9 Philip Morris SQL Interview Questions (Updated 2024)
At Philip Morris, SQL is often used to analyze smoking behavior trends, providing valuable insights into consumer habits and preferences. It also helps in improving supply chain efficiency by analyzing product distribution data, allowing them to streamline operations and enhance logistics, this is why Philip Morris frequently includes SQL problems in interviews for Data Analyst, Data Science, and Business Intelligence (BI) positions.
As such, to help you study for the Philip Morris SQL interview, we've collected 9 Philip Morris SQL interview questions in this article.
9 Philip Morris SQL Interview Questions
SQL Question 1: Find the top selling product in each month
Philip Morris is the global tobacco company best known for Marlboro and Parliament brands. Assume that we want to prepare an analysis of monthly top selling product with the total sales quantity. Here is the database you have:
Example Input:
| sale_id | product_id | sale_date | quantity |
|---|---|---|---|
| 1001 | 555 | 01/01/2022 00:00:00 | 400 |
| 1002 | 666 | 01/01/2022 00:00:00 | 500 |
| 1003 | 777 | 01/01/2022 00:00:00 | 600 |
| 1004 | 777 | 02/01/2022 00:00:00 | 700 |
| 1005 | 555 | 02/01/2022 00:00:00 | 800 |
| 1006 | 666 | 02/01/2022 00:00:00 | 900 |
| 1007 | 777 | 02/01/2022 00:00:00 | 1000 |
Example Input:
| product_id | product_name |
|---|---|
| 555 | Marlboro |
| 666 | Parliament |
| 777 | L&M |
Your task is to write a PostgreSQL query that will return the top selling product in each month with the corresponding total sales quantity.
Answer:
In this query, we have used a Window function called . After calculating the total sales quantity for each product in each month, we have ranked this sales quantity within each month with the highest quantity getting the rank 1. In the final query, we are selecting only the rows with rank = 1 which gives us the top selling product with quantity in each month.
For more window function practice, solve this Uber SQL problem within DataLemur's online SQL coding environment:
Visit Philip Morris' media center to uncover the latest updates and initiatives from one of the world's leading tobacco companies! Gaining insights into PMI's strategies can help you understand how they are evolving in a changing market landscape.
SQL Question 2: Top Three Salaries
Suppose there was a table of Philip Morris employee salary data. Write a SQL query to find the top three highest paid employees in each department.
Philip Morris Example Input:
| employee_id | name | salary | department_id |
|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 |
| 2 | Daniel Rodriguez | 2230 | 1 |
| 3 | Olivia Smith | 2000 | 1 |
| 4 | Noah Johnson | 6800 | 2 |
| 5 | Sophia Martinez | 1750 | 1 |
| 8 | William Davis | 6800 | 2 |
| 10 | James Anderson | 4000 | 1 |
Example Input:
| department_id | department_name |
|---|---|
| 1 | Data Analytics |
| 2 | Data Science |
Example Output:
| department_name | name | salary |
|---|---|---|
| Data Analytics | James Anderson | 4000 |
| Data Analytics | Emma Thompson | 3800 |
| Data Analytics | Daniel Rodriguez | 2230 |
| Data Science | Noah Johnson | 6800 |
| Data Science | William Davis | 6800 |
Solve this problem interactively on DataLemur:
Answer:
We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.
If the code above is tough, you can find a step-by-step solution here: Top 3 Department Salaries.
SQL Question 3: 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 4: Sales Analysis for Philip Morris
Philip Morris International is a multinational cigarette and tobacco manufacturing company. Suppose their sales department keeps records of their sales in different countries. Independently, they also keep record of various marketing strategies they implement in countries. They would like an SQL query that can show how different marketing strategies are affecting sales in various countries.
The sales data is stored in a Postgresql table called . Each row of this table represents a sale to a retailer. The columns are , , , , and .
Example Input:
| sale_id | country | product_id | sale_date | quantity | price |
|---|---|---|---|---|---|
| 1 | USA | 101 | 2022-09-09 | 100 | 10 |
| 2 | USA | 102 | 2022-09-10 | 200 | 20 |
| 3 | CAN | 101 | 2022-09-10 | 150 | 15 |
| 4 | CAN | 102 | 2022-09-11 | 300 | 25 |
| 5 | AUS | 101 | 2022-09-09 | 120 | 12 |
The marketing data is stored in another table called marketing. The columns in this table are , , and .
Example Input:
| strategy_id | country | start_date | end_date |
|---|---|---|---|
| 1 | USA | 2022-09-01 | 2022-09-10 |
| 2 | CAN | 2022-09-05 | 2022-09-15 |
| 3 | AUS | 2022-09-07 | 2022-09-17 |
Create an SQL query that shows how much revenue was generated in each country during the implementation of each marketing strategy.
Answer:
This query joins the and tables on the field and the field being between the and fields. It then calculates the total revenue for each marketing strategy in each country by summing the product of the and fields, and groups the results by and .
SQL Question 5: Can you give some examples of when denormalization might be a good idea?
Normalization can reduce redundancy and improve performance and flexibility in a database.
By dividing larger tables into smaller, more specific ones linked by foreign keys, it is often possible to improve query speed. Note: it is not always the case that query speed will be improved due to costly nature of joins. Still, we think normalization is a good idea because it can also increase flexibility by making it easier to alter individual tables without affecting others, which can be useful for adapting Philip Morris's database to ever-changing business needs.
SQL Question 6: Filter Customers Based on Purchase History and Location
Given a customer records database for Philip Morris, write a SQL query to find all customers who are located in a specific region (for example "North America") and have purchased more than $500 worth of tobacco products in the last month. Specifically, we want to find both the customer's ID and their total expenditure on tobacco products. Assume we have two tables - with fields , , and with fields , , , and .
Example Input:
| customer_id | name | region |
|---|---|---|
| 1 | John Doe | North America |
| 2 | Jane Doe | Europe |
| 3 | Jim Doe | North America |
| 4 | Jill Doe | Africa |
Example Input:
| purchase_id | customer_id | product_type | amount | purchase_date |
|---|---|---|---|---|
| 101 | 1 | tobacco | $200 | 2022-09-01 |
| 102 | 1 | tobacco | $400 | 2022-09-15 |
| 103 | 2 | tobacco | $600 | 2022-09-05 |
| 104 | 3 | tobacco | $450 | 2022-09-07 |
| 105 | 3 | alcohol | $250 | 2022-09-18 |
Expected Output:
| customer_id | total_expenditure |
|---|---|
| 1 | $600 |
Answer:
In this query, we are joining the and tables on . We filter customers based on their region and the product type and date of their purchases. Then, for each customer, we calculate their total expenditure on tobacco products in the last month. We use the clause to filter out customers whose total expenditure is not more than $500.
SQL Question 7: What distinguishes an inner join from a full outer join?
An inner join only includes rows from both tables that satisfy the join condition, whereas a full outer join includes all rows from both tables, regardless of whether they match the join condition or not.
For example, suppose you had a table of Philip Morris orders and Philip Morris customers.
INNER JOIN: When there is a match in the shared key or keys, rows from both tables are retrieved. In this example, an between the Orders and Customers tables would retrieve rows where the in the Orders table matches the in the Customers table.
FULL OUTER JOIN: A 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: Calculate Click-Through-Rate (CTR) for Philip Morris Digital Ads
As Philip Morris International invests in digital marketing to promote their products, they desire to understand the effectiveness of their campaigns. They record every impression (times ads are shown) and clicks that each ad receives. Given a dataset with impressions and clicks for each ad, your task is to compute the click-through-rate for each ad. Click-through rate (CTR) is the ratio of users who click on a link to the number of total users who view the ad.
Example Input:
| ad_id | impressions | clicks |
|---|---|---|
| 001 | 10000 | 100 |
| 002 | 15000 | 400 |
| 003 | 12000 | 300 |
| 004 | 8000 | 200 |
| 005 | 20000 | 500 |
Your goal is to write a PostgreSQL query that returns the and its corresponding click-through rate (CTR), calculated as (clicks/impressions) * 100. The click-through rate should be presented as a percentage with two decimal places.
Answer:
This SQL block works by selecting the and calculating the CTR. In the CTR calculation, the number of clicks is cast to to avoid integer division. The result is then rounded to two decimal figures for a cleaner output.
Example Output:
| ad_id | ctr |
|---|---|
| 001 | 1.00% |
| 002 | 2.67% |
| 003 | 2.50% |
| 004 | 2.50% |
| 005 | 2.50% |
The numbers in the CTR column represent the proportion of impressions that resulted in a click. For example, ad 001 had a CTR of 1.00%, meaning that 1.00% of the impressions resulted in a click.
To practice a similar problem about calculating rates, try this TikTok SQL Interview Question on DataLemur's online SQL code editor:
SQL Question 9: Analyze Sales Statistics by Joining Customer and Sales Tables
You are provided with two tables, and . The table contains detailed information about the customers, while the 'Sales' table includes specific product sales information.
Your task is to write an SQL query that retrieves all customers from the table who are from 'USA' and join this data with the 'Sales' table in order to find total sales per each of these customers.
Here are the tables:
Example Input:
| customer_id | first_name | last_name | country |
|---|---|---|---|
| 001 | John | Doe | USA |
| 002 | Jane | Smith | UK |
| 003 | Michael | Johnson | USA |
| 004 | Emma | Brown | Canada |
| 005 | David | White | USA |
Example Input:
| sales_id | customer_id | product_id | quantity | price |
|---|---|---|---|---|
| 0001 | 001 | 101 | 5 | 20 |
| 0002 | 001 | 102 | 2 | 50 |
| 0003 | 002 | 103 | 1 | 30 |
| 0004 | 003 | 104 | 3 | 15 |
| 0005 | 005 | 105 | 2 | 10 |
Answer:
This query first joins the and tables based on the matching . Then it filters out the data for customers from . The aggregate function is used along with to calculate the total sales per each customer from .
Because join questions come up so often during SQL interviews, try this interactive Snapchat SQL Interview question using JOINS:
Philip Morris SQL Interview Tips
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Philip Morris SQL interview is to solve as many practice SQL interview questions as you can! Besides solving the earlier Philip Morris SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Netflix, Airbnb, and Amazon.
Each exercise has multiple hints, full answers and best of all, there's an online SQL code editor so you can instantly run your query and have it executed.
To prep for the Philip Morris SQL interview you can also be helpful to solve SQL questions from other food and facilities companies like:
But if your SQL coding skills are weak, don't worry about diving straight into solving questions – refresh your SQL knowledge with this interactive SQL tutorial.
This tutorial covers topics including using ORDER BY and manipulating date/time data – both of which show up frequently during SQL job interviews at Philip Morris.
Philip Morris Data Science Interview Tips
What Do Philip Morris Data Science Interviews Cover?
In addition to SQL interview questions, the other types of questions to prepare for the Philip Morris Data Science Interview include:
- Stats Interview Questions
- Coding Questions in Python or R
- Open-Ended Data Case Studies
- ML Interview Questions
- Behavioral Interview Questions focussed on Philip Morris culture and values
How To Prepare for Philip Morris Data Science Interviews?
To prepare for Philip Morris Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from Google, Microsoft & tech startups
- a crash course on SQL, AB Testing & ML
- over 1000+ reviews on Amazon & 4.5-star rating
Don't ignore the behavioral interview – prep for that with this list of common Data Scientist behavioral interview questions.