11 Coca-Cola SQL Interview Questions (Updated 2024)
Data Analytics, Data Science, and Data Engineering employees at Coca-Cola write SQL queries to analyze beverage sales data from various regions, allowing them to identify which products are popular in different markets. They also use SQL to manage supply chain efficiencies, helping them optimize production and ensure timely delivery of products, that is why Coca-Cola usually asks SQL problems during interviews.
So, to help you study, here’s 11 Coca-Cola SQL interview questions – how many can you solve?
11 Coca-Cola SQL Interview Questions
SQL Question 1: Analyze Coca-Cola's VIP Customers
As an analyst in Coca-Cola company, you have two tables: and . The table has a list of customers with their details, whereas the table logs the transactions made by customers. Your task is to identify the top 5 'power users', defined as customers who've bought the most number of Coca-Cola cases in the year 2022.
Example Input:
| user_id | name | sign_up_date | |
|---|---|---|---|
| 1 | John | john@mail.com | 09/15/2021 |
| 2 | Sarah | sarah@mail.com | 01/10/2022 |
| 3 | Mike | mike@mail.com | 06/12/2022 |
| 4 | Emma | emma@mail.com | 03/11/2021 |
| 5 | Matt | matt@mail.com | 10/20/2021 |
Example Input:
| order_id | user_id | order_date | product | quantity |
|---|---|---|---|---|
| 1201 | 1 | 02/15/2022 | Coca-Cola Cases | 10 |
| 1502 | 2 | 04/16/2022 | Coca-Cola Cases | 20 |
| 1639 | 3 | 07/03/2022 | Coca-Cola Cases | 15 |
| 1783 | 1 | 03/22/2022 | Coca-Cola Cases | 7 |
| 1945 | 4 | 08/31/2022 | Coca-Cola Cases | 12 |
Answer:
Here is a PostgreSQL query to solve it:
This query will first aggregate the total quantity of Coca-Cola cases ordered by each user in 2022. Then it joins this with the users' table to associate each user with the total quantity of Coca-Cola cases ordered. The result is then sorted in descending order and the top 5 users (those who purchased the largest number of cases) are returned.
To practice a related customer analytics question on DataLemur's free online SQL code editor, try this Microsoft SQL Interview problem:
Explore Coca-Cola’s media center to catch up on the latest news and exciting brand innovations that are shaping the beverage industry! Understanding Coca-Cola's initiatives can provide valuable insights into how a leading brand adapts to market trends and consumer preferences.
SQL Question 2: 2nd Highest Salary
Suppose there was a table of Coca-Cola employee salary data. Write a SQL query to find the 2nd highest salary at the company.
Coca-Cola Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
Write a SQL query for 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's the operator do, and can you give an example?
The operator merges the output of two or more statements into a single result set. The two statements within the must have the same number of columns and the data types of the columns are all compatible.
For example, if you were a Data Analyst on the marketing analytics team at Coca-Cola, this statement would return a combined result set of both Coca-Cola's Google and Facebook ads that have more than 300 impressions:
SQL Question 4: Calculate Total Sales and Average Sales
Coca-Cola is interested to analyze their beverage sales. They have a table, where each row represents a sale of a product. They would like you to write a SQL query to calculate both the total sales and the average sales for each product grouping by month and year.
The table is structured as follows:
Example Input:
| sale_id | sale_date | product_id | quantity | price_per_unit |
|---|---|---|---|---|
| 4798 | 2022-06-05 | CCE01 | 12 | 1.50 |
| 9456 | 2022-06-15 | CCF01 | 20 | 2.00 |
| 2764 | 2022-07-11 | CCE01 | 15 | 1.50 |
| 3780 | 2022-07-18 | CCE01 | 20 | 1.50 |
| 8471 | 2022-07-22 | CCF01 | 10 | 2.00 |
Please calculate the total sales and the average sales for each product grouping by month and year.
Example Output:
| month_year | product | avg_sales | total_sales |
|---|---|---|---|
| 06-2022 | CCE01 | 18.00 | 18.00 |
| 06-2022 | CCF01 | 40.00 | 40.00 |
| 07-2022 | CCE01 | 52.50 | 105.00 |
| 07-2022 | CCF01 | 20.00 | 20.00 |
Answer:
This query calculates the average and total sales per product for each month by multiplying with for each sale. It uses SQL window function, the and , to calculate the average and total respectively. It then groups the results by month and product.
p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: What are the similarities and difference between relational and non-relational databases?
While knowing this answer is beyond the scope of most Data Analyst & Data Science interviews, Data Engineers at Coca-Cola should be at least aware of SQL vs. NoSQL databases.
Relational databases and non-relational (NoSQL) databases have some key differences, particularly in terms of how data is stored. Whereas relational databases have tables, made up of rows and columns, NoSQL databases use various data models like:
- Wide-Column Stores – this database uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row within the same table
- Key-Value Stores – instead of rows and columns, you have keys, where each key is associated with only one value in a collection (similar to a Python dictionary data structure!)
- Graph Stores – instead of rows of data, you have nodes, and then can also have edges between entities (much like a Graph Data Structure for those who've taken a Computer Science data structures & algorithms class)
This added flexibility makes NoSQL databases well-suited for handling non-tabular data or data with a constantly changing format. However, this flexibility comes at the cost of ACID compliance, which is a set of properties (atomic, consistent, isolated, and durable) that ensure the reliability and integrity of data in a database. While most relational databases are ACID-compliant, NoSQL databases may not provide the same level of guarantees.
SQL Question 6: Coca-Cola Product Sales Analysis
As a data analyst at Coca-Cola, your task is to analyze the sales data of the different products sold in various regions. Coca-Cola has a number of products such as Coke, Diet Coke, Coke Zero, etc., and sells these products in many different regions.
The company has been tracking the data for each sale including the product id, region id, units sold and the sale date.
Design a database with tables for products, regions, and sales. Then write a query to find the total units sold for each product in each region for the year 2020.
Table:
| product_id | product_name |
|---|---|
| 1 | Coke |
| 2 | Diet Coke |
| 3 | Coke Zero |
Table:
| region_id | region_name |
|---|---|
| 1 | North America |
| 2 | Europe |
| 3 | Asia |
Table:
| sale_id | product_id | region_id | units_sold | sale_date |
|---|---|---|---|---|
| 101 | 1 | 1 | 200 | 2020-01-05 |
| 102 | 2 | 2 | 150 | 2020-10-15 |
| 103 | 3 | 3 | 300 | 2020-07-20 |
| 104 | 1 | 3 | 250 | 2020-08-04 |
| 105 | 2 | 1 | 200 | 2020-03-14 |
Answer:
This query joins the table with and tables to get the necessary data. It then filters for the sales data of the year 2020 using the function. The clause is used to group the data by product and region, and the function is used to calculate the total units sold for each product in each region.
SQL Question 7: What are the similarities and differences between correleated and non-correlated sub-queries?
A non-correlated sub-query is not linked to the outer query and can be run on its own. It does not reference any columns from the outer query and is used to retrieve additional data for the outer query. On the other hand, a correlated sub-query is one that relies on the outer query and cannot be run independently. It uses the outer query to filter or transform data by referencing a column from it, while the outer query uses the results of the inner query.
Here is an example of a non-correlated sub-query:
The sub-query in this case is non-correlated, as it does not reference any columns from the outer query.
Here is an example of a correlated sub-query:
This query selects the and total sales of all Coca-Cola customers in the sales table whose are greater than the average of their own customer group. The sub-query in this case is correlated with the outer query, as it references the column from the outer query ().
Non-correlated sub-queries are typically faster, as they only have to be executed once, wheareas correlated sub-queries are slower since they have to be re-evaluated for each row of the outer query.
SQL Question 8: Average sales of Coca-Cola products
As a product analyst at Coca-Cola, we received quarterly sales data for our different products. Your task is to determine the average sales per product for each quarter across all years.
We assume sales of products are given in quantity. Input and output should be in the following format:
Sample Input:
| sale_id | product_id | product_name | quarter | year | quantity_sold |
|---|---|---|---|---|---|
| 1 | 123 | Coca-Cola Classic | Q1 | 2020 | 5000 |
| 2 | 456 | Diet Coke | Q1 | 2020 | 4500 |
| 3 | 123 | Coca-Cola Classic | Q2 | 2020 | 8000 |
| 4 | 456 | Diet Coke | Q2 | 2020 | 7000 |
| 5 | 123 | Coca-Cola Classic | Q1 | 2021 | 6000 |
| 6 | 456 | Diet Coke | Q1 | 2021 | 7000 |
Sample Output:
| product_name | quarter | average_sales |
|---|---|---|
| Coca-Cola Classic | Q1 | 5500.00 |
| Diet Coke | Q1 | 5750.00 |
| Coca-Cola Classic | Q2 | 8000.00 |
| Diet Coke | Q2 | 7000.00 |
Answer:
This SQL statement first groups the sales data by and using the clause. Then it uses the aggregate function to compute the average sales per product per quarter. The result is a table that includes each product's name, the quarter, and the average sales of that product in that quarter.
To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating sales rate over a period or this Amazon Average Review Ratings Question which is similar for obtaining average metrics for products.
SQL Question 9: Analyze the sales data of Coca-Cola products
Given a table, each row documents a transaction that indicates a (corresponds to a unique product), (corresponds to a unique sales region), (the date the sale occurred) and (the number of units sold in that transaction). Write a SQL query to find the total units sold for each Coca-Cola product for each sales region.
Example Input:
| transaction_id | sale_date | product_id | region_id | quantity |
|---|---|---|---|---|
| 1 | 2021-01-02 | 01 | A | 10 |
| 2 | 2021-01-04 | 02 | B | 20 |
| 3 | 2021-02-15 | 01 | B | 50 |
| 4 | 2021-02-20 | 03 | C | 30 |
| 5 | 2021-02-28 | 02 | A | 100 |
Example Output:
| region_id | product_id | total_quantity |
|---|---|---|
| A | 01 | 10 |
| B | 02 | 20 |
| B | 01 | 50 |
| C | 03 | 30 |
| A | 02 | 100 |
Answer:
This query will aggregate the sales data by and and will return the total quantity sold for each unique combination of and . The aggregate function is used to total the quantities sold. specifies the list of columns that we want to use as grouping columns.
SQL Question 10: What's a primary key?
The primary key of a table is a column or set of columns that serves as a unique identifier for each row. It ensures that all rows are distinct and does not allow null values.
For example, say you had stored some Facebook ad campaign data that Coca-Cola ran:
The CampaignID column is used to uniquely identify each row in the table, and the constraint ensures that there are no duplicate values. This helps to maintain the accuracy of the data by preventing duplicate rows. The primary key is also an important part of the table because it enables you to easily identify and reference specific campaigns in your Facebook Ad data. You can use it to join to other tables in the database, such as a table with data on the results of the campaigns.
SQL Question 11: Filter Coca-Cola Product Reviews
Suppose you are analyzing product reviews for Coca-Cola. You have been asked to find all the reviews that contain the word "sugar" in the . Additionally, include the date the review was written and the user who wrote it.
Consider the following sample table :
Example Input:
| review_id | user_id | review_date | review_text |
|---|---|---|---|
| 1 | 123 | 2022-09-25 00:00:00 | "Love the sweetness in Coca-Cola, good sugar level." |
| 2 | 456 | 2022-09-24 00:00:00 | "Coca-Cola is my go-to drink, always." |
| 3 | 789 | 2022-09-23 00:00:00 | "Not sure about the sugar content in this new Coca-Cola." |
| 4 | 321 | 2022-09-22 00:00:00 | "Coca-Cola Zero Sugar is the best!" |
| 5 | 654 | 2022-09-21 00:00:00 | "Can't drink other sodas, Coca-Cola for life." |
Question: Write a SQL query that retrieves all the reviews that contain the word "sugar", and the respective review dates and users.
Answer:
This query uses the keyword in SQL which is used in the clause to search for a specified pattern in a column. The '%' sign is used to define wildcards (missing letters) both before and after the pattern. In this case, the pattern is the word 'sugar'.
How To Prepare for the Coca-Cola SQL Interview
The key to acing a Coca-Cola SQL interview is to practice, practice, and then practice some more! Besides solving the earlier Coca-Cola SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Microsoft, Google, Amazon, and tech startups.
Each problem on DataLemur has multiple hints, step-by-step solutions and crucially, there's an online SQL coding environment so you can easily right in the browser your SQL query and have it executed.
To prep for the Coca-Cola SQL interview it is also a great idea to solve SQL questions from other food and facilities companies like:
- Tyson Foods SQL questions
- PepsiCo SQL questions
- Archer Daniels Midland SQL questions
- Brown-Forman SQL questions
In case your SQL foundations are weak, don't worry about diving straight into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.
This tutorial covers topics including rank window functions and LEFT vs. RIGHT JOIN – both of which show up often in Coca-Cola interviews.
Coca-Cola Data Science Interview Tips
What Do Coca-Cola Data Science Interviews Cover?
Besides SQL interview questions, the other types of questions to prepare for the Coca-Cola Data Science Interview are:
- Statistics and Probability Questions
- Python or R Coding Questions
- Product Analytics Questions
- ML Interview Questions
- Behavioral Questions based on Coca-Cola values & principles
How To Prepare for Coca-Cola Data Science Interviews?
To prepare for Coca-Cola Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from FAANG tech companies
- a refresher on Product Analytics, SQL & 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.