11 AutoNation SQL Interview Questions (Updated 2024)

At AutoNation, SQL does the heavy lifting for analyzing sales data to optimize pricing strategies, and managing dealership inventory. Because of this, AutoNation asks SQL problems during interviews for Data Science and Data Engineering positions.

Thus, to help you prep, here’s 11 AutoNation SQL interview questions – can you answer each one?

11 AutoNation SQL Interview Questions

SQL Question 1: Determine the VIP Users at AutoNation

AutoNation is a giant automotive retailer, and its power users can be considered the customers who purchase vehicles most frequently. To leverage these key customers, you need to identify who they are. Therefore, just as a SQL interview question, write a query that identifies the top five customers who have made the most purchases over the past year.

Consider the following sample tables and for your question.

Example Input:

Example Input:

Answer:

In PostgreSQL, you can achieve this by grouping by the customer_id and then counting the number of sales for each customer. You can then order by the count in descending order and limit to the top 5. The SQL statement is as follows:

This query should return the ID, first name, and last name of the top 5 customers who made the most purchases in the year 2021 along with the count of their purchases.

Please note to adjust the dates in the clause based on the actual situation or requirements.

To practice a similar customer analytics SQL question where you can solve it right in the browser and have your SQL query automatically checked, try this Walmart SQL Interview Question:

SQL Question 2: Employees Earning More Than Their Boss

Given a table of AutoNation employee salary information, write a SQL query to find all employees who earn more money than their direct manager.

AutoNation Example Input:

Example Output:

This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.

You can solve this question directly within the browser 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 solution above is hard to understand, you can find a step-by-step solution here: Well Paid Employees.

Read about Auto Nation's drive pink initiative and see how it empowers both their customers and emplyees.

SQL Question 3: What is database normalization?

Normalization involves breaking up your tables into smaller, more specialized ones and using primary and foreign keys to define relationships between them. Not only does this make your database more flexible and scalable, it also makes it easier to maintain. Plus, normalization helps to keep your data accurate by reducing the chance of inconsistencies and errors.

The only downside is now is that your queries will involve more joins, which are slow AF and often a DB performance botteleneck.

SQL Question 4: Calculate the Rolling Three Month Sales for Each Car Model

As a part of the data analyst team for AutoNation, you've been tasked with evaluating the sales performance of different car models that the company sells. Your objective is to write a SQL query that computes the rolling three-month sales for each car model from the table. For each model and month, calculate the count of sales in the past three months (including the current month).

Example Input:

Answer:

This query works by creating windows of sales records for each car model sorted by month (obtained using ). The COUNT function is then used over each window to calculate the number of sales in a rolling three-month period. Note that because the window is defined with , the count includes sales from the current month and the two preceding months. The output is then sorted by model_id and month for clearer presentation.

To practice a similar window function interview problem which uses RANK() on DataLemur's free interactive SQL code editor, try this Amazon BI Engineer interview question:

SQL Question 5: What is the purpose of the SQL constraint ?

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A UNIQUE constraint ensures that all values in a column are different. It is often used in conjunction with other constraints, such as NOT NULL, to ensure that the data meets certain conditions.

For example, if you had AutoNation sales leads data stored in a database, here's some constraints you'd use:

In this example, the UNIQUE constraint is applied to the "email" and "phone" fields to ensure that each AutoNation lead has a unique email address and phone number. This helps to ensure the integrity of the data in the database and prevents errors that could occur if two leads had the same email address or phone number.

SQL Question 6: Filtering Customers Records for AutoNation

AutoNation management wants to filter down the customers records that satisfy certain conditions. The goal is to find customers who have done purchases during last year, have spent more than $5000 overall, and have bought more than four different vehicle models.

For this scenario, consider the following two tables:

Example Input:

Example Input:

Answer:

This query first selects entries with a membership date earlier than 2020 and which purchases are made in 2020. It then aggregates these entries by customer_id and filters out those where the total price is more than 5000 and where more than four different vehicle models were purchased. The final output will be the customer_id along with total money spent and the number of different vehicle models that customer has bought.

SQL Question 7: What is the function of a primary key in a database?

The primary key of a table is a column or combination of columns that serves to uniquely identify each row in the table. To define a primary key in a SQL database, you can use the constraint.

For instance, consider a table of :

In this example, the column is the primary key of the AutoNation employees table.

Primary keys are important in databases for several reasons:

• Uniqueness: A primary key is used to uniquely identify each row in a table. This means that no two rows in the table can have the same primary key value. This is important because it helps to ensure the accuracy and integrity of the data in the table.
• Non-nullability: A primary key is typically defined as a non-null column, which means that it cannot contain a null value. This helps to ensure that every row in the table has a unique identifier.
• Relationship-building: Primary keys are often used to establish relationships between tables in a database. For example, you might use a primary key to link the table to the table.

SQL Question 8: Find the Average Price of Sold Cars

As part of an analysis into AutoNation's inventory and sales performance, you've been asked to determine the average selling price of each car model sold in the past year.

Example Input:

Example Output:

Answer:

The query first filters out records that have a sale_date later than or equal to '2022-01-01', then it groups the remaining records by car_model. The average sale_price for each group, rounded to 2 decimal places, is returned in the resulting groups. This provides the average selling price of each car model sold in the year 2022.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for aggregating sales data or this Wayfair Y-on-Y Growth Rate Question which is similar for analyzing sales performance.

SQL Question 9: Click-through Conversion Rates for AutoNation

Suppose AutoNation sends out emails to customers introducing new car models. In these emails, there are links that direct recipients to their website where they can view the details of the models and add any of their interest to their carts. AutoNation would want to track the following click-through and conversion rates:

1. Click-Through Rate (CTR): The ratio of users who click on the specific link to view the car details to the total number of users who read the emails.
2. Conversion Rate: The ratio of users who added the cars to their cart after viewing to the total number of users who clicked to view the car details.

Given two tables – "Emails" and "Website_Activities".

Example Input:

Example Input:

Write a PostgreSQL query to compute the click-through rate and conversion rate for each car model by the date.

Answer:

This SQL query joins the Website Activities on the Emails based on customer_id, car_model_id and date. It then groups the data by send_date and car_model_id, computes the total emails sent, click-through rate (sum of clicked / total emails sent), and conversion rate (sum of added_to_cart/ sum of clicked). The COALESCE function is used to handle possible division by zero for conversion_rate, where there might be clicks (email opened), but no conversion (car added to cart).

To solve a similar problem about calculating rates, solve this TikTok SQL question within DataLemur's interactive coding environment:

SQL Question 10: In SQL, what's the primary difference between the 'BETWEEN' and 'IN' operators?

The operator is used to select rows that fall within a certain range of values, while the operator is used to select rows that match values in a specified list.

For example, suppose you are a data analyst at AutoNation and have a table of advertising campaign data. To find campaigns with a spend between $1k and$5k, you could use BETWEEN:

To find advertising campaigns that were video and image based (as opposed to text or billboard ads), you could use the operator:

SQL Question 11: Find the Most Sold Car Model

As a data engineer in AutoNation, you are tasked with retrieving data to find out which car model has the most sales in each month from January to October 2022. Assume you have a database with two tables: and , where 'cars' contains information about the car, including its id and model, and 'sales' records the details of each sale, including the car_id, sale_date, and sale_price. Represent the answer with columns for month (mth), car_model, and total_sold.

Example Input:

Example Input:

Answer:

This query first creates a on the of both and , then it groups the resulting data by month and car model. The function is used to find the total number of sales for each car model in each month. The function gets the month from the sale date. The result is ordered firstly by month, then by total sold in a descending order, which ensures that for each month, the car model with the most sales is at the top.

How To Prepare for the AutoNation SQL Interview

The best way to prepare for a AutoNation SQL interview is to practice, practice, practice. In addition to solving the earlier AutoNation SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Google, Uber, and Microsoft.

Each exercise has hints to guide you, step-by-step solutions and best of all, there's an interactive SQL code editor so you can right in the browser run your SQL query and have it executed.

To prep for the AutoNation SQL interview it is also a great idea to practice interview questions from other automotive companies like:

• CarMax SQL questions

• Garrett Motion SQL questions

• Meritor SQL questions

• Asbury Automotive SQL questions

But if your SQL query skills are weak, don't worry about jumping right into solving questions – strengthen your SQL foundations with this free SQL for Data Analytics course.

This tutorial covers SQL concepts such as CASE/WHEN statements and AND/OR/NOT – both of these come up frequently during AutoNation SQL assessments.

AutoNation Data Science Interview Tips

What Do AutoNation Data Science Interviews Cover?

In addition to SQL query questions, the other question categories to practice for the AutoNation Data Science Interview include:

• Experimental Design & AB Testing Questions
• Python or R Coding Questions
• Product Analytics Questions
• ML Interview Questions
• Behavioral Interview Questions

How To Prepare for AutoNation Data Science Interviews?

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