10 Molson Coors SQL Interview Questions (Updated 2024)
At Molson Coors, employees write SQL queries to analyze consumption patterns across various demographics, helping them understand which beverages are popular among different age groups and regions. They also use SQL to optimize supply chain efficiency by analyzing inventory levels and sales data, ensuring that their products are always available when customers want them, this is the reason why Molson Coors asks SQL coding questions during interviews for Data Science, Data Engineering, and Data Analytics jobs.
Thus, to help you study, here’s 10 Molson Coors SQL interview questions – able to answer them all?
10 Molson Coors SQL Interview Questions
SQL Question 1: Identify VIP Customers for Molson Coors
Molson Coors, a multinational brewing company, wants to identify its VIP customers to target marketing efforts. To be considered a VIP, a customer needs to make substantial purchases (over 100 cases of beer) more than once in a month.
Please write a SQL query that will provide a list of VIP customers with the total number of cases they bought for each month of the year 2022.
Assume we have Access to two tables containing relevant data: table, which includes fields like , , and , and table, which includes , , and .
Example Input:
| customer_id | name | date_of_birth |
|---|---|---|
| 123 | John Smith | 02/10/1980 |
| 265 | Jane Doe | 08/14/1990 |
| 362 | Alice Johnson | 05/23/1985 |
Example Input:
| customer_id | date_of_sale | num_cases_sold |
|---|---|---|
| 123 | 01/08/2022 | 200 |
| 265 | 01/15/2022 | 90 |
| 123 | 01/27/2022 | 120 |
| 265 | 02/10/2022 | 110 |
| 362 | 02/23/2022 | 105 |
Answer:
This query starts by joining the two tables on the column. It then narrows down the result to records from the year 2022. The query groups the results by , name, and month, summing up the number of cases sold in each month. The clause ensures that only the customers who made substantial purchases more than once in a given month are considered. Finally, the query's results are ordered first by month and then in descending order by the number of cases bought.
To work on a similar customer analytics SQL question where you can solve it right in the browser and have your SQL code automatically checked, try this Walmart SQL Interview Question:
Stay informed with the latest news from Molson Coors, a company dedicated to brewing excellence and community engagement! Keeping up with their developments can help you appreciate how the beverage industry is evolving and responding to consumer trends.
SQL Question 2: Second Highest Salary
Imagine there was a table of Molson Coors employee salary data. Write a SQL query to find the 2nd highest salary among all employees.
Molson Coors Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
Solve this question and run your code right in DataLemur's online SQL environment:
Answer:
You can find a detailed solution here: 2nd Highest Salary.
SQL Question 3: What is database denormalization, and when is it a good idea to consider it?
Imagine you've got giant AF jigsaw puzzle with thousands of pieces, and each piece represents a piece of data in your database. You've spent hours organizing the puzzle into neat little piles, with each pile representing a table in your database. This process is called normalization, and it's a great way to make your database efficient, flexible, and easy to maintain.
But what if you want to solve the puzzle faster (aka make your queries run faster?)?
That's where denormalization comes in – Denormalization is like the puzzle-solving equivalent of taking a shortcut!
Instead of putting all the pieces in separate piles, you might decide to clone some of the pieces, and then have that one puzzle piece be put into multiple piles. Clearly, we are breaking the rules of physics, but that's just like de-normalization because it breaks the normal rules of normalization (1st, 2nd, 3rd normal forms).
By adding redundant puzzle pieces, it can be easier to find the pieces you need, but it also means that you have to be extra careful when you're moving pieces around or adding new ones (aka / commands become more complex).
On the plus side, denormalization can improve the performance of your database and make it easier to use. On the downside, it can make your database more prone to errors and inconsistencies, and it can be harder to update and maintain. In short, denormalization can be a helpful tool, but it's important to use it wisely!
SQL Question 4: Analyzing Beer Sales Across Different Regions
As a data analyst for the Molson Coors Brewing Company, you are asked to analyze the sales data of different beers across the regions in which the company operates. Analyze the sales data per month for each product and region, and compute the monthly percentage change in sales of each product per region. If there are products where the sales data for the previous month is not available, consider the monthly percentage change to 0.
You have two tables: a table containing columns , , and ; and a table with columns and .
Example Input:
| product_id | date | region_id | sales_value |
|---|---|---|---|
| 1 | 2021-01-01 | 3 | 500.0 |
| 1 | 2021-02-01 | 3 | 550.0 |
| 2 | 2021-01-01 | 3 | 700.0 |
| 2 | 2021-02-01 | 3 | 770.0 |
| 2 | 2021-03-01 | 3 | 700.0 |
Example Input:
| product_id | product_name |
|---|---|
| 1 | Molson Canadian |
| 2 | Coors Light |
Answer:
In this query, a common table expression (CTE) is used to introduce the lagged for each and combination, sorted in ascending order by . This CTE is fed into another CTE, , where the monthly percentage change is calculated by taking the difference between the current and previous month's sales value (divided by the current month sales), multiplied by 100. If there is no available sales data for the previous month, will return the current month's sales value (which will result in a 0% change). Lastly, is joined with table to get the product name. The final output lists the changes in monthly sales percentages for each product and region.
p.s. Window functions show up pretty frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: Can you describe the different types of joins in SQL?
In SQL, a join retrieves rows from multiple tables and combines them into a single result set.
Four JOIN types can be found in SQL. For an example of each one, suppose you had a table of Molson Coors orders and Molson Coors customers.
-
: Rows from both tables are retrieved when there is a match in the shared key or keys. An between the and tables would return only rows where the in the table matches the in the table.
-
: A 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, values will be returned for the right table's columns.
-
: A combines 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, values will be displayed for the left table's columns.
-
: A combines all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be displayed for the columns of the non-matching table.
SQL Question 6: Sales Analysis for Molson Coors
Molson Coors, a beer brewing company, wants to analyze their sales data more efficiently. They would like a report that shows the total quantity of each type of beer sold per month in the last year. They also want to know the total revenue generated by each type of beer. The company has two main tables, and .
The table contains data about each sale including the , the , the of the beer that was sold, and the sold.
The table contains data about each beer including the , , and .
Based on these requirements, design a SQL query that can generate this report, and provide sample input and output based on the database design.
Example Input:
| sale_id | sale_date | beer_id | quantity |
|---|---|---|---|
| 1234 | 2022-01-01 | 111 | 50 |
| 5678 | 2022-01-05 | 222 | 100 |
| 9123 | 2022-01-20 | 111 | 75 |
| 4567 | 2022-02-01 | 333 | 200 |
| 8912 | 2022-02-15 | 222 | 50 |
Example Input:
| beer_id | beer_name | price |
|---|---|---|
| 111 | Coors Light | 2 |
| 222 | Blue Moon | 3 |
| 333 | Miller Lite | 2.5 |
Answer:
This SQL query pulls the month of each sale and the corresponding beer name, calculates the total quantity sold for each month, and the total revenue for each beer per month. The clause filters out sales information for the last year, and the clause splits the data by month and beer. The clause sorts the output by month and total revenue. This way, you can easily see which beers generate the highest revenue each month.
Example Output:
| SaleMonth | beer_name | TotalQuantity | TotalRevenue |
|---|---|---|---|
| 1 | Blue Moon | 100 | 300 |
| 1 | Coors Light | 125 | 250 |
| 2 | Miller Lite | 200 | 500 |
| 2 | Blue Moon | 50 | 150 |
SQL Question 7: Can you explain the purpose of the SQL constraint?
A constraint ensures that all values in a column are different. This provides uniqueness for the column(s) and helps identify each row uniquely. Unlike primary key, there can be multiple unique constraints defined per table.
SQL Question 8: Calculate the Click-Through-Rate for Molson Coors' Ad Campaigns
Given a table detailing information about targeted ad campaigns by Molson Coors and another table that tracks individual user clicks on these ads, write a SQL query to calculate the Click Through Rate (CTR) for each campaign. The Click Through Rate is defined as the total number of clicks divided by the total number of impressions, expressed as a percentage. Consider an impression to be a single viewing of an ad.
Example Input:
| campaign_id | name | start_date | end_date | impressions |
|---|---|---|---|---|
| 501 | Summer Special | 06/01/2022 | 08/31/2022 | 10000 |
| 502 | Oktoberfest Launch | 09/01/2022 | 10/31/2022 | 8000 |
| 503 | Holiday Cheer | 11/01/2022 | 12/31/2022 | 12000 |
Example Input:
| click_id | user_id | click_timestamp | campaign_id |
|---|---|---|---|
| 719 | 123 | 06/30/2022 14:32:11 | 501 |
| 802 | 265 | 09/02/2022 19:48:29 | 502 |
| 939 | 362 | 06/02/2022 22:17:45 | 501 |
| 112 | 192 | 11/26/2022 00:20:38 | 503 |
| 451 | 981 | 12/15/2022 11:07:52 | 503 |
Expected Output:
| campaign_id | name | ctr |
|---|---|---|
| 501 | Summer Special | 0.02 |
| 502 | Oktoberfest Launch | 0.0125 |
| 503 | Holiday Cheer | 0.0166 |
Answer:
In the solution, we first join the and table on . Then use the function within to count the total number of associated with each campaign, convert the count total to a float and divide it by the , which gives us the Click Through Rate (CTR). We round this to 4 decimal places to get the CTR as a percentage. Each row in the output provides the , , and the CTR for that campaign.
To solve another question about calculating rates, solve this TikTok SQL question on DataLemur's online SQL code editor:
SQL Question 9: Average beer ratings per year for Molson Coors
As a data analyst for Molson Coors, your task is to write an SQL query that calculates the average annual rating for each type of beer sold by the company.
This information will help Molson Coors understand which of their beers are most liked by consumers and how perceptions change year on year.
Your result should include the year, the name of the beer, and its average rating for that year.
Example Input:
| beer_id | beer_name |
|---|---|
| 100 | Blue Moon |
| 200 | Coors Light |
| 300 | Miller Lite |
Example Input:
| rating_id | user_id | submit_date | beer_id | stars |
|---|---|---|---|---|
| 1 | 256 | 2020-05-12 | 100 | 5 |
| 2 | 512 | 2020-11-18 | 200 | 3 |
| 3 | 756 | 2021-04-25 | 100 | 4 |
| 4 | 892 | 2021-07-09 | 300 | 4 |
| 5 | 128 | 2022-03-13 | 200 | 4 |
Answer:
This query first extracts the year from the date the rating was submitted. It then calculates the average rating for each beer per year. The result is grouped by the year and the name of the beer, and is ordered by year and average rating in a descending order - from the highest rated beer to the lowest in each year.
Example Output:
| year | beer_name | avg_rating |
|---|---|---|
| 2020 | Blue Moon | 5.00 |
| 2020 | Coors Light | 3.00 |
| 2021 | Blue Moon | 4.00 |
| 2021 | Miller Lite | 4.00 |
| 2022 | Coors Light | 4.00 |
SQL Question 10: Can you explain the concept of a constraint in SQL?
Constraints are just rules for your DBMS to follow when updating/inserting/deleting data.
Say you had a table of Molson Coors employees, and their salaries, job titles, and performance review data. Here's some examples of SQL constraints you could implement:
: This constraint could be used to ensure that certain columns in the table, such as the employee's first and last name, cannot contain values.
: This constraint could be used to ensure that the employee ID is unique. This would prevent duplicate entries in the table.
: This constraint could be used to combine the and constraints to create a primary key for the table. The employee ID could serve as the primary key.
: This constraint could be used to establish relationships between the table and other tables in the database. For example, you could use a foreign key to link the employee ID to the department ID in a table to track which department each employee belongs to.
: This constraint could be used to ensure that certain data meets specific conditions. For example, you could use a constraint to ensure that salary values are always positive numbers.
: This constraint could be used to specify default values for certain columns. For example, you could use a constraint to set the employee hire date to the current date if no value is provided when a new employee is added to the database.
Molson Coors SQL Interview Tips
The key to acing a Molson Coors SQL interview is to practice, practice, and then practice some more! In addition to solving the earlier Molson Coors SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Google, Facebook, Microsoft and Amazon.
Each SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there is an interactive coding environment so you can instantly run your query and have it graded.
To prep for the Molson Coors SQL interview it is also useful to solve SQL questions from other food and facilities companies like:
- Conagra Brands SQL questions
- Hormel Foods SQL questions
- Keurig Dr Pepper SQL questions
- Andersons SQL questions
However, if your SQL coding skills are weak, forget about diving straight into solving questions – strengthen your SQL foundations with this free SQL tutorial.
This tutorial covers SQL concepts such as Subquery vs. CTE and aggregate window functions – both of which show up often in SQL job interviews at Molson Coors.
Molson Coors Data Science Interview Tips
What Do Molson Coors Data Science Interviews Cover?
In addition to SQL interview questions, the other types of questions to prepare for the Molson Coors Data Science Interview include:
- Statistics and AB Testing Questions
- Python or R Programming Questions
- Product Analytics Questions
- ML Modelling Questions
- Resume-Based Behavioral Questions
How To Prepare for Molson Coors Data Science Interviews?
I believe the optimal way to prepare for Molson Coors Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
It solves 201 data interview questions taken from tech companies like Netflix, Google, & Airbnb. The book's also got a crash course covering SQL, Product-Sense & ML. And finally it's helped a TON of people, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.
While the book is more technical in nature, it's also important to prepare for the Molson Coors behavioral interview. Start by reading the company's culture and values.