11 Carter's SQL Interview Questions (Updated 2024)
Carter's employees use SQL often for analyzing customer purchase patterns for predictive modeling, and assessing inventory data. So, it shouldn't surprise you that Carter's asks SQL problems during interviews for Data Analyst, Data Science, and BI jobs.
So, to help you study, here's 11 Carter's SQL interview questions – able to answer them all?
11 Carter's SQL Interview Questions
SQL Question 1: Identifying Power Users from Carter's Customer Database
Question: Carter's is a retail company that deals in adult and kids' apparel. They want to identify their VIP (also known as "power" or "whale") users. Assume that a VIP user is a customer who has placed more than 3 orders each month consistently for the last six months. Write a SQL query to find these power users.
Consider the following tables:
Sample Input:
| order_id | user_id | order_date | product_id | order_amount |
|---|---|---|---|---|
| 17001 | 123 | 01/08/2022 | 70101 | 150.35 |
| 18002 | 231 | 01/24/2022 | 70952 | 98.90 |
| 19003 | 362 | 01/28/2022 | 70101 | 150.35 |
| 20004 | 123 | 02/26/2022 | 70952 | 98.90 |
| 21005 | 231 | 02/01/2022 | 70101 | 150.35 |
| 22006 | 123 | 02/28/2022 | 70101 | 150.35 |
| 23007 | 231 | 02/15/2022 | 70101 | 150.35 |
| 24008 | 362 | 03/20/2022 | 70952 | 98.90 |
| 25009 | 362 | 03/25/2022 | 70952 | 98.90 |
| 26010 | 123 | 03/05/2022 | 70101 | 150.35 |
| 27011 | 362 | 03/30/2022 | 70952 | 98.90 |
| 28012 | 123 | 04/03/2022 | 70952 | 98.90 |
| 29013 | 231 | 04/08/2022 | 70101 | 150. |
Expected Output:
| UserID | Month-Year | Orders Count |
|---|---|---|
| 123 | Jan-2022 | 2 |
| 123 | Feb-2022 | 3 |
| 123 | Mar-2022 | 3 |
| 123 | Apr-2022 | 3 |
| 362 | Jan-2022 | 2 |
| 362 | Feb-2022 | 1 |
| 362 | Mar-2022 | 3 |
| 362 | Apr-2022 | 2 |
Answer:
You can use the following SQL query to find power users:
The provided query groups orders by the and (formatted to show month and year only) and counts the number of orders placed by each user each month. It then filters the results to only include users who have placed more than three orders each month in the last six months.
To practice another SQL customer analytics question where you can solve it interactively and have your SQL code instantly graded, try this Walmart SQL Interview Question:
SQL Question 2: Department Salaries
You're given a table of Carter's employee and department salaries. Write a SQL query to find departments where the departments average salary is higher than the company's average salary.
You can solve this problem and run your code right in DataLemur's online SQL environment:
The answer is LONG – 30+ lines of SQL. You can find a detailed solution with hints here: Department Salaries.
SQL Question 3: Can you explain the purpose of the constraint and give an example of when you might use it?
The constraint is used to specify a condition that the data in a column must meet. If a row is inserted or updated and the data in the column doesn't meet the condition specified by the CHECK constraint, the operation will sadly fail.
For example, you might use a constraint to ensure that a column contains only positive numbers, or that a date is within a certain range.
For example, if you had a table of Carter's employees, here's an example of how to use the CHECK constraint in a CREATE TABLE statement:
SQL Question 4: Analyze Monthly Average Review Scores
Carter's is dedicated to improving their products based on customer feedback. For this purpose, they regularly collect reviews of their products. Each review will have a rating from 1 (worst) to 5 (best). They would like to analyze the monthly average review score for each product.
Write a SQL query to calculate the monthly average review score for each product and order the result by month and product id.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-06-08 | 33455 | 3 |
| 7802 | 265 | 2022-06-10 | 45678 | 5 |
| 5293 | 362 | 2022-06-18 | 33455 | 4 |
| 6352 | 192 | 2022-07-26 | 45678 | 3 |
| 4517 | 981 | 2022-07-05 | 45678 | 2 |
Example Output:
| mth | product | avg_stars |
|---|---|---|
| 6 | 33455 | 3.50 |
| 6 | 45678 | 5.00 |
| 7 | 45678 | 2.50 |
Answer:
In PostgreSQL, an example of a SQL query that would solve this would be:
This SQL query first extracts the month from the using . Then we group the results by month and product id with and calculate the average score of reviews for each group with . The final result is ordered by month and product id.
p.s. Window functions show up super often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: What does the clause do vs. the clause?
Before we address vs. question, let's address the clause which is used in a statement to group rows into a set of summary rows. It's typically used in conjunction with aggregate functions such as:
- `MIN
The clause is used to filter the groups created by the clause. It's similar to the clause, but it is used to specify conditions on the groups created by the clause, rather than on the individual rows of the table.
For example:
This query retrieves the total salary for each department and groups the rows by department. The clause then filters the groups to include only Carter's departments where the total salary is greater than $1 million
Note that the clause must be used after the clause and can only reference columns listed in the clause or aggregated columns selected by the statement.
SQL Question 6: Analyzing Sales Data
Carter's, known for its children's apparel, operates numerous stores worldwide and maintains an online retail presence as well. You've been given data of the online transactions of Carter's. Each record consists of the transaction's id, the customer's id, the product id, the quantity of the product purchased, and the date of the transaction.
Design a SQL query that can give a report showing the total quantity of each product sold for each month.
Example Input:
| transaction_id | customer_id | product_id | quantity | transaction_date |
|---|---|---|---|---|
| 5671 | 132 | 1069 | 2 | 06/04/2022 |
| 7862 | 759 | 2091 | 1 | 06/15/2022 |
| 7653 | 484 | 2091 | 3 | 06/20/2022 |
| 0983 | 521 | 1069 | 1 | 07/10/2022 |
| 8672 | 247 | 2084 | 4 | 07/26/2022 |
Answer:
This query groups the sales table by the month of the transaction and the product id. It then sums up the quantity of each product sold in each month. The results are ordered by month and by the total quantity of each product sold in descending order, so you can easily see which products sold the most each month.
SQL Question 7: How do and differ when it comes to ranking rows in a result set?
In SQL, both and are used to rank rows within a result set. The key difference between the two functions is how deal with two or more rows having the same value in the ranked column (aka how the break ties).
RANK(): When there's a tie, leaves a gap in the ranking. For example, if three rows are tied for 2nd place, the RANK() function will assign a rank of 2 to the first of these rows, a rank of 3 to the second row, and a rank of 4 to the third row.
DENSE_RANK(): For ties, does not leave a gap in the ranking. Instead, it assigns the same rank to all tied rows, and then makes the next row 1 bigger. Confusing, I know, but here's an example to make it more clear: if three rows are tied for 3rd place, the function will assign a rank of 3 to all three rows, and then assign a rank of 4 to the next row.
Check out the Carter's Inc. career page to see what qulifications they're looking for!
SQL Question 8: Filter Customers Based on Purchase History
Carter's would like to send out promotional emails for their new range of baby clothes. However, they want to target specific customers: those who have made at least one purchase in the past month but haven't made any purchases of baby clothes in the past six months. The goal is to promote the new range to customers who are active but haven't purchased baby clothes recently.
Given the table , create a PostgreSQL query to filter out the customers based on the conditions above.
Example Input:
| purchase_id | customer_id | purchase_date | product_id | category |
|---|---|---|---|---|
| 1781 | 234 | 06/09/2022 | 78001 | 'Kids' |
| 9320 | 567 | 07/15/2022 | 85234 | 'Baby' |
| 6274 | 234 | 07/26/2022 | 78001 | 'Kids' |
| 3710 | 789 | 05/05/2022 | 12345 | 'Baby' |
| 2317 | 789 | 08/01/2022 | 45678 | 'Men' |
Answer:
To meet the data filtering requirements for the given problem, we use the SQL clause to filter the table for purchases that occurred in the last month. We also use the condition combined with another statement to exclude any customers who have purchased baby clothes in the past six months. The keyword is used to ensure that each customer_id is unique in the result.
SQL Question 9: Find the Average Quantity of a specific product sold each day.
Carter's, a popular kids' clothing retailer, wants to understand the daily sales volume for each product in a way that is easy to compare across a product line. They ask you to write a SQL query to determine the average number of specific product, for instance, item_id '1001', sold per day over the past month. Assume that data is available in two tables - and .
The table has columns: , , , .
The table has columns: , , , .
Example Input:
| sales_id | item_id | quantity_sold | sale_date |
|---|---|---|---|
| 1 | 1001 | 20 | 01/01/2022 |
| 2 | 1001 | 15 | 01/02/2022 |
| 3 | 1001 | 25 | 01/03/2022 |
| 4 | 2001 | 30 | 01/01/2022 |
| 5 | 2001 | 40 | 01/02/2022 |
Example Input:
| product_id | product_name | product_category | product_price |
|---|---|---|---|
| 1001 | 'Baby Girl Dress' | 'clothing' | 25 |
| 2001 | 'Baby Boy Jeans' | 'clothing' | 30 |
Example Output:
| item_id | product_name | avg_daily_quantity_sold |
|---|---|---|
| 1001 | 'Baby Girl Dress' | 20 |
Answer:
This SQL query first joins the 'sales' and 'products' tables on the 'item_id' and 'product_id' fields to match each sale with the correct product. We're specifically looking at sales in the date range from January 1, 2022 to January 31, 2022 for the product with item_id '1001'. It then calculates the average quantity sold per day (avg_daily_quantity_sold) by using the AVG function on the 'quantity_sold' field, grouping by 'item_id' and 'product_name' to get the average for each specific product. The result is rounded to 2 decimal places for clarity.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for requiring calculations based on product sales or this Wayfair Y-on-Y Growth Rate Question which is similar for involving sales data analysis.
SQL Question 10: How can you select records without duplicates from a table?
The clause in SQL allows you to select records that are unique, eliminating duplicates.
For example, if you had a table of Carter's employees, and wanted to see what are all the unique job titles that currently worked at the company, you could write the following query:
SQL Question 11: Calculate the Average Sale Price of Different Product Categories
Carter's is a major American designer and marketer of children's apparel. You have been given a list of transactions containing details about the product sold, its category, the sale price, and the date of sale. Using this data, write an SQL query to find out the average sale price of each product category for each month.
Please base your calculation on the following sample data:
Example Input:
| transaction_id | transaction_date | product_id | product_category | sale_price |
|---|---|---|---|---|
| 101 | 2022-06-04 | 2001 | 'Tops' | 30.99 |
| 102 | 2022-06-15 | 3001 | 'Bottoms' | 15.49 |
| 103 | 2022-06-20 | 4001 | 'Accessories' | 7.99 |
| 104 | 2022-07-02 | 2002 | 'Tops' | 25.85 |
| 105 | 2022-07-10 | 3002 | 'Bottoms' | 18.59 |
Example Output:
| month | product_category | avg_sale_price |
|---|---|---|
| 6 | 'Tops' | 30.99 |
| 6 | 'Bottoms' | 15.49 |
| 6 | 'Accessories' | 7.99 |
| 7 | 'Tops' | 25.85 |
| 7 | 'Bottoms' | 18.59 |
Answer:
The following SQL query solves the problem:
This query first extracts the month from the transaction_date, groups the transactions based on the month and the product_category, and then calculates the average sale price for each group. The result is sorted by month and product_category.
Preparing For The Carter's SQL Interview
The key to acing a Carter's SQL interview is to practice, practice, and then practice some more!
Beyond just solving the above Carter's SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like FAANG and tech startups.
Each exercise has hints to guide you, step-by-step solutions and crucially, there is an online SQL coding environment so you can instantly run your SQL query and have it checked.
To prep for the Carter's SQL interview it is also a great idea to practice SQL problems from other apparel companies like:
However, if your SQL coding skills are weak, don't worry about jumping right into solving questions – go learn SQL with this interactive SQL tutorial.
This tutorial covers things like filtering groups with HAVING and UNION vs. joins – both of these come up routinely in Carter's SQL interviews.
Carter's Data Science Interview Tips
What Do Carter's Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories covered in the Carter's Data Science Interview are:
- Statistics and Probability Questions
- Python Pandas or R Coding Questions
- Analytics and Product-Metrics Questions
- ML Interview Questions
- Behavioral Based Interview Questions
How To Prepare for Carter's Data Science Interviews?
I'm sort of biased, but I believe the best way to prepare for Carter's Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
The book has 201 interview questions taken from companies like Google, Tesla, & Goldman Sachs. It also has a crash course covering 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.