8 Becton Dickinson SQL Interview Questions (Updated 2024)
Becton Dickinson employees use SQL to analyze sales trends from transactional data, helping them identify market demands and adjust their strategies accordingly. They also rely on SQL to manage patient data stored in healthcare databases, ensuring that sensitive information is organized and easily accessible for healthcare professionals, this is the reason why Becton Dickinson asks SQL problems in interviews for Data Analyst, Data Science, and BI jobs.
So, to help you prep, we've collected 8 Becton Dickinson SQL interview questions – can you solve them?
8 Becton Dickinson SQL Interview Questions
SQL Question 1: Calculate Monthly Average Ratings of Products
Becton Dickinson is a global medical technology company that is advancing the world of health by improving medical discovery, diagnostics and the delivery of care. It is essential for them to understand the average rating of their products on a monthly basis. Write a SQL query to calculate the average ratings of products each month. The data available is in a table named , with columns , , , , . The column indicates the rating given by the user and it varies from 1 to 5. The column is a timestamp indicating when the review was submitted.
Sample Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 1 | 123 | 2022-01-06 | 101 | 4 |
| 2 | 265 | 2022-01-20 | 102 | 4 |
| 3 | 362 | 2022-02-18 | 101 | 3 |
| 4 | 192 | 2022-02-28 | 102 | 3 |
| 5 | 981 | 2022-03-25 | 102 | 2 |
Answer:
This query first extracts the month from the column using the function. It groups the data by the extracted month and , and calculates the average stars for each group. The part is to round the average to 2 decimal places. The result is then ordered by the month and average stars in descending order.
Example Output:
| month | product_id | avg_stars |
|---|---|---|
| 1 | 101 | 4.00 |
| 1 | 102 | 4.00 |
| 2 | 101 | 3.00 |
| 2 | 102 | 3.00 |
| 3 | 102 | 2.00 |
p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
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SQL Question 2: Department vs. Company Salary
Imagine there was a table of Becton Dickinson employee salary data, along with which department they were in. Write a query to compare the average salary of employees in each department to the company's average salary for March 2024. Return the comparison result as 'higher', 'lower', or 'same' for each department. Display the department ID, payment month (in MM-YYYY format), and the comparison.
Try this interview question and run your code right in DataLemur's online SQL environment:
The solution is LONG – 30+ lines of SQL. You can find a detailed solution here: Department Salaries.
SQL Question 3: When doing database schema design, what's an example of two entities that have a one-to-one relationship? What about one-to-many relationship?
In database schema design, a one-to-one relationship between two entities is where each entity is associated with only one instance of the other entity. For example, the relationship between a car and a license plate is one-to-one, because each car can only have one licensce plate, and each licensce plate belongs to exactly one car.
On the other hand, a one-to-many relationship is where one entity can be associated with multiple instances of the 2nd entity. For example, a teacher can teach multiple classes, but each class is associated with only one teacher.
SQL Question 4: "Calculate the click-through conversion rate for Becton Dickinson's marketing campaign."
Becton Dickinson has launched a new marketing campaign for their medical lab equipment. They want to know how effective their campaign has been at driving sales.
You have been given two tables: that tracks each click on the campaign ad made by a user, and . If a customer clicked on the ad and later made a purchase, their will appear in both tables. Using these tables, write a PostgreSQL query that calculates the click-through conversion rate, defined as the number of users who made a purchase after clicking on the ad divided by the total number of users who clicked the ad.
Example Input:
| click_id | customer_id | click_date |
|---|---|---|
| 1001 | 345 | 07/01/2022 00:00:00 |
| 1002 | 789 | 07/02/2022 00:00:00 |
| 1003 | 123 | 07/03/2022 00:00:00 |
| 1004 | 456 | 07/04/2022 00:00:00 |
| 1005 | 789 | 07/05/2022 00:00:00 |
Example Input:
| sale_id | customer_id | sale_date |
|---|---|---|
| 2001 | 123 | 07/10/2022 00:00:00 |
| 2002 | 789 | 07/11/2022 00:00:00 |
| 2003 | 345 | 07/12/2022 00:00:00 |
| 2004 | 456 | 07/13/2022 00:00:00 |
| 2005 | 789 | 07/15/2022 00:00:00 |
Answer:
This query basically works by joining the two tables on and counts the number of distinct s in both tables. The number of distinct s in the table represents the number of customers who made a purchase after clicking on the ad, and the number of distinct s in the table is the total number of customers who clicked the ad. The division of the two gives us the click-through conversion rate.
To practice a similar SQL problem on DataLemur's free interactive coding environment, solve this Meta SQL interview question:
SQL Question 5: Why are foreign key's important in databases?
A foreign key is a field in a database table that serves as a reference to the primary key of another table, allowing for the creation of a relationship between the two tables.
For a concrete example, let's inspect employee data from Becton Dickinson's HR database:
:
| employee_id | first_name | last_name | manager_id |
|---|---|---|---|
| 1 | Aubrey | Graham | 3 |
| 2 | Marshal | Mathers | 3 |
| 3 | Dwayne | Carter | 4 |
| 4 | Shawn | Carter |
In this table, is the primary key, and is used to uniquely identify each row.
could be a foreign key. It references the of the manager of each employee in the table, establishing a relationship between the employees and their managers. This foreign key allows you to easily query the table to find out who a specific employee's manager is, or to find out which employees report to a specific manager.
It is possible for a table to have multiple foreign keys that reference primary keys in different tables. For instance, the table could have additional foreign keys for the of the department where an employee works and the of the employee's location.
SQL Question 6: Calculating The Average Quality Check Score per Product
Becton Dickinson is a global medical technology company that sells various medical supplies, devices and laboratory equipment. Quality checks are a critical part of their operations to ensure their products meet high standards.
Suppose you are given following two tables: , which contains information about their products, and , which holds the results of quality checks conducted on these products. The "score" in table represents the quality check score out of 10 for a product on a particular check date.
Example Input:
| product_id | product_name |
|---|---|
| 101 | Syringe |
| 102 | Medical Glove |
| 103 | Test Tube |
Example Input:
| check_id | product_id | check_date | score |
|---|---|---|---|
| 1001 | 101 | 2022-06-01 | 8 |
| 1002 | 101 | 2022-06-05 | 9 |
| 1003 | 102 | 2022-06-10 | 7 |
| 1004 | 102 | 2022-06-15 | 8 |
| 1005 | 103 | 2022-06-20 | 6 |
| 1006 | 103 | 2022-06-25 | 7 |
Write a SQL query to calculate the average quality check score for each product for the month of June 2022.
Example Output:
| product_name | avg_score |
|---|---|
| Syringe | 8.50 |
| Medical Glove | 7.50 |
| Test Tube | 6.50 |
Answer:
This query joins the and tables on the field, filters for quality checks done in June 2022, groups by the and then calculates the average score for each product. The function is used to get the first day of the month for each check date, allowing us to filter for a specific month/year.
SQL Question 7: What's the difference between a clustered and non-clustered index?
Clustered and non-clustered indexes are both used to improve query performance, but they differ in how they are implemented.
A clustered index determines the physical order of the data rows in a table, while a non-clustered index does not. As a result, a table can have only one clustered index, but it can have multiple non-clustered indexes.
In terms of query efficiency & performance, a clustered index is generally faster for queries (reads) but updates (writes) to a clustered index are slower, as they require the data rows to be physically rearranged.
SQL Question 8: Locate Customers in Specific Territory
Becton Dickinson, a global medical technology company, has customers all over the world. They categorize their customers by territories so that they can manage customer-bases efficiently. Suppose you have been given a task to find all customers in the territory that contains the string 'Asia'. You are provided with a customer records table as shown below:
Example Input:
| customer_id | first_name | last_name | territory | |
|---|---|---|---|---|
| 1901 | John | Doe | john.doe@example.com | East Asia |
| 2702 | Jane | Smith | jane.smith@example.com | Southeast Asia |
| 3393 | Michael | Johnson | michael.johnson@example.com | South Asia |
| 4252 | Emily | Clark | emily.clark@example.com | North America |
| 5817 | Olivia | Brown | olivia.brown@example.com | West Asia |
Your task is to write a PostgreSQL query to fetch the details of the customers located in any territory which contains 'Asia'.
Answer:
Here's the SQL query in PostgreSQL for this task:
This SQL query will find the customers whose territory contains the string 'Asia'. The "%" symbol is a wildcard character that matches any sequence of characters. By placing '%' before and after 'Asia', it ensures that we search for 'Asia' anywhere within the territory field, hence capturing all customers within any territory containing 'Asia'.
Preparing For The Becton Dickinson SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Becton Dickinson SQL interview is to solve as many practice SQL interview questions as you can! In addition to solving the earlier Becton Dickinson SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Meta, Google and healthcare and pharmaceutical companies like Becton Dickinson.
Each SQL question has hints to guide you, detailed solutions and crucially, there is an interactive SQL code editor so you can instantly run your SQL query answer and have it executed.
To prep for the Becton Dickinson SQL interview you can also be a great idea to solve SQL questions from other healthcare and pharmaceutical companies like:
But if your SQL query skills are weak, forget about diving straight into solving questions – refresh your SQL knowledge with this interactive SQL tutorial.
This tutorial covers SQL concepts such as Self-Joins and window functions – both of these come up frequently during SQL interviews at Becton Dickinson.
Becton Dickinson Data Science Interview Tips
What Do Becton Dickinson Data Science Interviews Cover?
In addition to SQL interview questions, the other topics tested in the Becton Dickinson Data Science Interview are:
- Statistics and AB Testing Questions
- Python Pandas or R Coding Questions
- Business Sense and Product-Sense Questions
- ML Modelling Questions
- Behavioral Based Interview Questions
How To Prepare for Becton Dickinson Data Science Interviews?
I believe the best way to prepare for Becton Dickinson Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
It has 201 interview questions taken from FAANG (FB, Apple, Amazon, Netflix, Google). The book's also got a crash course covering Stats, SQL & ML. And finally it's helped thousands of people land their dream job in data, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.
While the book is more technical, it's also key to prepare for the Becton Dickinson behavioral interview. Start by understanding the company's cultural values.