9 Henry Schein SQL Interview Questions (Updated 2024)
At Henry Schein, SQL is essential for analyzing dental product sales data, helping them understand market trends and customer preferences. They also use SQL for predicting inventory needs based on these purchasing patterns, allowing them to maintain efficient stock levels and meet customer demand, that is why Henry Schein asks SQL questions during interviews for Data Science, Data Engineering, and Data Analytics jobs.
So, to help you ace the Henry Schein SQL interview, here’s 9 Henry Schein SQL interview questions in this article.
9 Henry Schein SQL Interview Questions
SQL Question 1: Calculate the average monthly sales by product
Henry Schein, which is a multinational healthcare product and service provider, wants to analyze their sales data to understand the overall performance of their products. Specifically, they want to calculate the average monthly sales for each product.
Given a table with , , , and columns, write a SQL query to calculate the average monthly sales by product.
Example Input:
| order_id | product_id | order_date | quantity_sold |
|---|---|---|---|
| 1001 | 2000 | 2022-02-01 | 50 |
| 1002 | 2000 | 2022-02-15 | 120 |
| 1003 | 3000 | 2022-02-20 | 80 |
| 1004 | 2000 | 2022-03-01 | 70 |
| 1005 | 3000 | 2022-03-15 | 60 |
| 1006 | 2000 | 2022-03-30 | 50 |
| 1007 | 3000 | 2022-04-01 | 90 |
Example Output:
| mth | product_id | avg_sales |
|---|---|---|
| 2 | 2000 | 85.0 |
| 3 | 2000 | 60.0 |
| 2 | 3000 | 80.0 |
| 3 | 3000 | 60.0 |
| 4 | 3000 | 90.0 |
Answer:
This query calculates average sales per month for each product. The query first extracts the month from the , groups data by the and the extracted month, and applies the average function to . The result is sorted by and . The clause with are window functions that perform the calculation across the set of rows related to the current row.
p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur
Dive into Henry Schein's dental technology offerings to see how they are revolutionizing the dental industry with innovative solutions! Learning about their advancements can give you a better understanding of how technology is enhancing dental practices and patient experiences.
SQL Question 2: 2nd Highest Salary
Imagine you had a table of Henry Schein employee salary data. Write a SQL query to find the 2nd highest salary at the company.
Henry Schein Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
Check your SQL query for this interview question and run your code right in DataLemur's online SQL environment:
Answer:
You can find a detailed solution with hints here: 2nd Highest Salary.
SQL Question 3: Can you explain the concept of a constraint in SQL?
Constraints are just rules your DBMS has to follow when updating/inserting/deleting data.
Say you had a table of Henry Schein products and a table of Henry Schein customers. Here's some example SQL constraints you'd use:
NOT NULL: This constraint could be used to ensure that certain columns in the product and customer tables, such as the product name and customer email address, cannot contain NULL values.
UNIQUE: This constraint could be used to ensure that the product IDs and customer IDs are unique. This would prevent duplicate entries in the respective tables.
PRIMARY KEY: This constraint could be used to combine the and constraints to create a primary key for each table. The product ID or customer ID could serve as the primary key.
FOREIGN KEY: This constraint could be used to establish relationships between the Henry Schein product and customer tables. For example, you could use a foreign key to link the customer ID in the customer table to the customer ID in the product table to track which products each customer has purchased.
CHECK: This constraint could be used to ensure that certain data meets specific conditions. For example, you could use a constraint to ensure that Henry Schein product prices are always positive numbers.
DEFAULT: This constraint could be used to specify default values for certain columns. For example, you could use a constraint to set the customer registration date to the current date if no value is provided when a new customer is added to the database.
SQL Question 4: Managing Inventory for Henry Schein
Henry Schein is a leading provider of healthcare products and services. As a Database Administrator at Henry Schein, you are tasked with managing the company's inventory more efficiently. Your main focus is on identifying the products with the highest demand based on quantity sold, from which you can advise the procurement team for better inventory planning.
To do this, you have two tables, and , with the following information:
Example Input:
| prod_id | prod_name | price |
|---|---|---|
| 101 | Dental Floss | 2.50 |
| 102 | Mouthwash | 3.75 |
| 103 | Toothbrush | 1.25 |
Example Input:
| sale_id | prod_id | sale_date | quantity |
|---|---|---|---|
| 2001 | 101 | 06/12/2022 00:00:00 | 50 |
| 2002 | 102 | 06/12/2022 00:00:00 | 30 |
| 2003 | 103 | 06/13/2022 00:00:00 | 75 |
| 2004 | 101 | 06/14/2022 00:00:00 | 40 |
| 2005 | 102 | 06/14/2022 00:00:00 | 25 |
Write a SQL query that returns the total quantity sold for each product for the month of June 2022, ordered by quantity in descending order.
Answer:
This query joins the and tables on the column. It then filters records for the month of June 2022. The clause aggregates data by , and the function calculates total quantities sold. The clause sorts results in descending order by .
SQL Question 5: What are the various forms of normalization?
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 6: Filter customer records by multiple conditions
As a data analyst at Henry Schein, you have been tasked to write a SQL query to ascertain which customers, based on their order history, are eligible for a special discount offer. These customers must meet the following conditions:
- They must be from the "USA"
- They must have made orders of a total amount of at least $1000
- Their last order must be within the last 3 months
Using the and tables provided below, write a SQL statement to retrieve these customer's names, country, total order amount, and the date of their last order.
Example Input:
| customer_id | name | country |
|---|---|---|
| 1 | John Doe | USA |
| 2 | Jane Doe | USA |
| 3 | Steve Smith | Canada |
| 4 | Sara Williams | USA |
| 5 | David Johnson | UK |
Example Input:
| order_id | customer_id | order_amount | order_date |
|---|---|---|---|
| 101 | 1 | 500 | 2023-01-12 |
| 102 | 2 | 800 | 2023-02-16 |
| 103 | 3 | 1200 | 2023-03-11 |
| 104 | 1 | 600 | 2023-03-18 |
| 105 | 4 | 1200 | 2023-04-06 |
| 106 | 2 | 500 | 2023-04-14 |
| 107 | 5 | 1500 | 2023-05-23 |
Answer:
This query first joins the and tables on , then filters for customers who are from the USA. It then groups the remaining results by , and uses the clause to impose conditions on the group, in this case, the sum of the order amount must be at least $1000 and the latest order must have occurred in the last 3 months. The result is a list of eligible customers' names, country, total order amount, and the date of their last order.
SQL Question 7: What are the various types of joins used in SQL?
Joins in SQL allow you to combine data from different tables based on a shared key or set of keys.
Four JOIN types are available in SQL. For an example of each one, say you had sales data exported from Henry Schein's Salesforce CRM stored in a PostgreSQL database, and had access to two tables: and .
- : retrieves rows from both tables where there is a match in the shared key or keys. For example, an between the table and the table would retrieve only the rows where the in the table matches the in the table.
- : retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the table). If there is no match in the right table, NULL values will be returned for the right table's columns.
- : retrieves all rows from the right table (in this case, the table) and any matching rows from the left table (the table). If there is no match in the left table, NULL values will be returned for the left table's columns.
- : retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, NULL values will be returned for the columns of the non-matching table.
SQL Question 8: Analyze Customer Purchase History and Product Inventory
Henry Schein, a company that primarily distributes medical and dental supplies, wants to have a better understanding of their customer's purchase patterns. They need a SQL query that can produce the following information:
- The total purchases by each customer.
- Their most purchased product.
- The current stock level of their most purchased product.
Please assume we have two tables: and .
contains customer ID, product ID, and quantity. stores product ID, description, and quantity in stock. Here is the example of data:
Example Input:
| purchase_id | customer_id | product_id | quantity |
|---|---|---|---|
| 1 | 1001 | 2001 | 20 |
| 2 | 1001 | 2002 | 10 |
| 3 | 1001 | 2001 | 25 |
| 4 | 1002 | 2001 | 30 |
| 5 | 1002 | 2002 | 20 |
Example Input:
| product_id | description | in_stock |
|---|---|---|
| 2001 | Medical Supplies | 100 |
| 2002 | Dental Supplies | 50 |
We want to produce a report like the following:
Example Output:
| customer_id | total_purchases | most_purchased_product | product_in_stock |
|---|---|---|---|
| 1001 | 55 | Medical Supplies | 100 |
| 1002 | 50 | Medical Supplies | 100 |
Answer:
Here's a PostgreSQL query to solve the problem:
This Postgres query first aggregates the total purchases of each product by each customer. It then uses a window function to rank the products by the total quantity purchased for each customer. The highest rank (1) is given to the product with the most quantity purchased. Finally, it joins this information with the inventory table to get the product description and the current stock level of the most purchased product by each customer.
Because join questions come up routinely during SQL interviews, take a stab at this Snapchat JOIN SQL interview question:
SQL Question 9: Calculate Average Sales Per Month for Each Product Type
Henry Schein wants to calculate average sales per month for different categories or types of products. They also want to apply certain arithmetic operations on the dataset. For example:
- Calculate the absolute difference between the count of different months' sales.
- Round the average sales up to the next whole number.
- Use the power function to calculate the square of the count of items sold.
- Calculate the modulo of the total sales count.
Example Input:
| sales_id | product_type | sales_date | product_id | quantity |
|---|---|---|---|---|
| 4112 | Dental | 01/15/2022 00:00:00 | 10089 | 20 |
| 2125 | Diagnostic | 05/23/2022 00:00:00 | 20356 | 50 |
| 7896 | Dental | 02/17/2022 00:00:00 | 10089 | 30 |
| 9023 | Vaccine | 05/29/2022 00:00:00 | 45612 | 10 |
| 5369 | Diagnostic | 03/30/2022 00:00:00 | 20356 | 40 |
Answer:
In the above query:
- We first extract the month part from the sales_date and group by product_type and month.
- We then calculate the average quantity of products sold each month per product type and round to the nearest whole number.
- We calculate the absolute difference in count from the previous month for the sales count by using the , and functions.
- We calculate the square value of the product count using the function.
- We also calculate the modulo of the total sales count using the modulus (%) operator.
To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating the year-on-year growth rate in sales, or this Amazon Average Review Ratings Question which is similar for calculating the average review rating for each product per month.
Henry Schein SQL Interview Tips
The best way to prepare for a Henry Schein SQL interview is to practice, practice, practice. In addition to solving the above Henry Schein SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Netflix, Google, and Amazon.
Each exercise has multiple hints, fully explained answers along with a discussion board to see how others solved it and crucially, there's an interactive SQL code editor so you can easily right in the browser your SQL query and have it checked.
To prep for the Henry Schein SQL interview you can also be wise to practice interview questions from other healthcare and pharmaceutical companies like:
- Universal Health Services SQL questions
- Baxter International SQL questions
- IQVIA SQL questions
- Regeneron SQL questions
But if your SQL coding skills are weak, forget about diving straight into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.
This tutorial covers SQL topics like math functions like CEIL()/FLOOR() and using ORDER BY – both of which show up routinely during Henry Schein SQL assessments.
Henry Schein Data Science Interview Tips
What Do Henry Schein Data Science Interviews Cover?
Beyond writing SQL queries, the other types of problems tested in the Henry Schein Data Science Interview include:
- Statistics and Probability Questions
- Python or R Coding Questions
- Product Data Science Interview Questions
- ML Modelling Questions
- Behavioral Questions based on Henry Schein cultural values
How To Prepare for Henry Schein Data Science Interviews?
To prepare for Henry Schein Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from Facebook, Google, & Amazon
- a crash course covering Stats, ML, & Data Case Studies
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Also focus on the behavioral interview – prep for it using this Behavioral Interview Guide for Data Scientists.