8 Catalent SQL Interview Questions (Updated 2024)
Data Analysts & Data Scientists at Catalent use SQL queries to analyze patient data from clinical trials, helping to identify trends and improve treatment protocols. They also rely on SQL to manage the supply chain of pharmaceutical products, ensuring that inventory levels align with production schedules and patient needs, which is why Catalent asks SQL problems during interviews.
To help you prepare for the Catalent SQL interview, here’s 8 Catalent SQL interview questions – scroll down to start solving them!
8 Catalent SQL Interview Questions
SQL Question 1: Identifying Power Users from Purchase History
As a database analyst at Catalent, a leading provider of pharmaceutical delivery technologies and solutions, one of your tasks is to identify the power users, who are customers who make frequent purchases. Here are two tables, and . The table contains user data, including the (a unique identifier for each user) and the (the date the user first became a customer). The table contains purchase data, including the (a unique identifier for each purchase), (the customer who made the purchase), (the product purchased), and .
For this task, write a SQL query to identify power users who have made more than 10 purchases within their first month of becoming a customer.
example input:
| user_id | created_at |
|---|---|
| 1 | 2020-02-01 |
| 2 | 2021-06-15 |
| 3 | 2021-11-01 |
example input:
| purchase_id | user_id | product_id | purchase_date |
|---|---|---|---|
| 101 | 1 | 201 | 2020-02-15 |
| 102 | 1 | 202 | 2020-02-22 |
| 103 | 2 | 203 | 2021-06-25 |
| 104 | 1 | 204 | 2020-02-28 |
| 105 | 3 | 205 | 2021-11-20 |
| 106 | 3 | 206 | 2021-11-23 |
Answer:
This query first joins the and tables on the field. It then restricts the selection to purchases made within one month of the user's creation date. The query then groups the results by and counts the number of purchases each user made. The clause restricts the results to users who made more than 10 purchases.
To solve a similar VIP customer analysis question on DataLemur's free interactive SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:
Dive into the latest news and events from Catalent, a leader in advanced delivery technologies and development solutions! Understanding Catalent's initiatives can provide you with a clearer picture of how they are enhancing the pharmaceutical and biotechnology industries.
SQL Question 2: Highly-Paid Employees
Given a table of Catalent employee salary data, write a SQL query to find all employees who earn more money than their direct boss.
Catalent 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.
Code your solution to this question 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 solution above is confusing, you can find a step-by-step solution here: Employee Salaries Higher Than Their Manager.
SQL Question 3: Can you describe the meaning of a constraint in SQL in layman's terms?
Constraints are used to specify the rules concerning data in the table. It can be applied for single or multiple fields in an SQL table during the creation of the table or after creating using the ALTER TABLE command. The constraints are:
Say you were storing sales analytics data from Catalent's CRM inside a database. Here's some example constraints you could use:
Here’s your text with the correct use of backticks:
-
PRIMARY KEY constraint: You might use a constraint to ensure that each record in the database has a unique identifier. For example, you could use the field as the primary key in the table.
-
FOREIGN KEY constraint: You might use a constraint to link the data in one table to the data in another table. For example, you could use a foreign key field in the table to reference the field in the table.
-
NOT NULL constraint: You might use a constraint to ensure that a field cannot contain a value. For example, you could use a constraint on the field in the table to ensure that each opportunity has a name.
-
UNIQUE constraint: You might use a constraint to ensure that the data in a field is unique across the entire table. For example, you could use a constraint on the field in the table to ensure that each contact has a unique email address.
-
CHECK constraint: You might use a constraint to ensure that the data in a field meets certain conditions. For example, you could use a constraint to ensure that the field in the table is a value between 0 and 100.
-
DEFAULT constraint: You might use a constraint to specify a default value for a field. For example, you could use a constraint on the field in the table to set the default value to "prospecting".
SQL Question 4: Find the weekly average workers' productivity in each production line
Assume that Catalent is a pharmaceutical company that has multiple production lines. Catalent wants to analyze the weekly output of each production line for the last three months. Write a SQL query to find the weekly average workers' productivity (in terms of units produced per hour) for each production line. Worker productivity is given by units produced in a shift divided by the shift's duration.
Example Input:
| shift_id | worker_id | start_time | end_time | production_line_id | units_produced |
|---|---|---|---|---|---|
| 1001 | 501 | 2022-06-01 08:00:00 | 2022-06-01 16:00:00 | 301 | 400 |
| 1002 | 502 | 2022-06-01 08:00:00 | 2022-06-01 16:00:00 | 301 | 500 |
| 1003 | 501 | 2022-06-02 08:00:00 | 2022-06-02 16:00:00 | 302 | 600 |
| 1004 | 503 | 2022-06-07 08:00:00 | 2022-06-07 16:00:00 | 301 | 700 |
| 1005 | 502 | 2022-06-08 08:00:00 | 2022-06-08 16:00:00 | 302 | 350 |
Example Output:
| week | production_line | avg_productivity |
|---|---|---|
| 22 | 301 | 28.125 |
| 22 | 302 | 37.500 |
| 23 | 301 | 43.750 |
| 23 | 302 | 21.875 |
Answer:
This SQL uses window function to calculate the weekly average productivity for each production line. It firstly extracts the week from the start time. Then for each partition of week and production line, the window function calculates the average productivity where productivity is given by units produced divided by shift duration. The clause is used to limit the calculation to the last three months.
p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: How can you identify duplicates in a table? Do have any other approaches?
One way to find duplicate records in a table is by using , and then seeing which groups have more than one occurence:
Another way is by using the operator:
SQL Question 6: Average Duration of Development Projects
As an analyst at Catalent, a leading global provider of advanced delivery technologies, development, and manufacturing solutions for drugs, biologics etc., you are tasked to find the average duration of all development projects that were completed last year.
Assume you have a table named "projects" with the following schema:
Example Input:
| project_id | project_name | start_date | end_date |
|---|---|---|---|
| 101 | "Development project A" | 2021-01-02 | 2021-04-05 |
| 102 | "Development project B" | 2021-03-01 | 2021-09-30 |
| 103 | "Development project C" | 2021-06-15 | 2022-02-20 |
| 104 | "Development project D" | 2020-12-15 | 2021-05-01 |
In this case, the expected output would look like this:
Example Output:
| avg_duration |
|---|
| 115 |
The duration is calculated as the difference in days between and .
Answer:
This query will calculate the average duration of all projects that completed in 2021. The function is used to fetch the year component from the and to fetch the number of days from the interval computed as the difference between and . The function then computes the average from these extracted days.
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating time periods or this Facebook Average Post Hiatus (Part 1) Question which is similar for finding duration between dates.
SQL Question 7: What's a correlated sub-query? How does it differ from a non-correlated sub-query?
While a correlated subquery relies on columns in the main query's clause and cannot function independently, a non-correlated subquery operates as a standalone query and its results are integrated into the main query.
An example correlated sub-query:
This correlated subquery retrieves the names and salaries of Catalent employees who make more than the average salary for their department. The subquery references the department column in the main query's clause () and uses it to filter the rows of the subquery's clause ().
An example non-correlated sub-query:
This non-correlated subquery retrieves the names and salaries of Catalent employees who make more than the average salary for the Data Science department (which honestly should be very few people since Data Scientists are awesome and deserve to be paid well).The subquery is considered independent of the main query can stand alone. Its output (the average salary for the Data Science department) is then used in the main query to filter the rows of the Catalent employees table.
SQL Question 8: Analyzing pharmaceutical manufacturing productivity
Assuming you are a data analyst at Catalent, a giant pharmaceutical company. You're given a database that logs the production details of each drug they manufacture. The details consist of the drug id, batch id, factory location, the date it was manufactured and the quantity produced (in kilograms).
The higher management needs your help to identify the highest quantity produced for each drug per factory location on a monthly basis to assess the productivity.
Please write a SQL query to address this.
Example Input:
| batch_id | drug_id | factory_location | manufactured_date | quantity_in_kg |
|---|---|---|---|---|
| 1001 | A101 | UK | 2021-12-02 | 250 |
| 1002 | A102 | US | 2021-12-03 | 350 |
| 1003 | A102 | UK | 2021-12-05 | 300 |
| 1004 | A101 | US | 2022-01-03 | 270 |
| 1005 | A101 | UK | 2022-01-04 | 400 |
Example Output:
| year_month | drug_id | factory_location | max_quantity |
|---|---|---|---|
| 2021-12 | A101 | UK | 250 |
| 2021-12 | A102 | US | 350 |
| 2021-12 | A102 | UK | 300 |
| 2022-01 | A101 | UK | 400 |
| 2022-01 | A101 | US | 270 |
Answer:
This query groups rows by each drug by each factory location on a monthly basis, and returns the maximum quantity of each drug produced in those groups.
Catalent 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 Catalent SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Microsoft, Google, and Meta.
Each exercise has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there's an online SQL coding environment so you can easily right in the browser your SQL query answer and have it executed.
To prep for the Catalent SQL interview it is also wise to practice SQL questions from other healthcare and pharmaceutical companies like:
- Bright HealthCare SQL questions
- Dentsply Sirona SQL questions
- Covetrus SQL questions
- Elanco Animal Health SQL questions
In case your SQL foundations are weak, forget about going right into solving questions – improve your SQL foundations with this free SQL for Data Analytics course.
This tutorial covers things like joins and handling NULLs in SQL – both of these come up frequently in SQL interviews at Catalent.
Catalent Data Science Interview Tips
What Do Catalent Data Science Interviews Cover?
In addition to SQL interview questions, the other question categories covered in the Catalent Data Science Interview are:
- Probability & Stats Questions
- Python Pandas or R Coding Questions
- Product Data Science Interview Questions
- ML Modelling Questions
- Behavioral Questions based on Catalent values & principles
How To Prepare for Catalent Data Science Interviews?
To prepare for Catalent Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from companies like Google, Tesla, & Goldman Sachs
- a crash course covering Product Analytics, SQL & ML
- over 1000+ reviews on Amazon & 4.5-star rating
Don't forget about the behavioral interview – prep for it using this guide on acing behavioral interviews.