases, as joins can be expensive and slow.
-
Simplification: Denormalization can also be used to simplify the design of a database by reducing the number of tables and relationships that need to be managed. This can make it easier to understand and maintain the database.
-
Ease of use: Denormalization can also make it easier for users to work with a database by providing them with a more intuitive and straightforward data model.
While denormalization can be a useful tool for improving performance and scalability, it's important to keep in mind that it can make update and delete operations more complex. This is because denormalization can create data duplicates, which can make it harder to maintain data integrity. So, to avoid any headaches, it's a good idea to start with a well-normalized database design and then consider denormalization only if it's absolutely necessary for your specific performance and scalability needs. In other words, denormalization can be a bit of a wild card, so it's best to handle it with care!
SQL Question 6: Pet Sitter Booking Query
Rover is a pet services provider that connects pet owners with pet sitters for various services such as dog boarding, dog walking, etc. You are tasked with designing a database to store the booking information between pet owners and pet sitters. A typical booking consists of the pet owner, pet sitter, service type, booking date, number of pets, and total booking cost.
Design a database that will effectively store this information and demonstrate your design with an SQL query that retrieves the total revenue generated by each pet sitter for a specific month.
Example Input:
| owner_id | owner_name |
|---|---|
| 100 | John |
| 200 | Jack |
| 300 | Amy |
Example Input:
| sitter_id | sitter_name |
|---|---|
| 101 | Emma |
| 201 | Liam |
| 301 | Oliver |
Example Input:
| service_id | service_type |
|---|---|
| 900 | Dog Boarding |
| 800 | Dog Walking |
Example Input:
| booking_id | owner_id | sitter_id | service_id | booking_date | num_of_pets | total_cost |
|---|---|---|---|---|---|---|
| 1 | 100 | 101 | 900 | 06/01/2022 | 2 | 100 |
| 2 | 200 | 101 | 800 | 06/02/2022 | 1 | 50 |
| 3 | 100 | 201 | 900 | 06/10/2022 | 3 | 150 |
| 4 | 300 | 101 | 900 | 07/01/2022 | 1 | 50 |
Answer:
This SQL query calculates the total revenue generated by each pet sitter for the month of June 2022. The query uses the EXTRACT function to retrieve the booking month and year from the column and groups the results by . The total revenue for each pet sitter is then calculated using the SUM aggregate function on the column.
SQL Question 7: What's a database view, and when would you use one?
Database views are created to provide customized, read-only versions of your data that you can query just like a regular table. So why even use one if they're just like a regular table?
Views are useful for creating a simplified version of your data for specific users, or for hiding sensitive data from certain users while still allowing them to access other data.
SQL Question 8: Average Duration of Dog Walks
As a data analyst for Rover, a pet services platform, you've been asked to analyze the company's dog walking service. Specifically, your task is to compute the average duration of dog walks per month, in minutes. This information will help the company understand patterns in how long most dog walks are and if any changes in strategy need to be implemented.
To do this, you have been given the following sample data:
Example Input:
| walk_id | dog_id | walker_id | start_time | end_time |
|---|---|---|---|---|
| 1001 | 101 | 201 | 2022-08-01 10:00:00 | 2022-08-01 11:00:00 |
| 1002 | 102 | 202 | 2022-08-02 14:00:00 | 2022-08-02 14:30:00 |
| 1003 | 103 | 203 | 2022-08-03 09:00:00 | 2022-08-03 10:30:00 |
| 1004 | 104 | 204 | 2022-08-04 16:00:00 | 2022-08-04 16:45:00 |
| 1005 | 105 | 205 | 2022-09-05 18:00:00 | 2022-09-05 18:20:00 |
| 1006 | 106 | 206 | 2022-09-06 12:00:00 | 2022-09-06 12:30:00 |
Answer:
Here's a PostgreSQL query that can be used to solve the problem.
This SQL query uses the DATE_TRUNC function to divide the data by month. For each month, it calculates the average of dog walks' duration using the AVG function and the EXTRACT function to calculate the difference between end_time and start_time in minutes. The data is then grouped by the month and sorted in ascending order. The result will be the average dog walk duration (in minutes) for each month.
To practice a very similar question try this interactive Facebook Active User Retention Question which is similar for requiring monthly data analysis or this Amazon Average Review Ratings Question which is similar for needing to calculate averages.
How To Prepare for the Rover SQL Interview
The best way to prepare for a Rover SQL interview is to practice, practice, practice.
In addition to solving the earlier Rover SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Facebook, Google, and VC-backed startups.
Each SQL question has multiple hints, full answers and most importantly, there is an interactive SQL code editor so you can right online code up your SQL query answer and have it checked.
To prep for the Rover SQL interview it is also a great idea to practice SQL questions from other tech companies like:
However, if your SQL skills are weak, don't worry about jumping right into solving questions – go learn SQL with this SQL tutorial for Data Scientists & Analysts.
This tutorial covers SQL concepts such as removing NULLs and Self-Joins – both of which pop up frequently in Rover SQL interviews.
Rover Data Science Interview Tips
What Do Rover Data Science Interviews Cover?
Besides SQL interview questions, the other types of problems tested in the Rover Data Science Interview are:
- Statistics & AB Testing Questions
- Coding Questions in Python or R
- Product-Sense Questions
- Machine Learning and Predictive Modeling Questions
- Behavioral Interview Questions
How To Prepare for Rover Data Science Interviews?
I'm a tad biased, but I believe the optimal way to prep for Rover Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
The book covers 201 data interview questions sourced from FAANG tech companies. It also has a crash course on Python, SQL & ML. And finally it's helped thousands of people land their dream job in data, which is how it's gotten to be an Amazon best-seller with over 1000+ 5-star reviews.