8 Performance Food Group SQL Interview Questions (Updated 2024)

Updated on

October 31, 2024

Performance Food Group relies on SQL queries to closely look at sales trends and improve their supply chain, using data patterns specific to the food industry. This hands-on approach helps them see which products are selling quickly and where they need to adjust inventory, which is why Performance Food Group ask SQL questions in interviews for Data Analytics, Data Science, and Data Engineering jobs.

So, to help you prepare, here’s 8 Performance Food Group SQL interview questions – can you answer each one?

Performance Food Group SQL Interview Questions

8 Performance Food Group SQL Interview Questions

SQL Question 1: Identify the Top Customers of Performance Food Group

The Performance Food Group is a broadline food distributor, supplying a range of food products to different customers like restaurants, cafeterias, and others. As a data analyst for Performance Food Group, your task is to identify the 'Whale Users' - the clients that frequently place large orders with the company.

Your job is to write a SQL query that identifies the top 10 customers based on the total quantity of items ordered over the last 1 year.

Create tables and to assist the analysis:

Sample Input:

order_idcustomer_idorder_date
101500107/20/2021
102250111/09/2021
103105403/25/2022
104500105/17/2022
105362507/05/2022

Sample Input:

order_iditem_idquantity
101200100
102150500
102175300
1037525
104200200
10515050

Answer:

The following SQL Query can accomplish the task:


This SQL query performs a JOIN operation between the and tables based on the . It then filters out the orders placed within the last year. The clause groups the total quantity of items ordered by each customer. Finally, the clause along with the keyword sorts the customers in descending order of their ordered item quantities. The at the end ensures that only the top 10 customers are listed.

To work on another SQL customer analytics question where you can solve it interactively and have your SQL code instantly graded, try this Walmart SQL Interview Question:

Walmart SQL Interview Question

SQL Question 2: Top 3 Salaries

Assume there was a table of Performance Food Group employee salary data. Write a SQL query to find the top 3 highest earning employees within each department.

Performance Food Group Example Input:

employee_idnamesalarydepartment_id
1Emma Thompson38001
2Daniel Rodriguez22301
3Olivia Smith20001
4Noah Johnson68002
5Sophia Martinez17501
8William Davis68002
10James Anderson40001

Example Input:

department_iddepartment_name
1Data Analytics
2Data Science

Example Output:

department_namenamesalary
Data AnalyticsJames Anderson4000
Data AnalyticsEmma Thompson3800
Data AnalyticsDaniel Rodriguez2230
Data ScienceNoah Johnson6800
Data ScienceWilliam Davis6800

Check your SQL query for this question interactively on DataLemur:

Top 3 Department Salaries

Answer:

We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.


If the code above is tough, you can find a step-by-step solution with hints here: Top 3 Department Salaries.

SQL Question 3: What do stored procedures do?

Stored procedures in SQL are like recipes in a cookbook. Just like a recipe tells you the ingredients and instructions for making a particular dish, a stored procedure tells the DBMS the logic/statements needed to perform a specific task. Just like you can use a recipe to make the same dish over and over again, you can use a stored procedure to repeat the same task multiple times with different input parameters (which is why stored procedures are so damn useful!).

Say you were a Data Analyst working on a HR analytics project. A common sub-task you might have to do is calculate the average salary for a given department at Performance Food Group, which would be perfect for a stored procedure:


To call this stored procedure and find the average salary for the Data Science department you'd execute a query like this:


Performance Food Group SQL Interview Questions

SQL Question 4: Identify Top Selling Products per Quarter

You are working as a Data Analyst in Performance Food Group. The sales team would like to identify their top-selling products per each quarter year over year to strategize their sales approach. They are interested to know the product_id, total quantity sold, and the rank of each product for each quarter of each year.

Example Input:

order_idproduct_idsale_datequantity
12001230001/15/202250
12002230101/20/2022100
12003230002/01/202280
12004230204/01/2022150
12005230104/10/202290
12006230007/01/202270
12007230107/05/2022110
12008230204/15/202295

Example Output:

yearquarterproduct_idtotal_quantityrank
2022123001301
2022123011002
2022223022451
202222301902
2022323011101
202232300702

Answer:


This query uses the window function . The function is applied over each partition defined by year and quarter, and within each partition, the products are ordered by the total quantity sold in descending order. It individually summarizes each product's total sales quantity for each quarter of each year and assigns a ranking to each product based on the quantity sold within that specific quarter of the year. The output is then sorted by year, quarter, and rank, meaning that for each quarter of each year, you can see the top-selling products with their corresponding sales quantities.

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

SQL Interview Questions on DataLemur

SQL Question 5: What does the keyword do?

The keyword added to a statement can be used to get records without duplicates.

For example, say you had a table of Performance Food Group customers:

namecity
AkashSF
BrittanyNYC
CarlosNYC
DiegoSeattle
EvaSF
FayeSeattle

Suppose you wanted to figure out which cities the customers lived in, but didn't want duplicate results, you could write a query like this:


Your result would be:

city
SF
NYC
Seattle

SQL Question 6: Order Analysis for Performance Food Group

Performance Food Group (PFG) delivers over 150,000 food and related products to customers across the United States. They are interested in analyzing their sales information to better understand their client's behavior. Part of this analysis includes tracking orders for each client and analyzing the frequency and quantities of products bought.

The given tables include and . The table has all the order details including , , and . The table contains specific product details for each order including , , , and .

Please create a SQL query to find out the total value of orders for each customer for the month of June 2022.

Example Input:

order_idorder_datecustomer_id
112206/08/20222001
278406/10/20223002
392007/18/20222001
954007/26/20223002
845107/05/20223002

Example Input:

order_idproduct_idquantityprice
11224001320.00
27844002515.00
39204001220.00
95404003150.00
84514002415.00

Answer:

Given the tables above, the SQL query would look like this:


This query first joins the table with the table by their mutual , then filters by the month and year to focus on June 2022. The function is applied to the product of and to get the total value of orders for that month. Finally, it groups the results by to provide a total value for each customer.

SQL Question 7: What are some similarities and differences between unique and non-unique indexes?

Some similarities between unique and non-unique indexes include:

  1. Both types improve the performance of SQL queries by providing a faster way to lookup the desired data.
  2. Both types use an additional data structure to store the indexed data, which requires additional storage space which impacts write performance.
  3. Both types of indexes can be created on one or more columns of a table.

Some differences between unique and non-unique indexes include:

  1. A unique index enforces the uniqueness of the indexed columns, meaning that no duplicate values are allowed in the indexed columns. A non-unique index allows duplicate values in the indexed columns.
  2. A unique index can be used to enforce the primary key of a table, but a non-unique index cannot.
  3. A unique index can have a maximum of one NULL value in the indexed columns, but a non-unique index can have multiple NULLs

SQL Question 8: Calculate the average cost of products supplied by each vendor

As a Data Analyst at Performance Food Group, you are tasked with gauging the product costs from different vendors to aid pricing and negotiation strategies. Given a table and a table, your task is to find the average cost of products supplied by each vendor.

Example Input:

product_idvendor_idproduct_namecost
001123Apple2.50
002123Orange1.80
003456Cabbage0.59
004456Brocolli1.20
005789Chicken7.00
006789Beef10.00

Example Input:

vendor_idvendor_name
123Fresh Fruits Inc.
456Green Veggies Co.
789All Meat Ltd.

Answer:


This query joins the and tables on . It then computes the average cost of all products by each vendor using the function and the clause. The results are finally sorted by in descending order.

Example Output:

vendor_nameaverage_cost
All Meat Ltd.8.50
Fresh Fruits Inc.2.15
Green Veggies Co.0.89

In the output, each row contains the vendor's name and the average cost of the products they supply. For instance, we can interpret that the average cost of products supplied by "All Meat Ltd." is $8.50.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating cost-related aggregates or this McKinsey 3-Topping Pizzas Question which is similar for aggregating cost based on item composition.

Performance Food Group SQL Interview Tips

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Performance Food Group SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the above Performance Food Group SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Google, Microsoft and Silicon Valley startups.

DataLemur SQL and Data Science Interview Questions

Each DataLemur SQL question has multiple hints, step-by-step solutions and best of all, there is an online SQL coding environment so you can instantly run your query and have it checked.

To prep for the Performance Food Group SQL interview it is also helpful to solve interview questions from other food and facilities companies like:

But if your SQL skills are weak, forget about going right into solving questions – refresh your SQL knowledge with this interactive SQL tutorial.

DataLemur SQL tutorial

This tutorial covers SQL topics like filtering on multiple conditions using AND/OR/NOT and LAG window function – both of which come up routinely in Performance Food Group SQL assessments.

Performance Food Group Data Science Interview Tips

What Do Performance Food Group Data Science Interviews Cover?

Besides SQL interview questions, the other question categories to practice for the Performance Food Group Data Science Interview include:

Performance Food Group Data Scientist

How To Prepare for Performance Food Group Data Science Interviews?

I believe the best way to prepare for Performance Food Group Data Science interviews is to read the book I wrote: Ace the Data Science Interview.

It solves 201 interview questions sourced from tech companies like Google & Microsoft. The book's also got a crash course on Product Analytics, SQL & ML. And finally it's helped a TON of people, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.

Nick Singh author of the book Ace the Data Science Interview

While the book is more technical, it's also key to prepare for the Performance Food Group behavioral interview. A good place to start is by understanding the company's values and mission.

© 2024 DataLemur, Inc

Career Resources

Free 9-Day Data Interview Crash CourseFree SQL Tutorial for Data AnalyticsUltimate SQL Interview GuideAce the Data Job Hunt Video CourseAce the Data Science InterviewBest Books for Data Analysts