10 Hershey SQL Interview Questions (Updated 2024)
At Hershey, SQL is used across the company to analyze sales data, helping them identify customer preferences and tailor their marketing strategies to reach chocolate lovers more effectively. They also rely on SQL to manage supply chain data, ensuring that production and distribution processes are optimized for efficiency so their delicious treats are always available when and where customers want them, this is the reason why Hershey asks SQL problems during interviews for Data Analyst, Data Science, and BI jobs.
To help you study for the Hershey SQL interview, here’s 10 Hershey SQL interview questions – can you solve them?
10 Hershey SQL Interview Questions
SQL Question 1: Identify Power Customers for Hershey
Hershey, a top chocolate producer, wants to identify their "power" customers - those who place the most orders and have the highest overall spending over the past year. They also want to know the total amount of money each power customer has spent. Using the customers and orders tables below, write a SQL query to identify these power customers. The column in the table represents the total amount of the order.
Example Input:
| customer_id | first_name | last_name |
|---|---|---|
| 1 | John | Doe |
| 2 | Jane | Smith |
| 3 | Emily | Jones |
| 4 | Daniel | Davis |
Example Input:
| order_id | customer_id | order_date | order_total |
|---|---|---|---|
| 1 | 1 | 01/01/2021 | 100.00 |
| 2 | 2 | 02/15/2021 | 75.00 |
| 3 | 1 | 03/15/2021 | 120.00 |
| 4 | 3 | 04/30/2021 | 135.00 |
| 5 | 4 | 05/15/2021 | 50.00 |
| 6 | 1 | 06/01/2021 | 90.00 |
| 7 | 2 | 07/15/2021 | 66.00 |
| 8 | 3 | 08/30/2021 | 140.00 |
| 9 | 1 | 09/15/2021 | 150.00 |
Answer:
In this solution, we join the and tables using the field that is common between them. We count the number of orders and sum the total spent for each customer within the past year (2021 here). The results are grouped by and and ordered in descending order for both and . Therefore, customers with more orders and more total spent will appear first, identifying them as Hershey's power customers.
To practice a super-customer analysis question on DataLemur's free online SQL code editor, try this Microsoft SQL Interview problem:
Discover how Hershey is leveraging artificial intelligence to balance data and creativity, enhancing their marketing strategies to connect with consumers more effectively! This approach highlights the importance of innovation in building brand loyalty and adapting to the ever-changing market landscape.
SQL Question 2: Department Salaries
You're given a table of Hershey employee and department salary information. Write a SQL query to find departments where the departments average salary is higher than the company's average salary.
Solve this question interactively on DataLemur:
The solution is LONG – 30+ lines of SQL. You can find a detailed solution with hints here: Department vs. Company Salary.
SQL Question 3: Could you explain what a self-join is?
A self-join is a operation in which a single table is joined to itself. To perform a self-join, you must specify the table name twice in the clause, giving each instance a different alias. You can then join the two instances of the table using a clause, and specify the relationship between the rows in a clause.
Think of using a self-joins whenever your data analysis involves analyzie pairs of the same things, like comparing the salaries of employees within the same department, or identifying pairs of products that are frequently purchased together (which you can do in this real SQL question from a Walmart interview).
For another self-join example, suppose you were conducting an HR analytics project and needed to examine how frequently employees within the same department at Hershey interact with one another, you could use a self-join query like the following to retrieve all pairs of Hershey employees who work in the same department:
This query returns all pairs of Hershey employees who work in the same department, and excludes pairs where the employee's id is the same (since this would represent the same Hershey employee being paired with themselves).
SQL Question 4: Monthly Average Rating
Hershey's would like to keep track of how well each of its products is performing month by month based on customer reviews. Write a SQL query that calculates the average rating for each product for each month.
Assume reviews are stored in a table named . Here's how the data in the table looks like:
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 06/08/2022 | 50001 | 4 |
| 7802 | 265 | 06/15/2022 | 69852 | 4 |
| 5293 | 362 | 06/22/2022 | 50001 | 3 |
| 6352 | 192 | 07/15/2022 | 69852 | 3 |
| 4517 | 981 | 07/22/2022 | 69852 | 2 |
Answer:
The query groups rows by the month part of the and by . For each group, it calculates the average (mean) number of . The results are then ordered first by month, and within each month by product_id.
p.s. Window functions show up super often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: What does the function do, and when would you use it?
The function allows you to select the first non-NULL value from a list of values. It is often used to replace a NULL value with a default value in order to run aggregate functions like or on a column without being affected by values.
For example, if you conducted a customer satisfaction survey for a company and asked customers to rate their level of agreement with a statement on a scale of 1 to 10, some customers may not have answered all the questions, resulting in NULL values in the survey data:
| customer_id | question_id | agree_amount |
|---|---|---|
| 101 | 1 | 9 |
| 101 | 2 | 10 |
| 202 | 1 | 6 |
| 202 | 2 | NULL |
| 303 | 1 | 4 |
| 303 | 2 | NULL |
To replace the NULLs in the column with the default value of 5 which corresponds to neutral on the survey, you could run the following SQL query:
You'd get the following output:
| customer_id | question_id | agree_amount |
|---|---|---|
| 101 | 1 | 9 |
| 101 | 2 | 10 |
| 202 | 1 | 6 |
| 202 | 2 | 5 |
| 303 | 1 | 4 |
| 303 | 2 | 5 |
SQL Question 6: Filter Hershey's Product Sales Data
Given a data table containing a record of product sales from Hershey's, write a SQL query to filter the records to show only those sales where the product sold was 'Chocolate' and the sale occurred in the 'Pennsylvania' state. Assume the table has the following columns: (int), (string), (date), (string), (double).
Example Input:
| sale_id | product_name | sale_date | state | price |
|---|---|---|---|---|
| 1 | Chocolate | 10/25/2022 | New York | 2.25 |
| 2 | Peppermint Patties | 11/15/2022 | Pennsylvania | 1.75 |
| 3 | Chocolate | 11/20/2022 | Pennsylvania | 2.25 |
| 4 | Almond Joy | 10/30/2022 | California | 2.00 |
| 5 | Chocolate | 11/22/2022 | Pennsylvania | 2.25 |
Example Output:
| sale_id | product_name | sale_date | state | price |
|---|---|---|---|---|
| 3 | Chocolate | 11/20/2022 | Pennsylvania | 2.25 |
| 5 | Chocolate | 11/22/2022 | Pennsylvania | 2.25 |
Answer:
This query works by using the command to filter the data in the table. The AND keyword is used to ensure both conditions are met, i.e., has to be 'Chocolate' and the state has to be 'Pennsylvania'. Only the rows satisfying both these conditions are shown in the result.
SQL Question 7: What are the different normal forms (NF)?
Normal forms are guidelines that are used to help design a relational database in a way that minimizes redundancy and ensures the integrity of the data. The 3 most commonly use normal forms are the 1st, 2nd, and 3rd normal forms. Here's a brief explanation of each:
-
1st Normal Form (1NF) is all about keeping it simple - each column should only have one value and there should be no repeating groups of data.
-
2nd Normal Form (2NF) is about organization - your database should already be in 1NF and all the non-key columns should depend on the primary key. This means that each non-key column should be completely dependent on the entire primary key, not just part of it.
-
3rd Normal Form (3NF) is about independence - if your database is already in 2NF, then all the non-key columns should not depend on each other. They should be self-sufficient and not rely on other non-key columns.
SQL Question 8: Find The Monthly Average of Chocolate Sales in Each Product Category
As a data analyst at Hershey, we're interested in finding out the monthly average chocolate sales for each of our product categories to help us optimize our marketing and production strategies. Your database includes two tables: and .
The table has four columns: (integer), (date), (integer), and (integer). Records for every single item sold are entered into this table, with the linking it to the table.
The table has three columns: (integer), (text), and (text). This table contains the details about each of our product.
Write a PostgreSQL query to return a table with three columns: month, product category, and the average quantity of products sold in that product category in that month.
Table:
| sale_id | sale_date | product_id | quantity_sold |
|---|---|---|---|
| 8673 | 01/06/2022 | 10001 | 25 |
| 7804 | 01/06/2022 | 10002 | 30 |
| 6293 | 04/07/2022 | 10001 | 40 |
| 7354 | 04/07/2022 | 10003 | 35 |
| 4517 | 31/07/2022 | 10002 | 50 |
Table:
| product_id | category | product_name |
|---|---|---|
| 10001 | Chocolate bars | Hershey's Milk Chocolate |
| 10002 | Chocolate bars | Hershey's Dark Chocolate |
| 10003 | Cocoa powder | Hershey's Cocoa Powder |
Answer:
This SQL block starts by joining the and tables on the . It groups the result on both the and . Finally, it calculates the average of for each resulting group. This result will give us the average quantity of each category of product sold during each month.
SQL Question 9: Identifying Purchases with Specific Product Names
As a DB admin at Hershey, you receive frequent questions from marketing about the customer's purchase behavior. One day, the marketing team wants to know which customers have a preference for purchasing products containing the word 'Chocolate' in their names from a given 'purchases' table. Could you help them by writing an SQL query to filter out those customer records from a 'purchases' database?
Note: Assume that product names are saved in a column entitled in the table.
Example Input:
| purchase_id | customer_id | purchase_date | product_name | amount |
|---|---|---|---|---|
| 8976 | 190 | 01/01/2023 00:00:00 | Hershey's Milk Chocolate | 50 |
| 7643 | 315 | 01/04/2023 00:00:00 | Hershey's Cookies 'n' Creme | 30 |
| 6432 | 865 | 01/06/2023 00:00:00 | Hershey's Special Dark Chocolate | 40 |
| 9582 | 670 | 01/07/2023 00:00:00 | Skittles Original Fruit | 25 |
| 5036 | 315 | 01/09/2023 00:00:00 | Hershey's Milk Chocolate | 60 |
Example Output:
| customer_id | product_name |
|---|---|
| 190 | Hershey's Milk Chocolate |
| 315 | Hershey's Cookies 'n' Creme |
| 865 | Hershey's Special Dark Chocolate |
| 315 | Hershey's Milk Chocolate |
Answer:
In this query, we used the SQL keyword to filter the customer records from the table. The used with the keyword serves as a wildcard, meaning it will match any string of any length, including an empty string. So this query will return all records where contains the word Chocolate.
SQL Question 10: What's the purpose of the the command?
combines the results from two or more statements, but only returns the rows that are exactly the same between the two sets.
For example, say you were doing an HR Analytics project for Hershey, and had access to Hershey's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables. You could use operator to find all employees who also show up in the contractors table:
Hershey 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. In addition to solving the earlier Hershey SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.
Each interview question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and best of all, there is 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 Hershey SQL interview it is also helpful to solve SQL problems from other food and facilities companies like:
- Seaboard SQL questions
- Molson Coors SQL questions
- Conagra Brands SQL questions
- Hormel Foods SQL questions
However, if your SQL coding skills are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this interactive SQL tutorial.
This tutorial covers topics including CASE/WHEN/ELSE statements and 4 types of JOINS – both of which come up routinely in Hershey interviews.
Hershey Data Science Interview Tips
What Do Hershey Data Science Interviews Cover?
In addition to SQL query questions, the other question categories covered in the Hershey Data Science Interview are:
- Statistics and Probability Questions
- Python or R Coding Questions
- Product Data Science Interview Questions
- Machine Learning Questions
- Behavioral Interview Questions
How To Prepare for Hershey Data Science Interviews?
To prepare for the Hershey Data Science interview make sure you have a deep understanding of the company's culture and values – this will be clutch for acing the behavioral interview. For the technical Data Science interviews, get ready by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG tech companies
- A Refresher on SQL, AB Testing & ML
- Amazing Reviews (1000+ 5-star reviews on Amazon)