8 LCI Industries SQL Interview Questions (Updated 2024)
At LCI Industries, SQL used for analyzing production data for quality control and managing supply-chain logistics. For this reason LCI Industries asks SQL query questions during interviews for Data Science and Data Engineering positions.
So, to help you study, here's 8 LCI Industries SQL interview questions – able to solve them?
8 LCI Industries SQL Interview Questions
SQL Question 1: Calculate the monthly average sales per product
LCI Industries manufactures leisure products across various product lines and these products are sold globally. You are given a dataset named 'sales' containing product-wise sales information, such as product_id, sales_date, and units_sold. Now, each product may have multiple entries in a given month because products are sold throughout the month.
The task is to write a SQL query to calculate the average sales per product for each month.
Example Input:
| sales_id | sales_date | product_id | units_sold |
|---|---|---|---|
| 101 | 2022-06-01 | 50001 | 10 |
| 102 | 2022-06-07 | 69852 | 5 |
| 103 | 2022-06-15 | 50001 | 15 |
| 104 | 2022-07-02 | 69852 | 8 |
| 105 | 2022-07-12 | 69852 | 7 |
Example Output:
| month | product | avg_units_sold |
|---|---|---|
| 6 | 50001 | 12.50 |
| 6 | 69852 | 5.00 |
| 7 | 69852 | 7.50 |
Answer:
This query first extracts the month from the sales_date using . It then groups the data by 'month' and 'product' and for each group, it calculates the average units sold. The result is ordered by 'month' and 'product'. The function works on the set of values for each group and returns the average sales per product for each month.
p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 2: 2nd Highest Salary
Given a table of LCI Industries employee salary data, write a SQL query to find the 2nd highest salary among all employees.
LCI Industries Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
Test your SQL query for this interview question and run your code right in DataLemur's online SQL environment:
Answer:
You can find a step-by-step solution with hints here: 2nd Highest Salary.
Check out the LCI Industries career page, to see what qulifications they're looking for!
SQL Question 3: What's a constraint in SQL, and do you have any examples?
Constraints are just rules your DBMS has to follow when updating/inserting/deleting data.
Say you had a table of LCI Industries products and a table of LCI Industries customers. Here's some example SQL constraints you'd use:
NOT NULL: This constraint could be used to ensure that certain columns in the product and customer tables, such as the product name and customer email address, cannot contain NULL values.
UNIQUE: This constraint could be used to ensure that the product IDs and customer IDs are unique. This would prevent duplicate entries in the respective tables.
PRIMARY KEY: This constraint could be used to combine the NOT NULL and UNIQUE constraints to create a primary key for each table. The product ID or customer ID could serve as the primary key.
FOREIGN KEY: This constraint could be used to establish relationships between the LCI Industries product and customer tables. For example, you could use a foreign key to link the customer ID in the customer table to the customer ID in the product table to track which products each customer has purchased.
CHECK: This constraint could be used to ensure that certain data meets specific conditions. For example, you could use a CHECK constraint to ensure that LCI Industries product prices are always positive numbers.
DEFAULT: This constraint could be used to specify default values for certain columns. For example, you could use a DEFAULT constraint to set the customer registration date to the current date if no value is provided when a new customer is added to the database.
SQL Question 4: Analyzing Click-Through and Conversion Rates for LCI Industries
LCI Industries is a company that is interested in understanding how effective their digital marketing strategies are. They specifically want to understand click-through rates (CTR) of their ads and also the conversion rates – the percentage of users who add a product to a cart after viewing it.
Here are the two tables with some sample data to setup the problem:
| click_id | user_id | click_time | ad_id |
|---|---|---|---|
| 5231 | 101 | 06/08/2022 00:00:00 | 68284 |
| 7632 | 234 | 06/10/2022 00:00:00 | 63873 |
| 8193 | 675 | 06/11/2022 00:00:00 | 68284 |
| 6242 | 359 | 06/11/2022 00:00:00 | 63873 |
| 9917 | 898 | 06/12/2022 00:00:00 | 68284 |
| action_id | user_id | product_id | action_time |
|---|---|---|---|
| 2917 | 101 | 72800 | 06/08/2022 00:05:00 |
| 2082 | 234 | 62405 | 06/10/2022 00:10:00 |
| 3943 | 675 | 72800 | 06/12/2022 00:00:00 |
| 2242 | 359 | 62405 | 06/11/2022 00:15:00 |
| 7917 | 898 | 72800 | 06/12/2022 00:09:00 |
The table represents all the clicks on various ads, with each ad representing a product. The table represents users adding products to the cart. The same user id in both tables indicates that the user clicked an ad and then added the same product to the cart.
Now let's write a query that calculates the click-through rate and conversion rate per ad for a given period:
Answer:
This query first calculates the total number of clicks for each ad and the total number of products added to the cart for each ad. It then joins these two tables and calculates the conversion rate by dividing the number of cart additions by the total clicks for each ad. The coalesce function ensures that if there are no matches in the table for an ad, it would consider the as 0 to avoid any division by zero errors.
To practice another question about calculating rates, try this TikTok SQL Interview Question on DataLemur's online SQL code editor:
SQL Question 5: In SQL, are values same the same as zero or a blank space?
A value represents a missing or unknown value. It is different from a zero or a blank space, which are actual values.
It's important to handle values properly in SQL because they can cause unexpected results if not treated correctly. For example, comparisons involving values always result in . Also values are not included in calculations. For example, will ignore values in the column.
SQL Question 6: Average Cost Analysis of Materials
LCI Industries is into manufacturing and supplying of a range of products in the automobile, marine, and rail industries. As a part of cost control and efficiency exercise, find out the average cost of materials used by the company in each quarter of the year.
We have the table that contains information about the materials purchased by the company, and their costs.
Example Input:
| material_id | purchase_date | material_type | cost |
|---|---|---|---|
| 001 | 01/15/2022 | Steel | 1050 |
| 002 | 02/12/2022 | Aluminum | 800 |
| 003 | 03/08/2022 | Rubber | 300 |
| 004 | 04/20/2022 | Steel | 1200 |
| 005 | 05/16/2022 | Aluminum | 870 |
| 006 | 06/22/2022 | Plastic | 200 |
| 007 | 07/18/2022 | Steel | 1150 |
| 008 | 08/20/2022 | Aluminum | 920 |
We need to derive a result that looks something like this:
Example Output:
| quarter | material_type | avg_cost |
|---|---|---|
| Q1 | Steel | 1050.00 |
| Q1 | Aluminum | 800.00 |
| Q1 | Rubber | 300.00 |
| Q2 | Steel | 1200.00 |
| Q2 | Aluminum | 870.00 |
| Q2 | Plastic | 200.00 |
| Q3 | Steel | 1150.00 |
| Q3 | Aluminum | 920.00 |
Answer:
With this query, we are using the clause with the aggregate function to calculate the average cost of each material type in each quarter. We have used a statement to map the months to their corresponding quarters. The query returns the average cost grouped by quarter and material type.
SQL Question 7: What is the purpose of a primary key in a database?
A primary key is a column or group of columns that uniquely identifies a row in a table. For example, say you had a database of LCI Industries marketing campaigns data:
In this LCI Industries example, the CampaignID column is the primary key of the MarketingCampaigns table. The constraint ensures that no two rows have the same CampaignID. This helps to maintain the integrity of the data in the table by preventing duplicate rows.
SQL Question 8: Calculate Average Considering Discounts for Each ProductCategory
LCI Industries operates a large number of manufacturing facilities across various regions. They offer products that are eligible for different levels of discounts. We want to calculate the average price for each product category after taking into account the discounts that have been applied.
Consider the following tables:
Example Input:
| product_id | product_name | product_category | price |
|---|---|---|---|
| 1001 | Solar Panel | Energy | 150 |
| 1002 | Bike Rack | Outdoor | 90 |
| 1003 | Window AC | Cooling | 250 |
| 1004 | Portable Heater | Heating | 75 |
| 1005 | Tire Kit | Automotive | 50 |
Example Input:
| product_id | discount_percentage |
|---|---|
| 1001 | 5 |
| 1002 | 10 |
| 1003 | 15 |
| 1004 | 20 |
| 1005 | 25 |
Write a PostgreSQL query to calculate the average price for each after deducting the discount. Round the result to two decimal places.
The output should contain and .
Answer:
This query fist joins the and tables based on . The average price for each product category is calculated by first subtracting the discount percentage from the price, and this result is averaged using the AVG function. The ROUND function is used to restrict the result to two decimal places. The result is grouped by to get the average price for each category after taking into account the discounts.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating results for each category or this Amazon Average Review Ratings Question which is similar for calculating average metrics for each product.
LCI Industries SQL Interview Tips
The key to acing a LCI Industries SQL interview is to practice, practice, and then practice some more!
Beyond just solving the above LCI Industries SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Facebook, Google, and VC-backed startups.
Each interview question has multiple hints, fully explained answers along with a discussion board to see how others solved it and crucially, there is an interactive coding environment so you can right online code up your SQL query answer and have it executed.
To prep for the LCI Industries SQL interview it is also useful to practice interview questions from other automotive companies like:
In case your SQL coding skills are weak, forget about going right into solving questions – improve your SQL foundations with this DataLemur SQL Tutorial.
This tutorial covers topics including math functions in SQL and AND/OR/NOT – both of these come up often in LCI Industries SQL assessments.
LCI Industries Data Science Interview Tips
What Do LCI Industries Data Science Interviews Cover?
In addition to SQL query questions, the other types of questions tested in the LCI Industries Data Science Interview are:
- Probability & Stats Questions
- Python Pandas or R Coding Questions
- Product-Sense Questions
- ML Interview Questions
- Behavioral Interview Questions
How To Prepare for LCI Industries Data Science Interviews?
The best way to prepare for LCI Industries Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from companies like Google, Tesla, & Goldman Sachs
- A Crash Course on Python, SQL & ML
- Great Reviews (1000+ 5-star reviews on Amazon)