9 Campbell Soup SQL Interview Questions (Updated 2024)

Campbell Soup employees use SQL to dive deep into sales data from various regions, helping them spot trends and understand what products will be in demand in the future. It also helps them predict future demands, ensuring they have the right amount of inventory ready to satisfy customer cravings, this is the reason why Campbell Soup tests SQL problems in interviews for Data Science, Data Engineering, and Data Analytics jobs.

Thus, to help you prep, here’s 9 Campbell Soup SQL interview questions – how many can you solve?

9 Campbell Soup SQL Interview Questions

SQL Question 1: Finding the Campbell Soup "Whale Users"

Assume the Campbell Soup Company wants to identify its "whale users", basically the customers who frequently purchase a large quantity of their products. The requirements to be a "whale user" are purchasing at least 1000 cans of soup a month for at least 3 different months.

You have access to the table where every row represents a purchase of multiple cans of soup made by a customer. The table columns are: , , and .

Write a SQL query to find the customer_ids of "whale users" and the corresponding months where they achieved "whale" status.

Example Input:

Example Output:

Answer:

You can use a combination of PostgreSQL function to extract the Month & Year from and clause to get the total quantity by customer by month. Then use the clause to filter out those where the quantity is at least 1000.

Here's a PostgreSQL query for the problem:

In the output, represents the ID of the "whale user", 'month' is the month when the customer achieved the "whale" status. In our sample data, customer 100 achieved "whale" status in June and July, and customer 102 in June and August.

To solve a related super-user data analysis question on DataLemur's free online SQL coding environment, try this recently asked Microsoft SQL interview question:

Visit Campbell Soup's newsroom to catch up on their latest news and innovations in the food industry! Understanding Campbell's initiatives can give you a better perspective on how established brands are evolving to meet the needs of today's consumers.

SQL Question 2: Department vs. Company Salary

You're given a table of Campbell Soup employee and department salaries. Write a SQL query to find departments where the departments average salary is higher than the company's average salary.

Write a SQL query for this interview question directly within the browser on DataLemur:

The solution is LONG – 30+ lines of SQL. You can find a step-by-step solution here: Department vs. Company Salary.

SQL Question 3: What is the difference between a correlated subquery and non-correlated subquery?

A non-correlated sub-query is not linked to the outer query and can be run on its own. It does not reference any columns from the outer query and is used to retrieve additional data for the outer query. On the other hand, a correlated sub-query is one that relies on the outer query and cannot be run independently. It uses the outer query to filter or transform data by referencing a column from it, while the outer query uses the results of the inner query.

Here is an example of a non-correlated sub-query:

The sub-query in this case is non-correlated, as it does not reference any columns from the outer query.

Here is an example of a correlated sub-query:

This query selects the and total sales of all Campbell Soup customers in the sales table whose are greater than the average of their own customer group. The sub-query in this case is correlated with the outer query, as it references the column from the outer query ().

Non-correlated sub-queries are typically faster, as they only have to be executed once, wheareas correlated sub-queries are slower since they have to be re-evaluated for each row of the outer query.

SQL Question 4: Sales Analysis with Window Functions

As a data analyst at Campbell Soup, you have two datasets before you: which contains the sales data and which represents the product catalog. Write a SQL query that will return the average weekly sales for each product from the table. Rank these average weekly sales within each product's category to determine the product with the highest average weekly sales in its category.

Example Input:

Example Input:

Example Output:

Answer:

This query calculates the average weekly sales for each product by using the window function partitioned by and week start date. It then assigns a rank within each product's category based on the average weekly sales using the window function. The output reveals the product with the highest average weekly sales in its respective category.

To solve another window function question on DataLemur's free interactive SQL code editor, try this Google SQL Interview Question:

SQL Question 5: How do the and window functions differ from each other?

While both and are used to rank rows, the key difference is in how they deal with ties.

RANK(): When there's a tie, leaves a gap in the ranking. For example, if three rows are tied for 2nd place, the function will assign a rank of 2 to the first of these rows, a rank of 3 to the 2nd row in the tie, and a rank of 4 to the the 3rd tie.

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.

Suppose we had data on how many deals different salespeople at Campbell Soup:

To rank these salespeople, we could execute the following query:

The result of this query would be:

As you can see, the function assigns a rank of 1 to the first row (Akash), a rank of 2 to the second row (Brittany), and so on. In contrast, the , gives both Akash and Brittany a rank of 1, since they are tied, then moves on to rank 2 for Carlos.

SQL Question 6: Soup Production & Sales Tracking

As a Data analyst at Campbell Soup company, you are tasked with designing a database scheme to keep track of various soup products, their production units, sales units, and raw materials required to produce each product.

Every soup product at Campbell Soup company can be identified by a , and has other associated attributes such as , , and .

Campbell Soup company keeps track of the raw materials required for each product — this information includes , , .

Both production and sales units are recorded with corresponding dates and the quantity of units produced or sold.

Create a database schema and relevant tables necessary to store this data and ensure referential integrity.

Here is some sample data:

Example Input:

Example Input:

Example Input:

Example Input:

Consider the data available is till 06/13/2022. Write a PostgreSQL query to find the remaining inventory for each product.

Answer:

Here's a possible solution to the problem. First calculate total units produced and sold for each product, then subtract total units sold from total units produced to find remaining inventory.

In this answer, with the use of , we calculate sum of and for each from the and tables respectively. Then, in the main query, we subtract the total units sold from the total units produced for each product to get the remaining inventory. The function is used to handle values if a product does not exist in the or table.

SQL Question 7: In SQL, are NULLs treated the same as zero's and blank spaces?

A NULL value represents a missing or unknown value. It is different from a zero or a blank space, which are actual values. It is important to handle NULL values properly in SQL because they can cause unexpected results if not treated correctly.

SQL Question 8: Filtering Customers Purchasing a Specific Soup Type

Campbell Soup is interested in better understanding the purchasing habits of its customers. Specifically, they want to find out customers who purchased "Tomato Soup" in the United States during the Summer months (June, July, August). You are tasked to write a SQL query to filter down the customer records database to only show customers who meet this criteria.

Example Input:

Example Input:

Answer:

This query joins and tables on . It only selects records where the product is 'Tomato Soup', the country is 'USA', and the purchase month is between June and August. The condition is used to limit the records to the Summer months.

The output of this query will be a table with two columns, and , containing only the customers who meet the given conditions.

SQL Question 9: Average Monthly Sales per Soup Flavor

As a data analyst for Campbell Soup, you are tasked with the responsibility of tracking product performance. Your manager has requested for a report showing the average monthly sales for each soup flavor. Use the sales database which consists of a table with the following columns:

:

:

From this and table, write a SQL query to generate a summary showing the average monthly quantity sold per soup flavor.

Expected Output:

Answer:

This query will extract the month from each sale date and group them by month and product name. Then, it will calculate the average quantity of products sold for each combination of month and product. This gives us the monthly average quantity sold for each soup flavor.

Preparing For The Campbell Soup SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Campbell Soup SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the earlier Campbell Soup SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Netflix, Google, and Amazon.

Each interview question has hints to guide you, detailed solutions and crucially, there's an online SQL code editor so you can easily right in the browser your SQL query and have it checked.

To prep for the Campbell Soup SQL interview you can also be wise to practice SQL problems from other food and facilities companies like:

• Constellation Brands SQL questions
• Hershey SQL questions
• Seaboard SQL questions
• Molson Coors SQL questions

But if your SQL query skills are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.

This tutorial covers topics including LEAD/LAG window functions and aggregate functions like SUM()/COUNT()/AVG() – both of these come up often during SQL interviews at Campbell Soup.

Campbell Soup Data Science Interview Tips

What Do Campbell Soup Data Science Interviews Cover?

In addition to SQL query questions, the other types of problems tested in the Campbell Soup Data Science Interview include:

• Experimental Design & AB Testing Questions
• Coding Questions in Python or R
• Product Data Science Interview Questions
• ML Modelling Questions
• Behavioral Interview Questions focussed on Campbell Soup values & principles

How To Prepare for Campbell Soup Data Science Interviews?

To prepare for Campbell Soup Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions taken from Microsoft, Amazon & startups
• a refresher covering Product Analytics, SQL & ML
• over 1000+ reviews on Amazon & 4.5-star rating

Also focus on the behavioral interview – prepare for it with this list of common Data Scientist behavioral interview questions.