10 Autoliv SQL Interview Questions (Updated 2024)
Data Analytics, Data Science, and Data Engineering employees at Autoliv write SQL queries as a core part of their job. They use it to analyze crash-test data for safety improvements, and manage manufacturing databases for efficient production tracking. Which is why Autoliv evaluates jobseekers on SQL interview problems.
Thus, to help you prepare, we've collected 10 Autoliv SQL interview questions – how many can you solve?
10 Autoliv SQL Interview Questions
SQL Question 1: Compute the Average Monthly Failure Rate for Each Product Type
Assume you work for Autoliv, a company specialising in automotive safety systems. They have a table that logs every product failure with a timestamp and product information. Your task is to write a PostgreSQL query that calculates the average failure rate for each type of product on a monthly basis.
Here's a sample table:
Example Input
| failure_id | product_type | failure_date | failure_count |
|---|---|---|---|
| 1001 | airbag | 01/01/2021 00:00:00 | 2 |
| 1002 | seatbelt | 02/01/2021 00:00:00 | 3 |
| 1003 | airbag | 02/07/2021 00:00:00 | 1 |
| 1004 | seatbelt | 02/14/2021 00:00:00 | 2 |
| 1005 | airbag | 03/01/2021 00:00:00 | 1 |
| 1006 | seatbelt | 03/01/2021 00:00:00 | 2 |
| 1007 | airbag | 04/01/2021 00:00:00 | 3 |
Your result should look like this:
Example Output
| month | product_type | avg_failures |
|---|---|---|
| 01 | airbag | 2.00 |
| 02 | airbag | 1.00 |
| 02 | seatbelt | 2.50 |
| 03 | airbag | 1.00 |
| 03 | seatbelt | 2.00 |
| 04 | airbag | 3.00 |
Answer
Explanation: This query first extracts the month from the column. Then it computes the average over each for each month. The clause with is a window function; it does the calculation (AVG) for each group of rows (month, product_type). The result is then sorted by and .
To solve a related window function SQL problem on DataLemur's free interactive coding environment, try this Amazon BI Engineer interview question:
SQL Question 2: Department vs. Company Salary
Imagine you had a table of Autoliv employee salaries, along with which department they were in. Write a query to compare the average salary of employees in each department to the company's average salary. Return the comparison result as 'higher', 'lower', or 'same' for each department. Display the department ID, payment month (in MM-YYYY format), and the comparison.
Solve this question directly within the browser on DataLemur:
The answer is LONG – 30+ lines of SQL. You can find a detailed solution with hints here: Department Salaries.
SQL Question 3: What is denormalization?
Database denormalization is when you add redundancy to a database, and break typical normalization rules (codified by the 1st, 2nd, 3rd normal forms).
Denormalization is typically used to improve the performance of a database, particularly when the database is being for OLAP (Online Analytical Processing) purposes. By denormalizing a database, you can reduce the number of joins that are required to retrieve data, which can greatly improve the speed of queries since joins are costly and slow. However, denormalization can also introduce some problems, such as increased data redundancy and the need for more complex update and delete operations since data has been duplicated into multiple tables.
In general, denormalization should be used with caution and only after careful consideration of the trade-offs involved. It's typically better to start with a well-normalized database design then denormalize only if your database isn't scaling as well as you want.
SQL Question 4: Vehicle Production Analysis
Autoliv is a company that specializes in automotive safety systems. They want to analyze their vehicle production, primarily focusing on the number of safety systems installed in each vehicle model they produce. Use the table and table to find the vehicle model that has the most safety systems installed.
Sample Input:
| vehicle_id | model | production_year |
|---|---|---|
| 1001 | 'Model A' | 2021 |
| 1002 | 'Model B' | 2021 |
| 1003 | 'Model C' | 2021 |
| 1004 | 'Model A' | 2022 |
| 1005 | 'Model B' | 2022 |
Sample Input:
| system_id | vehicle_id | system_type |
|---|---|---|
| 2001 | 1001 | 'Airbag' |
| 2002 | 1001 | 'Seatbelt' |
| 2003 | 1001 | 'ABS' |
| 2004 | 1002 | 'Seatbelt' |
| 2005 | 1003 | 'Airbag' |
| 2006 | 1003 | 'Seatbelt' |
| 2007 | 1003 | 'ABS' |
| 2008 | 1004 | 'Airbag' |
| 2009 | 1004 | 'Seatbelt' |
| 2010 | 1005 | 'Airbag' |
| 2011 | 1005 | 'Seatbelt' |
Answer:
This query first joins the and tables on . This results in a virtual table that contains each vehicle model along with each safety system installed in it. Then, it groups this table by and for each group (i.e., each vehicle model), it counts the number of rows (i.e., the number of safety systems). Finally, it orders the results by in descending order and returns the top result. This will be the vehicle model with the most safety systems installed.
SQL Question 5: What is the process for finding records in one table that do not exist in another?
To find records in one table that aren't in another, you can use a and check for values in the right-side table.
Here is an example using two tables, Autoliv employees and Autoliv managers:
This will return all rows from Autoliv employees where there is no matching row in managers based on the column.
You can also use the operator in PostgreSQL and Microsoft SQL Server to return the records that are in the first table but not in the second. Here is an example:
This will retrieve all rows from employees that do not appear in managers. The operator works by retreivingthe rows that are returned by the first query, but not by the second.
Please note that is not supported by all DBMS systems, such as MySQL and Oracle (however, you can use the operator to achieve a similar outcome).
SQL Question 6: Average production time for a specific model
Suppose we have a table that keeps records of when each automobile safety product (like seatbelts, airbags etc) went into production and when it was finished for the automobile company "Autoliv". The table ('production') includes columns for 'product_id', 'model', 'start_date' and 'end_date'. Write a SQL query to find the average production time in days for each model.
Example Input:
| product_id | model | start_date | end_date |
|---|---|---|---|
| 1051 | Seatbelt | 2021-01-01 | 2021-01-05 |
| 1362 | Airbag | 2021-02-03 | 2021-02-07 |
| 2973 | Seatbelt | 2021-03-04 | 2021-03-10 |
| 3412 | Airbag | 2021-04-06 | 2021-04-10 |
| 4179 | Seatbelt | 2021-05-07 | 2021-05-15 |
Example Output:
| model | average_production_time |
|---|---|
| Seatbelt | 6.67 |
| Airbag | 4.00 |
Answer:
This query first calculates the production time for each product by subtracting the start_date from the end_date (and then using EXTRACT to only retrieve the day part of the interval). After that, it takes the average of these production times grouped by model.
To practice a very similar question try this interactive Tesla Unfinished Parts Question which is similar for analyzing product production times or this Facebook Average Post Hiatus (Part 1) Question which is similar for calculating duration-based statistics.
SQL Question 7: What's a primary key?
A primary key is a column or set of columns in a table that uniquely identifies each row in the table. The primary key is used to enforce the uniqueness and non-nullability of the rows in the table.
In a SQL database, a primary key is defined using the constraint. For example, say you had a table of :
In this example, the column is the primary key of the Autoliv employees table. It is defined as an integer and is marked as the primary key using the constraint.
A table can have only one primary key, but the primary key can consist of multiple columns. For example, say you had a table of Autoliv customer transactions:
In the above example, the primary key of the Orders table consists of two columns: TransactionID and ProductID. This means that the combination of OrderID and ProductID must be unique for every row in the table.
SQL Question 8: Average Price of Autoliv Products
Given the 'sales' and 'products' tables of the Autoliv company, which manufactures and sells safety parts for automobiles, find the average price of each product sold each month.
Example Input:
| sale_id | sale_date | product_id | price |
|---|---|---|---|
| 1011 | 06/08/2022 00:00:00 | 7001 | 120 |
| 1832 | 06/09/2022 00:00:00 | 8002 | 110 |
| 3903 | 06/18/2022 00:00:00 | 7001 | 125 |
| 4862 | 07/01/2022 00:00:00 | 8002 | 100 |
| 5678 | 07/15/2022 00:00:00 | 8002 | 115 |
Example Input:
| product_id | product_name |
|---|---|
| 7001 | Airbag |
| 8002 | Safety belt |
Example Output:
| mth | product | avg_price |
|---|---|---|
| 6 | Airbag | 122.50 |
| 6 | Safety belt | 110.00 |
| 7 | Safety belt | 107.50 |
Answer:
The question asks to find the average price of each product sold each month. The query first joins the 'sales' and 'products' tables on 'product_id'. The function is used to obtain the month from the 'sale_date'. Then, the clause groups the data by month and product. The function is used to calculate the average price of the products sold in each group. The output is ordered by month and product.
SQL Question 9: Find Records with Particular Car Model in Autoliv Database
As an analyst at Autoliv, you need to find more data about a particular car model as part of your ongoing analysis of car safety metrics. The task is to generate a list of entries involving a specific car model. In this regard, write a query that can filter records of car models stored in a database and return details where the model name contains 'Sedan'.
The table looks like this:
Example Input:
Answer:
You can use the keyword in SQL to solve this task:
Writeup of Answer:
This query accesses the table and filters out the records where the field contains the string 'Sedan'. The '%' on both sides of 'Sedan' is a wildcard in SQL, which can represent zero, one, or multiple characters, enabling a match anywhere in the string. Therefore, every record in the column containing 'Sedan' will be selected. The resulting output will be a list of all such entries from the Autoliv's database.
Learn more about Autoliv and read their Diversity and Inclusion statements.
SQL Question 10: What do stored procedures do?
Stored procedures in SQL are like recipes in a cookbook. Just like a recipe tells you the ingredients and instructions for making a particular dish, a stored procedure tells the DBMS the logic/statements needed to perform a specific task. Just like you can use a recipe to make the same dish over and over again, you can use a stored procedure to repeat the same task multiple times with different input parameters (which is why stored procedures are so damn useful!).
Say you were a Data Analyst working on a HR analytics project. A common sub-task you might have to do is calculate the average salary for a given department at Autoliv, which would be perfect for a stored procedure:
To call this stored procedure and find the average salary for the Data Science department you'd execute a query like this:
Preparing For The Autoliv SQL Interview
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews.
Besides solving the earlier Autoliv SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.
Each interview question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and most importantly, there's an online SQL coding environment so you can instantly run your query and have it checked.
To prep for the Autoliv SQL interview it is also helpful to solve interview questions from other automotive companies like:
However, if your SQL skills are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this free SQL for Data Analytics course.
This tutorial covers things like working with string/text data and Subquery vs. CTE – both of which pop up frequently in Autoliv SQL interviews.
Autoliv Data Science Interview Tips
What Do Autoliv Data Science Interviews Cover?
In addition to SQL query questions, the other types of questions to practice for the Autoliv Data Science Interview are:
- Statistics and Probability Questions
- Python Pandas or R Coding Questions
- Business Sense and Product-Sense Questions
- ML Interview Questions
- Behavioral & Resume-Based Questions
How To Prepare for Autoliv Data Science Interviews?
I'm sort of biased, but I believe the best way to study for Autoliv Data Science interviews is to read the book Ace the Data Science Interview.
The book solves 201 interview questions taken from tech companies like Netflix, Google, & Airbnb. It also has a crash course covering Python, SQL & ML. And finally it's vouched for by the data community, which is how it's gotten to be an Amazon best-seller with over 1000+ 5-star reviews.