9 PVH Corp SQL Interview Questions (Updated 2025)

PVH Corp employees use SQL daily for trend prediction, and managing customer databases for targeted marketing campaigns. For this reason PVH Corp often tests SQL coding questions in interviews for Data Analyst, Data Science, and BI jobs.

Thus, to help you practice, here’s 9 PVH Corp SQL interview questions – able to answer them all?

9 PVH Corp SQL Interview Questions

SQL Question 1: Calculate the monthly sales for each product

PVH Corp. is a global apparel company, owning brands like Tommy Hilfiger, Calvin Klein, and many others. A common query might involve analyzing the monthly sales of their different products over a period of time. You are given a dataset containing the sales transactions. Write a SQL query to calculate the total sales per month for each product using window functions. Assume that every transaction in the dataset is completed.

Suppose you have the following transaction table:

transaction Example Input:

The output should return the total monthly sales for each product.

Answer:

SELECT 
  product,
  EXTRACT(MONTH FROM transaction_date) AS month,
  SUM(amount) OVER (
        PARTITION BY product, 
        EXTRACT(MONTH FROM transaction_date)
        ORDER BY transaction_date
        ) as total_sales_monthly 
FROM 
  transaction 

This query partitions the data by product and month, then sums up the sales amount from the beginning of each partition. This provides a rolling sum of sales for each product in each month. The window specification ORDER BY transaction_date is necessary to perform the cumulative sum in the correct order. EXTRACT is used to get the month part of the transaction_date.

Example Output:

Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur

SQL Question 2: Highly-Paid Employees

Assume there was a table of PVH Corp employee salary data. Write a SQL query to find all employees who earn more than their direct manager.

PVH Corp employees Example Input:

Example Output:

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

Test your SQL query for this problem interactively on DataLemur:

Answer:

First, we perform a SELF-JOIN where we treat the first employee table (mgr) as the managers' table and the second employee table (emp) as the employees' table. Then we use a WHERE clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.

SELECT
  emp.employee_id AS employee_id,
  emp.name AS employee_name
FROM employee AS mgr
INNER JOIN employee AS emp
  ON mgr.employee_id = emp.manager_id
WHERE emp.salary > mgr.salary;

If the solution above is confusing, you can find a step-by-step solution here: Employees Earning More Than Managers.

SQL Question 3: What's a foreign key?

A foreign key is a column or group of columns in a table that refers to the primary key in another table. The foreign key constraint helps maintain referential integrity between the two tables.

For example, let's look at the PVH Corp sales database:

pvh_corp_sales:

+------------+------------+------------+------------+ | order_id | product_id | customer_id| quantity | +------------+------------+------------+------------+ | 1 | 222 | 1 | 2 | | 2 | 333 | 1 | 1 | | 3 | 444 | 2 | 3 | | 4 | 555 | 3 | 1 | +------------+------------+------------+------------+

In this table, product_id and customer_id could both be foreign keys. They reference the primary keys of other tables, such as a Products table and a Customers table, respectively. This establishes a relationship between the pvh_corp_sales table and the other tables, such that each row in the sales database corresponds to a specific product and a specific customer.

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SQL Question 4: Calculate the Average Sale Price Per Brand in PVH Corp for a Given Year.

PVH Corp is a global company that owns brands like Tommy Hilfiger, Calvin Klein, Van Heusen, IZOD, and Arrow. As an SQL developer at PVH Corp, you are given a task to write a query that returns the average price of all sold items per brand during the year 2021. Your result should consist of each brand and its corresponding average price in descending order.

Depending on the structure of the database, we'll assume there are two main tables sales and brands.

sales Example Input

brands Table

Your output should be:

Example Output

Answer:

SELECT b.brand_name, AVG(s.sale_price) AS avg_sale_price
FROM sales s
JOIN brands b ON s.brand_id = b.brand_id
WHERE EXTRACT(YEAR FROM s.sale_date) = 2021
GROUP BY b.brand_name
ORDER BY avg_sale_price DESC;

This query joins the sales and brands tables on the brand_id column to allow for brand names to be included in the output. It filters the sales data to include only the sales from the year 2021 using the WHERE clause with the EXTRACT(YEAR FROM s.sale_date) = 2021 condition. Then, for each brand it uses the AVG function to calculate the average sale price. Finally, results are ordered in descending order by the average sale price.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating metrics for specific categories in descending order or this Wayfair Y-on-Y Growth Rate Question which is similar for calculating yearly aggregation values.

SQL Question 5: What are the ACID properties in a DBMS?

A DBMS (database management system), in order to ensure transactions are relaible and don't ruin the integrity of the data, tries to mantain the following ACID properties: Atomicity, Consistency, Isolation, and Durability.

To make this concept more concrete, here is what each of the ACID properties would mean in the context of banking transactions:

• Atomicity: a transaction is either completed fully, or not complete at all. For example, if a customer is transferring money from one account to another, the transaction should either transfer the full amount or none at all.
• Consistency: a transaction will only be completed if it follows all database constraints and checks. For example, if a customer is withdrawing money from an account, the transaction should only be completed if the account has sufficient funds available, otherwise the transaction is rejected
• Isolation: ensures that concurrent transactions are isolated from each other, so that the changes made by one transaction cannot be seen by another transaction. This isolation prevents race conditions, like two customers trying to withdraw money from the same account at the same time.
• Durability: ensures that once a transaction has been committed and completed, the changes are permanent. A reset / shutdown of the database shouldn't erase someone's savings accounts!

SQL Question 6: Click-Through-Rate Analysis for PVH Corp.

PVH Corp., as a global leader in various segments of the apparel industry, makes extensive use of digital marketing. They are analysing the effectiveness of these digital marketing advertisements. In particular, they want to understand the click-through rate that is brought by these ads.

For a given week, the marketing team gathers data on the unique views of an ad (how many unique users saw the ad), and how many of those views resulted in a click (the user clicked on the ad, leading them to the PVH Corp. product website). They want a SQL query to easily determine the click-through rate, calculated as (number of unique clicks / number of unique views) * 100% for each ad.

ad_events Sample data

Answer:

SELECT
    ad_id,
    ROUND(((COUNT(DISTINCT CASE WHEN event='click' THEN user_id END) * 1.0) / COUNT(DISTINCT CASE WHEN event='view' THEN user_id END)) * 100, 2) AS click_through_rate
FROM
    ad_events
GROUP BY
    ad_id;

This query first counts the unique user IDs for each ad where the event was 'click' and 'view'. Then, it calculates the click-through rate by dividing the count of unique 'click' user IDs by the unique 'view' user IDs and multiplying it by 100 to turn it into a percentage. The ROUND function is used to limit the result to two decimal places. The results are grouped by ad_id to provide click-through rates for each ad.

To practice a similar SQL problem on DataLemur's free interactive coding environment, try this SQL interview question asked by Facebook:

SQL Question 7: Can you explain the distinction between cross join and natural join?

A cross join is a type of JOIN operation in SQL that creates a new table by combining each row from the first table with every row from the second table. It is also known as a cartesian join.

For example, say you worked on the Marketing Analytics team at PVH Corp, and needed to understand what advertising copy (text) goes best with what advertising creative (the photo that gets posted with the advertisement copy).

Here is an example of a cross-join between a table of ad_copy and a table of ad_creative:

SELECT ad_copy.copy AS ad_copy, ad_creative.image_url AS ad_creative
FROM ad_copy
CROSS JOIN ad_creative;

A natural join, on the other hand, is a type of JOIN that combines rows from two or more tables based on their common columns. It is called a "natural" join because it is based on the natural relationship that exists between the common columns in the tables being joined.

For an example of each one, say you had sales data exported from PVH Corp's Salesforce CRM stored in a datawarehouse which had two tables: sales and pvh_corp_customers.

An INNER JOIN (which is a type of natural join) combines the two tables on the common customer_id field

SELECT *
FROM sales
INNER JOIN pvh_corp_customers
ON sales.customer_id = pvh_corp_customers.id

This query will return rows from the sales and pvh_corp_customers tables that have matching customer id values. Only rows with matching customer_id values will be included in the results.

One main difference between cross joins and natural joins is that cross joins do not require any common columns between the tables being joined, while natural joins do. Another difference is that cross joins can create very large tables if the input tables have a large number of rows, while natural joins will only return a table with the number of rows equal to the number of matching rows in the input tables.

SQL Question 8: Find Customers From NYC

PVH Corp, a leading fashion and lifestyle company, uses a customers database to store its customer information. They want to keep track of their customer base in New York City for a marketing campaign. Could you write down an SQL query to find all customers whose city is 'New York City' and address contains the word 'Street'?

Here's some sample customer data for the context:

customers Example Input:

Answer:

Here's the SQL query to solve the problem:

SELECT *
FROM customers
WHERE city = 'New York City' AND address LIKE '%Street%';

I used a combination of exact match condition with WHERE city = 'New York City' clause and a LIKE clause WHERE address LIKE '%Street%'. LIKE clause combined with '%Street%' will match any customers whose address contains 'Street'. These customers will be from 'New York City' and whose addresses contain the word 'Street'.

SQL Question 9: Customer Purchases and Product Information Analysis

As a data analyst at PVH Corp, you are tasked with analyzing the company's customer purchase history. Your objective is to create a SQL query that retrieves the list of all the customers along with their respective total spending and the most expensive product they have bought. To accomplish this, you need to join two tables: customers table and products table.

The customers table has the following fields:

• customer_id: The unique ID assigned to each customer.
• customer_name: The name of the customer.
• purchase_id: The IDs of the purchases made by the customer.
• product_id: The IDs of the products bought in each purchase.

The products table has the following fields:

• product_id: The unique ID assigned to each product.
• product_name: The name of the product.
• price: The price of the product.

Answer:

You'd use a SQL query such as the below to solve this:

SELECT c.customer_name, SUM(p.price) AS total_spending, MAX(p.price) AS most_expensive_product
FROM customers c
JOIN products p ON c.product_id = p.product_id
GROUP BY c.customer_id, c.customer_name
ORDER BY total_spending DESC;

This query works by joining the customers and products tables based on the product_id field. It then groups the records by customer_id and customer_name. For each group (which represents a single customer), it sums up the price of the products they bought to find the total spending. It also finds the maximum product price within the group, which gives us the price of the most expensive product they bought. Finally, it orders the results by total spending in descending order.

Since joins come up routinely during SQL interviews, take a stab at this Snapchat SQL Interview question using JOINS:

Also read their "We are PVH" Statement to help you understand the brand even better!

Preparing For The PVH Corp SQL Interview

The key to acing a PVH Corp SQL interview is to practice, practice, and then practice some more! In addition to solving the above PVH Corp SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Microsoft, Google, Amazon, and tech startups.

Each SQL question has multiple hints, step-by-step solutions and crucially, there's an interactive SQL code editor so you can right in the browser run your SQL query answer and have it executed.

To prep for the PVH Corp SQL interview you can also be useful to practice SQL questions from other apparel companies like:

• Levi Strauss SQL questions

• Columbia Sportswear SQL questions

• Skechers SQL questions

• Deckers Outdoor SQL questions

In case your SQL skills are weak, don't worry about going right into solving questions – go learn SQL with this free SQL tutorial.

This tutorial covers things like creating summary stats with GROUP BY and LAG window function – both of which come up routinely in PVH Corp SQL interviews.

PVH Corp Data Science Interview Tips

What Do PVH Corp Data Science Interviews Cover?

In addition to SQL interview questions, the other topics to practice for the PVH Corp Data Science Interview include:

• AB Testing Questions
• Python Pandas or R Coding Questions
• Product Data Science Interview Questions
• Machine Learning and Predictive Modeling Questions
• Behavioral Based Interview Questions

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