11 Ralph Lauren SQL Interview Questions (Updated 2024)
Ralph Lauren employees write SQL queries daily customer purchase trends and inventory management. That's why Ralph Lauren often tests SQL query questions during interviews for Data Science and Data Engineering positions.
Thus, to help you practice, here's 11 Ralph Lauren SQL interview questions – can you solve them?
11 Ralph Lauren SQL Interview Questions
SQL Question 1: Identify Power Shoppers at Ralph Lauren
Ralph Lauren is interested in identifying their top customers for a special rewards program. A top customer, or "power shopper", is defined as a user who has spent more than $10,000 in total over the past 12 months.
Two tables are given - and . table keeps track of each user's details while table records all the purchases made by the users.
Assuming today's date is "09/15/2022".
Example Input:
Example Input:
Answer:
This PostgreSQL query first joins the and tables on the field. It then filters for purchases made within the last 12 months, as determined by the clause. The clause is used to consolidate all purchases made by each user. Lastly, it employs to filter out users who have spent less than 10,000 in the past year.
To solve a related super-user data analysis question on DataLemur's free online SQL coding environment, try this Microsoft Teams Power User SQL Interview Question:
SQL Question 2: Department vs. Company Salary
You're given a table of Ralph Lauren employee and department salary data. Write a SQL query to find departments where the departments average salary is higher than the company's average salary.
Try this interview question 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: Why would you use the SQL constraint?
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 Ralph Lauren employees, here's an example of how to use the CHECK constraint in a CREATE TABLE statement:
SQL Question 4: Analyze Product Reviews Over Time
Ralph Lauren, being a brand with a wide range of products, relies heavily on customer reviews for their products. You are provided with a table that contains customer reviews data which includes , , , , and (rating).
Your task is to write a SQL query to compute the average reviews received by each product on a monthly basis. Order the result by the year and month in ascending order, then by average stars in descending order.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-06-08 | 50001 | 4 |
| 7802 | 265 | 2022-06-10 | 69852 | 4 |
| 5293 | 362 | 2022-06-18 | 50001 | 3 |
| 6352 | 192 | 2022-07-26 | 69852 | 3 |
| 4517 | 981 | 2022-07-05 | 69852 | 2 |
Example Output:
| year_month | product_id | avg_stars |
|---|---|---|
| 2022-06 | 50001 | 3.50 |
| 2022-06 | 69852 | 4.00 |
| 2022-07 | 69852 | 2.50 |
Answer:
This query uses the PostgreSQL function to truncate the to the nearest month and year (giving us '2022-06-01', etc.). It then groups the reviews by this truncated date and the , calculating the average number of stars for each group. The results are ordered first by date in ascending order, then by the average number of stars in descending order.
Pro Tip: Window functions are a frequent SQL interview topic, so practice all the window function problems on DataLemur
SQL Question 5: What is the difference between a primary key and a foreign key?
A primary key is a column (or set of columns) in a table that uniquely identifies each row in the table. It cannot contain null values and must be unique across all rows in the table.
A foreign key is a column (or set of columns) in a table that references the primary key of another table. It is used to establish a relationship between the two tables. A foreign key can contain null values, and multiple rows in the referencing table can reference the same row in the referenced table.
For example, consider a database with two tables: and . The Ralph Lauren customers table might have a primary key column called , while the Ralph Lauren orders table might have a foreign key column called that references the column in the table. This establishes a relationship between the two tables, such that each row in the orders table corresponds to a specific Ralph Lauren customer.
SQL Question 6: Ralph Lauren Customers Filtering
For Ralph Lauren's customer records, you are tasked with retrieving all customers from the United States that have made purchases summing up to more than $1000 in total over the first half of the year, 2022.
Sample data for this scenario would look like this:
Example Input:
| purchase_id | customer_id | country | amount | purchase_date |
|---|---|---|---|---|
| 514 | 3456 | USA | 300.00 | 01/25/2022 |
| 847 | 2875 | AUS | 100.00 | 02/11/2022 |
| 3421 | 3456 | USA | 350.00 | 02/28/2022 |
| 7836 | 3945 | USA | 275.00 | 03/04/2022 |
| 6845 | 3456 | USA | 400.00 | 04/15/2022 |
| 7610 | 2875 | AUS | 250.00 | 05/29/2022 |
| 3492 | 3945 | USA | 350.00 | 06/15/2022 |
Answer:
In order to solve this problem, you would want to filter for customers based in the USA that have made purchases totaling over $1000 within the first half of 2022. You could do this with the WHERE, AND and SUM commands like so:
This query will first filter for purchases made within the US and the first half of 2022, then group the remaining records by to get the total purchase amount for each customer within this period. The clause then ensures that only the customers who spent over $1000 in total are selected.
SQL Question 7: What distinguishes an inner join from a full outer join?
An inner join only includes rows from both tables that satisfy the join condition, whereas a full outer join includes all rows from both tables, regardless of whether they match the join condition or not.
For example, suppose you had a table of Ralph Lauren orders and Ralph Lauren customers.
INNER JOIN: When there is a match in the shared key or keys, rows from both tables are retrieved. In this example, an between the Orders and Customers tables would retrieve rows where the in the Orders table matches the in the Customers table.
FULL OUTER JOIN: A retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, NULL values will be returned for the columns of the non-matching table.
SQL Question 8: Average Price of Given Clothing Type Sold
At Ralph Lauren, each clothing item falls under a certain type (e.g., Shirts, Pants, Shoes, etc.). Over a certain period, what is the average selling price for each type of clothing?
Example Input:
| sale_id | customer_id | sale_date | clothing_type | selling_price |
|---|---|---|---|---|
| 1111 | 879 | 01/08/2021 | Shirts | 55.60 |
| 2222 | 564 | 12/07/2021 | Shirts | 45.90 |
| 3333 | 234 | 22/06/2021 | Pants | 89.50 |
| 4444 | 321 | 19/06/2021 | Shoes | 120.00 |
| 5555 | 678 | 29/07/2021 | Shoes | 150.25 |
Example Output:
| clothing_type | avg_price |
|---|---|
| Shirts | 50.75 |
| Pants | 89.50 |
| Shoes | 135.13 |
Answer:
This query finds the average price of each type of clothing by grouping the sales data by clothing type and then applying the AVG function to the selling price for each group. The result is a list of clothing types accompanied by their average selling price.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating category-based averages or this Wayfair Y-on-Y Growth Rate Question which is similar for analysis of sales data.
SQL Question 9: Finding top-selling product categories
You are a data analyst at Ralph Lauren. Consider you have a 'sales' table which contains information about all purchases made on the Ralph Lauren's official website. Each record includes the date when a particular item was sold (), the item's , the it falls under, and the of that item sold.
Assuming each product only belongs to one category, write a SQL query that will return the with the highest total quantity sold for each month.
Example Input:
| sale_id | sale_date | product_id | category_id | quantity |
|---|---|---|---|---|
| 1001 | 2022-06-01 | 4001 | 1 | 3 |
| 1002 | 2022-06-03 | 4002 | 2 | 1 |
| 1003 | 2022-06-05 | 4001 | 1 | 2 |
| 1004 | 2022-06-09 | 4003 | 3 | 1 |
| 1005 | 2022-07-02 | 4002 | 2 | 5 |
| 1006 | 2022-07-10 | 4003 | 3 | 4 |
| 1007 | 2022-07-15 | 4001 | 1 | 3 |
| 1008 | 2022-07-30 | 4003 | 3 | 5 |
Example Output:
| mth | category | quantity |
|---|---|---|
| 6 | 1 | 5 |
| 7 | 3 | 9 |
Answer:
The query begins by summing up the quantities over a partition defined by the month and category of sale. The outer query then selects the maximum summed quantity for each month (with categories as a second level of grouping). This returns the category with the highest quantity of products sold for each month.
SQL Question 10: How does differ from just ?
Both and are used to combine the results of two or more SELECT statements into a single result set.
However, only includes one instance of a duplicate, whereas includes duplicates.
SQL Question 11: Finding Specific Customer Data in the Database
Ralph Lauren is trying to identify customers who have an "@ralphlauren.com" email domain. In the customer database, the data is stored under different columns, including first name, last name, email, customer id. Write a SQL query to select customers who have a "@ralphlauren.com" email domain.
Consider the following Example Input:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 12345 | John | Doe | john.doe@gmail.com |
| 23456 | Jane | Smith | jane.smith@ralphlauren.com |
| 34567 | Alex | Brown | alex.brown@ralphlauren.com |
| 45678 | Emma | Johnson | emma.johnson@yahoo.com |
| 56789 | Oliver | Davis | oliver.davis@ralphlauren.com |
Answer:
In PostgreSQL, you can use the keyword to match a specified pattern. The wildcard character is used to substitute any number of characters. Here is the necessary query:
This query will check the column in the table and only return the rows where the field ends with "@ralphlauren.com".
The output would enlist customers who have a "@ralphlauren.com" email domain:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 23456 | Jane | Smith | jane.smith@ralphlauren.com |
| 34567 | Alex | Brown | alex.brown@ralphlauren.com |
| 56789 | Oliver | Davis | oliver.davis@ralphlauren.com |
Preparing For The Ralph Lauren SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Ralph Lauren SQL interview is to solve as many practice SQL interview questions as you can!
In addition to solving the above Ralph Lauren SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like FAANG and tech startups.
Each exercise has hints to guide you, detailed solutions and crucially, there is an online SQL coding environment so you can instantly run your SQL query and have it executed.
To prep for the Ralph Lauren SQL interview you can also be useful to practice SQL problems from other apparel companies like:
In case your SQL foundations are weak, don't worry about jumping right into solving questions – strengthen your SQL foundations with this SQL tutorial for Data Analytics.
This tutorial covers things like joining a table to itself and LAG window function – both of which pop up often during Ralph Lauren SQL assessments.
Ralph Lauren Data Science Interview Tips
What Do Ralph Lauren Data Science Interviews Cover?
In addition to SQL interview questions, the other types of questions covered in the Ralph Lauren Data Science Interview are:
- Probability & Stats Questions
- Coding Questions in Python or R
- Product Data Science Interview Questions
- ML Interview Questions
- Resume-Based Behavioral Questions
Also stay up to date with Ralph Lauren news to help you prepare for the interview!
How To Prepare for Ralph Lauren Data Science Interviews?
I'm sorta biased, but I think the best way to prep for Ralph Lauren Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
The book has 201 interview questions taken from tech companies like Google & Microsoft. It also has a crash course covering SQL, Product-Sense & ML. And finally it's helped thousands of people land their dream job in data, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.