9 West Pharma SQL Interview Questions (Updated 2024)
Data Analysts and Data Engineers at West Pharma rely on SQL queries to analyze pharmaceutical manufacturing data, helping them find ways to improve efficiency and streamline production workflows. They also use SQL to manage patient information, allowing them to create personalized healthcare solutions for each patient, this is the reason why West Pharma frequently asks jobseekers SQL interview questions.
Thus, to help you study for the West Pharma SQL interview, here’s 9 West Pharmaceutical Services SQL interview questions in this blog.
9 West Pharmaceutical Services SQL Interview Questions
SQL Question 1: Identifying Power User Activity in West Pharma database
West Pharma is interested in identifying their power users. Specifically, they want to find customers who have placed orders worth more than $5000 each month consistently over the past three months.
Please write a SQL query to find such power users, given the table and table as shown below:
Example Input:
| order_id | customer_id | order_date | total_order_value |
|---|---|---|---|
| 001 | 5016 | 01/01/2022 | $5500 |
| 002 | 1526 | 01/01/2022 | $1000 |
| 003 | 5016 | 02/01/2022 | $5900 |
| 004 | 1526 | 02/01/2022 | $600 |
| 005 | 5016 | 03/01/2022 | $6200 |
| 006 | 3871 | 06/10/2022 | $3000 |
Example Input:
| customer_id | customer_name | customer_registration_date |
|---|---|---|
| 5016 | John Doe | 01/01/2020 |
| 1526 | Jane Doe | 02/02/2019 |
| 3871 | Mary Johnson | 03/03/2021 |
Answer:
The query above uses a to combine relevant information from the and tables. Using the clause, the query filters the results to focus only on the orders made within the specified three-month period. The clause groups the orders by customer. The clause is then used to filter the groups of orders by customers who have made orders worth more than $5,000 each month over the three-month period. The results are then ordered by the sum of order values in descending order.
To practice a related customer analytics question on DataLemur's free interactive SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:
Stay updated with the latest news and events from West Pharma, a leader in innovative drug delivery and containment solutions! Keeping an eye on West Pharma's developments can help you understand the evolving landscape of pharmaceutical services and their impact on healthcare.
SQL Question 2: Department Salaries
Assume there was a table of West Pharma employee salaries, 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 interactively on DataLemur:
The answer is LONG – 30+ lines of SQL. You can find a detailed solution with hints here: Department vs. Company Salary.
SQL Question 3: What's an index, and what are the different types?
A database index is a way to optimize the performance of a database by reducing the amount of data that needs to be searched to retrieve a record.
There are several types of indexes that can be used in a database:
- Primary index: a unique identifier is used to access the row directly.
- Unique index: used to enforce the uniqueness of the indexed columns in a table.
- Composite index: created on multiple columns of a table, is used to speed up the search process for multiple columns
- Clustered index: determines the physical order of the data in a table
For a concrete example, say you had a table of West Pharma customer payments with the following columns: , , , and .
Here's what a clustered index on the column would look like:
A clustered index on the column would determine the physical order of the records in the table based on the . This means that the records with the earliest values would be stored together physically in the table, followed by records with later values.
Having a clustered index on the column can speed up queries that filter or sort the data based on the , as the records are already physically sorted in the table. For example, if you want to retrieve all the payments made in the month of January, the database can use the clustered index to quickly locate and retrieve the desired records without having to search through the entire table.
SQL Question 4: Average Monthly Sales Volume
As part of the analysis team at West Pharma, you have been given the task to analyze the sales data. Your goal is to write a PostgreSQL query using a window function to find out the average monthly sales volume for each product.
Example Input:
| sales_id | product_id | sales_date | volume_sold |
|---|---|---|---|
| 201 | 50001 | 7/10/2021 | 200 |
| 212 | 50001 | 7/15/2021 | 125 |
| 234 | 69852 | 7/18/2021 | 300 |
| 256 | 66600 | 8/01/2021 | 400 |
| 275 | 69852 | 8/10/2021 | 150 |
| 286 | 66600 | 8/15/2021 | 350 |
| 308 | 66600 | 8/25/2021 | 200 |
| 331 | 50001 | 9/10/2021 | 250 |
Expected Output:
| month | product_id | avg_volume_sold |
|---|---|---|
| 7 | 50001 | 162.5 |
| 7 | 69852 | 300 |
| 8 | 66600 | 316.67 |
| 8 | 69852 | 150 |
| 9 | 50001 | 250 |
Answer:
The solution uses the window function with to calculate the average sales volume for each product in every month. The function is used to get the month from the . Finally, the clause is used to return the results in the order of the month and .
Please note that in the output, the average volumes are rounded to 2 decimal points for readability.
p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: How do you locate records in one table that are absent from another?
To discover records in one table that are not present in another, you can utilize a and filter out any values in the right-side table.
For example, say you had a table of West Pharma customers and a 2nd table of all purchases made with West Pharma. To find all customers who did not make a purchase, you'd use the following
This query returns all rows from the customers table, along with any matching rows from the purchases table. If there is no matching row in the purchases table, values will be returned for all of the right table's columns. The clause then filters out any rows where the purchases.id column is , leaving only customers who have not made a purchase.
SQL Question 6: Average Quantity of Products Manufactured
As a data analyst for West Pharma, you are tasked to track the efficiency of their production lines. Each product has an associated id and numerous batches are produced regularly. Write a SQL query that will calculate the average quantity of each product manufactured per day within a specific month. Assume we have a table tracking day-to-day manufacturing details.
Example Input:
| id | product_id | date_produced | quantity_produced |
|---|---|---|---|
| 1 | 555 | 2022-06-01 | 200 |
| 2 | 555 | 2022-06-02 | 230 |
| 3 | 566 | 2022-06-02 | 120 |
| 4 | 555 | 2022-06-03 | 210 |
| 5 | 566 | 2022-06-03 | 130 |
| 6 | 555 | 2022-07-01 | 220 |
| 7 | 566 | 2022-07-01 | 140 |
Example Output:
| mth | product | avg_quantity |
|---|---|---|
| 6 | 555 | 213.33 |
| 6 | 566 | 125.00 |
| 7 | 555 | 220.00 |
| 7 | 566 | 140.00 |
Answer:
This query first uses the function to get the month from the column. Then, it groups the data by the month and the , and calculates the average quantity produced for each unique grouping. The resulting table will have a row for each product each month, displaying the average quantity produced in that particular month.
To practice a very similar question try this interactive Tesla Unfinished Parts Question which is similar for tracking production progress or this Amazon Average Review Ratings Question which is similar for grouping by month.
SQL Question 7: Could you explain what a self-join is and provide examples of when it might be used?
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 analyze 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 West Pharma interact with one another, you could use a self-join query like the following to retrieve all pairs of West Pharma employees who work in the same department:
This query returns all pairs of West Pharma employees who work in the same department, and excludes pairs where the employee's id is the same (since this would represent the same West Pharma employee being paired with themselves).
SQL Question 8: Find the maximum quantity of each product sold per region.
West Pharma sells a variety of pharmaceutical products across multiple regions. The company wants to review its sales data to find the product that has the maximum number of sales in each region. Write a query to find the maximum quantity of each product sold per region.
Example Input:
| sale_id | product_id | region | quantity | sale_date |
|---|---|---|---|---|
| 1 | 101 | North | 250 | 01/01/2022 |
| 2 | 102 | East | 400 | 02/02/2022 |
| 3 | 101 | South | 300 | 05/03/2022 |
| 4 | 103 | North | 50 | 06/10/2022 |
| 5 | 102 | West | 700 | 07/11/2022 |
| 6 | 101 | East | 200 | 07/15/2022 |
| 7 | 103 | South | 150 | 08/05/2022 |
| 8 | 102 | North | 500 | 08/20/2022 |
Example Output:
| region | max_product_id | max_quantity |
|---|---|---|
| North | 102 | 500 |
| East | 102 | 400 |
| South | 101 | 300 |
| West | 102 | 700 |
Answer:
The PostgreSQL query to find the maximum quantity of each product sold per region would look like this:
This query groups by and , then calculates the maximum quantity sold for each product in each region. We then select the , (aliased as ), and the maximum (aliased as ). Finally, we order the result by to make it easier to see which product sold the most in each region.
SQL Question 9: Calculate Effective Drug Output
West Pharma, a pharmaceutical company, maintains monthly data on the quantity of drugs produced, the percentage defects in manufacturing, and the subsequent corrections made. They want to calculate the effective drug output each month, taking into consideration the defects and corrections. The effective output is calculated using the formula:
The input data has each row representing one month's performance for a specific drug, and the columns consists of , , , , , . Compute the effective drug output for each month rounded to the nearest whole number. The output should include , , , .
Example Input:
| month | year | drug_id | produced | defect_percentage | corrections |
|---|---|---|---|---|---|
| 1 | 2022 | 101 | 5000 | 5 | 200 |
| 1 | 2022 | 102 | 6000 | 8 | 300 |
| 2 | 2022 | 101 | 4000 | 3 | 150 |
| 2 | 2022 | 102 | 5500 | 6 | 250 |
| 3 | 2022 | 101 | 4500 | 4 | 180 |
| 3 | 2022 | 102 | 5800 | 7 | 280 |
Example Output:
| month | year | drug_id | effective_output |
|---|---|---|---|
| 1 | 2022 | 101 | 4950 |
| 1 | 2022 | 102 | 5820 |
| 2 | 2022 | 101 | 4038 |
| 2 | 2022 | 102 | 5365 |
| 3 | 2022 | 101 | 4526 |
| 3 | 2022 | 102 | 5626 |
Answer:
This SQL query calculates the effective output for each row/month by subtracting the quantity equivalent to the defect percentage from the produced quantity and adding the corrections. It uses arithmetic operators and the function to round the results to the nearest whole number. The calculations are performed directly within the statement, and there are no or constraints since the processing is straightforward.
To practice a very similar question try this interactive CVS Health Pharmacy Analytics (Part 1) Question which is similar for calculation involving production data or this Tesla Unfinished Parts Question which is similar for dealing with defects in manufacturing.
West Pharma SQL Interview Tips
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the West Pharma SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the earlier West Pharma SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like FAANG (FB, Apple, Amazon, Netflix, Google).
Each exercise has multiple hints, fully explained answers along with a discussion board to see how others solved it and most importantly, there is an interactive coding environment so you can instantly run your SQL query and have it executed.
To prep for the West Pharma SQL interview you can also be wise to solve SQL questions from other healthcare and pharmaceutical companies like:
- Hill-Rom Holdings SQL questions
- Change Healthcare SQL questions
- ResMed SQL questions
- IDEXX Laboratories SQL questions
But if your SQL coding skills are weak, forget about diving straight into solving questions – go learn SQL with this DataLemur SQL Tutorial.
This tutorial covers topics including WHERE vs. HAVING and math functions in SQL – both of which show up frequently in West Pharma interviews.
West Pharmaceutical Services Data Science Interview Tips
What Do West Pharma Data Science Interviews Cover?
In addition to SQL query questions, the other types of problems to prepare for the West Pharma Data Science Interview are:
- Statistics & AB Testing Questions
- Python or R Programming Questions
- Product Analytics Questions
- ML Interview Questions
- Behavioral & Resume-Based Questions
How To Prepare for West Pharma Data Science Interviews?
To prepare for the West Pharma Data Science interview make sure you have a strong understanding of the company's values and company principles – this will be clutch for acing the behavioral interview. For technical interviews get ready by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from Microsoft, Amazon & startups
- A Crash Course on SQL, AB Testing & ML
- Great Reviews (1000+ 5-star reviews on Amazon)