9 Lamb Weston Holdings SQL Interview Questions (Updated 2024)
At Lamb Weston Holdings, SQL is used to analyze food production data, helping the company identify areas to maximize efficiency and reduce waste in their manufacturing process. They also use SQL to track sales trends, enabling the company to better predict demand and ensure they have the right products in stock when customers need them, that is why Lamb Weston Holdings asks SQL questions during interviews for Data Science, Analytics, and & Data Engineering jobs.
Thus, to help you practice, we've collected 9 Lamb Weston Holdings SQL interview questions – can you solve them?
9 Lamb Weston Holdings SQL Interview Questions
SQL Question 1: Analyzing Monthly Sales
As a Data Analyst at Lamb Weston Holdings, you are asked to analyze the monthly sales of different product categories. The data is stored in the table where each row represents a sale. Each sale has a unique , indicating when the sale occurred, indicating the product category sold, and .
Please write a SQL query that shows the total units sold of each product category for each month. In addition, compute the difference in total units sold from the previous month for each product category.
Example Input:
| sale_id | sales_date | product_category | units_sold |
|---|---|---|---|
| 3927 | 03/31/2022 | Fries | 200 |
| 1827 | 03/31/2022 | Hash Browns | 100 |
| 5746 | 04/01/2022 | Hash Browns | 150 |
| 3838 | 04/01/2022 | Fries | 300 |
| 7392 | 04/02/2022 | Fries | 200 |
| 1964 | 04/02/2022 | Hash Browns | 120 |
Example Output:
| mth | product_category | total_units_sold | units_sold_difference |
|---|---|---|---|
| 3 | Fries | 200 | null |
| 3 | Hash Browns | 100 | null |
| 4 | Fries | 500 | 300 |
| 4 | Hash Browns | 270 | 170 |
Answer:
This PostgreSQL query utilizes window functions to calculate the cumulative sum of units sold by product category by month, as well as the month-over-month unit sold difference. By using the clause with the window function, the function operates on a subset of rows related to the current row. The clause within the window function defines the order in which the rows will be arranged before the function is applied. The function is used to access data from a previous row in the same result set without the need for a self-join.
To practice a related window function SQL problem on DataLemur's free interactive coding environment, solve this Amazon SQL Interview Question:
Explore Lamb Weston Holdings' newsroom to uncover the latest innovations and trends in the frozen food industry! Understanding their advancements can provide valuable insights into how they are shaping the market and meeting consumer needs.
SQL Question 2: Employees Earning More Than Their Boss
Suppose you had a table of Lamb Weston Holdings employee salary data. Write a SQL query to find the employees who earn more than their direct manager.
Lamb Weston Holdings Example Input:
| employee_id | name | salary | department_id | manager_id |
|---|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 | |
| 2 | Daniel Rodriguez | 2230 | 1 | 10 |
| 3 | Olivia Smith | 8000 | 1 | 8 |
| 4 | Noah Johnson | 6800 | 2 | 8 |
| 5 | Sophia Martinez | 1750 | 1 | 10 |
| 8 | William Davis | 7000 | 2 | NULL |
| 10 | James Anderson | 4000 | 1 | NULL |
Example Output:
| employee_id | employee_name |
|---|---|
| 3 | Olivia Smith |
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 and run your code right in DataLemur's online SQL environment:
Answer:
First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.
If the code above is tough, you can find a detailed solution here: Employee Salaries Higher Than Their Manager.
SQL Question 3: How can you determine which records in one table are not present in another?
To locate records in one table that are absent from another, you can use a and then look for values in the right-side table.
For example, say you exported Lamb Weston Holdings's CRM (Customer Relationship Management) database, and had a table of sales leads, and a second table of companies.
Here's an example of how a query can find all sales leads that are not associated with a company:
This query returns all rows from the sales leads table, along with any matching rows from the companies table. If there is no matching row in the companies table, values will be returned for all of the right table's columns. The clause then filters out any rows where the column is , leaving only sales leads that are NOT associated with a company.
SQL Question 4: Identify New Customers with Large Orders
As a data analyst at Lamb Weston Holdings, a company that specializes in frozen potato products, it is your task to identify new customers who made significant purchases last quarter. Specifically, you are asked to filter the customer records to find all customers who made their first purchases in the last quarter and whose total purchase volume in their first month of purchase was more than 100 units. Include the customers' contact information and the total volume of their first month's purchase.
Assume you have access to two tables - and .
Example Input:
| order_id | customer_id | order_date | product_id | quantity |
|---|---|---|---|---|
| 6578 | 324 | 2022-07-02 | 2001 | 60 |
| 9867 | 324 | 2022-07-15 | 2002 | 80 |
| 3412 | 488 | 2022-05-31 | 2001 | 70 |
| 3453 | 488 | 2022-06-01 | 2002 | 50 |
| 5687 | 658 | 2022-03-05 | 2001 | 90 |
| 4213 | 658 | 2022-03-20 | 2002 | 20 |
Example Input:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 324 | John | Doe | john.doe@example.com |
| 488 | Jane | Smith | jane.smith@example.com |
| 658 | Bill | Jones | bill.jones@example.com |
Answer:
This query first identifies the customers who made their first orders in the 3rd quarter of 2022. For these customers, the query calculates the total quantity of their first month's purchases. The query then filters out any customers whose total purchase quantity in their first month was 100 or lower. The final output includes the customer's id, name, email, and total quantity of their first month's purchase.
SQL Question 5: How does a left join differ from a right join?
Both types of joins in SQL help you retrieve data from multiple tables and merge the results into a single table.
To demonstrate the difference between a left join versus a right join, imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.
A retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.
A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.
SQL Question 6: Click-through Conversion Rate for Lamb Weston's Digital Products
Assume that Lamb Weston Holdings, a global leader in potato technology, has a website where customers can view and add potato products to their cart. A frequently used KPI is the click-through conversion rate, which tracks the ratio of customers who added a product to their cart after viewing it. The task is to calculate the monthly click-through conversion rate.
Given two tables: and
Example Input:
| view_id | user_id | view_date | product_id |
|---|---|---|---|
| 101 | 1 | 06/01/2022 12:00:00 | 50001 |
| 102 | 2 | 06/06/2022 14:00:00 | 50002 |
| 103 | 3 | 06/20/2022 18:00:00 | 50003 |
| 104 | 4 | 07/01/2022 09:00:00 | 50001 |
| 105 | 1 | 07/05/2022 11:00:00 | 50002 |
Example Input:
| cart_id | user_id | cart_date | product_id |
|---|---|---|---|
| 201 | 1 | 06/02/2022 15:00:00 | 50001 |
| 202 | 2 | 06/07/2022 09:00:00 | 50002 |
| 203 | 3 | 06/20/2022 21:00:00 | 50003 |
| 204 | 5 | 07/02/2022 16:00:00 | 50001 |
Answer:
Here is a PostgreSQL query that can solve the given task:
This query works by first calculating the number of distinct views and add to carts on a monthly basis for each product. Then it joins these two CTEs (Common Table Expressions) on month and product_id. By dividing the number of carts by the number of views, we get the click-through conversion rate for each product on a monthly basis. Note that we cast num_carts to float to allow for decimal division.
To practice another question about calculating rates, try this TikTok SQL question within DataLemur's interactive SQL code editor:
SQL Question 7: How would you go about optimizing a slow SQL query?
There's several steps you can take to troubleshoot a slow SQL query.
First things first, figure out why the query is slow! You can use and commands in PostgreSQL to identify any performance bottlenecks. After that, you can start changing your query, depending on what the source of the query performance issue is.
Generally, indexes can help speed up queries. Also de-normalizing your tables might help, to remove slow joins.
Lastly, you could always just upgrade your hardware! Time and money wasted improving query performance could just be better spent on mroe powerful database servers!
While this is a very surface-level approach to optimizing SQL query performance, it should do the trick for Data Analyst interviews and Data Science interviews at Lamb Weston Holdings. Data Engineers should know a bit more about the and before the interview.
SQL Question 8: Finding Specific Customers in the Database
Lamb Weston Holdings is looking to target some of their marketing efforts towards a specific pool of customers. They've noted that customers with email addresses containing 'potato' seem to be significantly engaged with their products. They've asked you to retrieve all fields from the customer table for customers whose email addresses contain 'potato'.
Sample Input:
:
| customer_id | first_name | last_name | date_of_birth | country | |
|---|---|---|---|---|---|
| 1 | John | Doe | johndoe@gmail.com | 1985-05-16 | USA |
| 2 | Jane | Smith | janesmith@mail.com | 1970-12-03 | USA |
| 3 | Tom | Blanco | tom.potato@mail.com | 1999-01-10 | Canada |
| 4 | Maria | Rodriguez | mariarod@gmail.com | 1988-07-14 | Spain |
| 5 | Emily | Potato | emilylovespotatoes@gmail.com | 1990-09-20 | USA |
Answer:
This query uses the LIKE keyword in SQL to filter down the customer records. The "%" symbol serves as a wildcard that can match any sequence of characters. Thus, '%potato%' will match all strings that contain 'potato' anywhere in them.
SQL Question 9: Calculating Overall Production Efficiency
As a database manager at Lamb Weston Holdings, a large producer of frozen potato products, one of your tasks involves reviewing and assessing production data. For a given year, you're asked to calculate the efficiency of each plant, which is determined by taking the absolute difference of the target and actual production, dividing it by the target, and then rounding the result to two decimal places. You also need to calculate the total power used per plant and find the square root of this data.
Use the tables and to perform these operations.
Example Input:
| production_id | plant_id | year | target_production | actual_production |
|---|---|---|---|---|
| 101 | 1 | 2021 | 10000 | 9500 |
| 102 | 2 | 2021 | 15000 | 15500 |
| 103 | 3 | 2021 | 20000 | 19800 |
| 104 | 1 | 2022 | 10500 | 10700 |
| 105 | 2 | 2022 | 15200 | 15400 |
Example Input:
| usage_id | plant_id | year | total_power |
|---|---|---|---|
| 201 | 1 | 2021 | 1200 |
| 202 | 2 | 2021 | 1600 |
| 203 | 3 | 2021 | 2000 |
| 204 | 1 | 2022 | 1300 |
| 205 | 2 | 2022 | 1600 |
Answer:
This query first joins the and tables on and . It then calculates the by taking the absolute difference between and , dividing that by , and using the ROUND() function to limit it to two decimal places. The POWER() function is also used to calculate the square root of the used per plant for each year.
To practice a very similar question try this interactive Snapchat Sending vs. Opening Snaps Question which is similar for calculating percentages and rounding them to decimal places or this Alibaba Compressed Mean Question which is similar for calculation on production data.
Lamb Weston Holdings SQL Interview Tips
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews. Besides solving the above Lamb Weston Holdings SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Google, Microsoft and Silicon Valley startups.
Each SQL question has multiple hints, detailed solutions and most importantly, there's an online SQL coding environment so you can instantly run your SQL query answer and have it checked.
To prep for the Lamb Weston Holdings SQL interview it is also helpful to solve interview questions from other food and facilities companies like:
- Flowers Foods SQL questions
- TreeHouse Foods SQL questions
- Darling Ingredients SQL questions
- Sanderson Farms SQL questions
But if your SQL skills are weak, don't worry about going right into solving questions – improve your SQL foundations with this free SQL for Data Analytics course.
This tutorial covers SQL concepts such as math functions like ROUND()/CEIL() and LAG window function – both of these come up frequently in Lamb Weston Holdings SQL interviews.
Lamb Weston Holdings Data Science Interview Tips
What Do Lamb Weston Holdings Data Science Interviews Cover?
Beyond writing SQL queries, the other types of questions tested in the Lamb Weston Holdings Data Science Interview are:
- AB Testing Questions
- Coding Questions in Python or R
- Product Data Science Interview Questions
- ML Interview Questions
- Behavioral & Resume-Based Questions
How To Prepare for Lamb Weston Holdings Data Science Interviews?
To prepare for the Lamb Weston Holdings Data Science interview have a deep understanding of the company's cultural values – this will be important for acing the behavioral interview. For technical interviews prepare by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from Facebook, Google & startups
- A Crash Course covering SQL, Product-Sense & ML
- Great Reviews (1000+ reviews, 4.5-star rating)