9 Church & Dwight SQL Interview Questions (Updated 2024)
Church & Dwight employees use SQL to analyze consumer purchase history and loyalty program data to identify trends in FMCG product sales. It is also used to optimize supply chain management by predicting demand for specific product lines based on seasonal fluctuations and regional preferences, resulting Church & Dwight to ask SQL problems during interviews for Data Science and Data Engineering positions.
So, to help you study for the Church & Dwight SQL interview, we'll cover 9 Church & Dwight SQL interview questions in this article.
9 Church & Dwight SQL Interview Questions
SQL Question 1: Analyzing Sales Revenue
Suppose you are data analyst at Church & Dwight and you want to analyze the sales data. Your task is to write a SQL query to calculate the total and average revenue per product over each month. You need to use SQL window functions in your query.
Here is the example input data.
Example Input:
| sales_id | sale_date | product_id | price | units |
|---|---|---|---|---|
| 101 | 2021-01-01 | 2001 | 10 | 100 |
| 102 | 2021-01-05 | 2001 | 10 | 120 |
| 103 | 2021-01-15 | 2002 | 20 | 150 |
| 104 | 2021-02-01 | 2001 | 10 | 100 |
| 105 | 2021-02-15 | 2002 | 20 | 200 |
| 106 | 2021-02-28 | 2001 | 10 | 150 |
Answer:
The SQL query above first creates a CTE () where it groups the sales data by month and , and calculates the total revenue per product for each month. It also calculates the average revenue per product over each month using the window function . Then, it selects the month, product_id, total_revenue, and average_revenue from the CTE and orders the result by month and product_id.
Pro Tip: Window functions are a frequent SQL interview topic, so practice every window function problem on DataLemur
SQL Question 2: Second Highest Salary
Given a table of Church & Dwight employee salary information, write a SQL query to find the 2nd highest salary among all employees.
Church & Dwight Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
Code your solution to this problem directly within the browser on DataLemur:
Answer:
You can find a step-by-step solution with hints here: 2nd Highest Salary.
SQL Question 3: What are the ACID properties in a DBMS?
ACID refers to the four key properties that are essential to the reliable and correct execution of database transactions. These properties are:
Atomicity: ensures that a transaction is treated as a single operation, and either all of the changes are made or none of them are! Basically, the database version of a "-FULL SEND-"
Consistency: ensures that the data is in a consistent state before and after a transaction is completed. For example, if wiring money to a friendly Nigerian prince whose fallen on hard times, consistency ensures that the total value of funds lost in my account is the same amount that's gained in the prince's account!
Isolation: ensures that the intermediate state of a transaction is invisible to other transactions. Back to the wiring-the-prince-some-money example, isolation ensures that another transaction sees the transferred funds in my account OR the princes, but not in both accounts at the same time
Durability: ensures that once a transaction has been completed successfully, the changes made by the transaction are permanent and cannot be undone, even in the event of a system failure. Basically, no taksies backsies (even if your system has a meltdown!).
SQL Question 4: Finding the Most Purchased Product
Church & Dwight needs to know which product is the most popular among their customers in each of the states. Using their "sales" database, your task is to write a SQL query that calculates the product with the most quantity sold in each state. The relevant fields are "product_id", "quantity", and "state".
Example Input:
| sale_id | product_id | state | quantity |
|---|---|---|---|
| 1101 | 510 | NY | 7 |
| 1102 | 620 | CA | 8 |
| 1130 | 510 | CA | 5 |
| 1151 | 600 | TX | 4 |
| 1182 | 620 | TX | 10 |
| 1203 | 600 | NY | 3 |
| 1230 | 620 | CA | 2 |
Answer:
This query first calculates the total quantity of each product sold in each state (subquery). Then it selects the product with the maximum sold quantity in each state.
SQL Question 5: What are the three different normal forms?
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 6: Average Quantity of Products Sold Per Order for Church & Dwight
Church & Dwight, a manufacturer of household products, needs to track the performance of their sales. They are particularly interested in the average quantity of products sold per order.
Using the and tables, can you write a SQL query that calculates the average quantity of products sold per order for Church & Dwight?
Example Input:
| order_id | customer_id | order_date | ship_date |
|---|---|---|---|
| 8675 | 154 | 06/12/2022 00:00:00 | 06/15/2022 00:00:00 |
| 9012 | 789 | 06/13/2022 00:00:00 | 06/17/2022 00:00:00 |
| 6903 | 265 | 06/15/2022 00:00:00 | 06/18/2022 00:00:00 |
| 8291 | 178 | 06/18/2022 00:00:00 | 06/20/2022 00:00:00 |
| 7476 | 943 | 06/20/2022 00:00:00 | 06/24/2022 00:00:00 |
Example Input:
| detail_id | order_id | product_id | quantity |
|---|---|---|---|
| 3401 | 8675 | 5001 | 4 |
| 8802 | 8675 | 6985 | 3 |
| 4503 | 9012 | 6985 | 2 |
| 6352 | 6903 | 5001 | 5 |
| 7417 | 8291 | 5001 | 1 |
Answer:
This query first joins the table with the table on the field. Then it groups by and calculates the average for each group using the AVG function. The result is the average quantity of products sold per order.
To practice a very similar question try this interactive Alibaba Compressed Mean Question which is similar for calculating average quantity per order or this Walmart Histogram of Users and Purchases Question which is similar for < Tracking quantity of products bought per order.
SQL Question 7: In what circumstances might you choose to denormalize a database?
Database normalization has several benefits:
-
Reduces Redundancy: Normalization can minimize redundancy by breaking down a larger, general table into smaller, more granular tables. This often reduces the amount of data that needs to be accessed for particular queries, since some duplicated columns can be removed.
-
Improves Data Integrity: Normalization can help to ensure the integrity of the data by minimizing the risk of data inconsistencies and errors. By establishing clear relationships between the tables via primary and foreign keys, and enforcing these constraints, you can have more reliable records and relationships stored in your DB.
-
Improves Performance: Normalization can improve the performance of the database by reducing the amount of data that needs to be stored and accessed in a single table. This results in faster query times and better overall performance.
SQL Question 8: Analyze Sales and Customer Table
We have two tables, and , for the company Church & Dwight. The table contains all transactions that have occurred, and the table contains detailed information about each customer.
The columns of the table are structured as follows:
- sale_id (unique identifier of the sale)
- product_id (unique identifier of the product)
- customer_id (unique identifier of the customer)
- quantity (quantity of the product bought)
- purchase_date (date of the purchase)
The columns of the table are structured as follows:
- customer_id (unique identifier of the customer)
- customer_name (name of the customer)
- customer_email (email of the customer)
Write a query to find the top 5 customers who have made the most purchases, sorted in descending order. The output should include customer name, email, and total quantity bought.
Example Input:
| sale_id | product_id | customer_id | quantity | purchase_date |
|---|---|---|---|---|
| 4567 | 001 | 123 | 5 | 05/01/2022 00:00:00 |
| 4890 | 002 | 456 | 8 | 06/15/2022 00:00:00 |
| 5001 | 003 | 123 | 2 | 07/20/2022 00:00:00 |
| 5342 | 001 | 789 | 10 | 07/25/2022 00:00:00 |
| 6002 | 002 | 123 | 3 | 07/30/2022 00:00:00 |
Example Input:
| customer_id | customer_name | customer_email |
|---|---|---|
| 123 | John Doe | johndoe@gmail.com |
| 456 | Jane Smith | janesmith@gmail.com |
| 789 | Mike Davis | mikedavis@gmail.com |
Answer:
This query joins the and tables on the column, sums up the amount per customer, and retrieves the top 5 customers who bought the most. It displays the , , and bought.
Since join questions come up frequently during SQL interviews, take a stab at an interactive Spotify JOIN SQL question:
SQL Question 9: Calculate the Scaled Rating for Each Product
Company "Church & Dwight" would like to calculate the scaled rating for each of their products. The scaled rating should be a value between 0 and 1, calculated by taking the square root of the average rating, subtracting the minimum rating, and then dividing by the range of the ratings. The company also wants to round this scaled rating value to 2 decimal places.
For this task, assume unique product_ids correspond to unique products, and that the "reviews" table has the following structure:
Example Input:
| review_id | product_id | stars |
|---|---|---|
| 101 | 1 | 5 |
| 102 | 1 | 4 |
| 103 | 1 | 3 |
| 104 | 2 | 2 |
| 105 | 2 | 4 |
| 106 | 2 | 5 |
| 107 | 3 | 1 |
| 108 | 3 | 3 |
| 109 | 3 | 5 |
For each product, calculate the scaled rating as described above.
Answer:
This SQL query works by first grouping the reviews by product and then, within each grouping, calculating two aggregates: the average , and the minimum and maximum . The result of these operations is then used in the expression that calculates the scaled rating. Finally, the type cast and function are used to limit the output to 2 decimal places.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for its requirement of calculating average ratings or this Alibaba Compressed Mean Question which is similar for its need for rounding to a decimal place value.
Church & Dwight SQL Interview Tips
The best way to prepare for a Church & Dwight SQL interview is to practice, practice, practice. Beyond just solving the earlier Church & Dwight SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Google, Microsoft and Silicon Valley startups.
Each interview question has multiple hints, detailed solutions and crucially, there is an online SQL code editor so you can right online code up your query and have it graded.
To prep for the Church & Dwight SQL interview you can also be wise to practice SQL questions from other consumer good companies like:
In case your SQL foundations are weak, forget about going right into solving questions – improve your SQL foundations with this free SQL tutorial.
This tutorial covers things like Union vs. UNION ALL and functions like SUM()/COUNT()/AVG() – both of which show up often in Church & Dwight SQL assessments.
Church & Dwight Data Science Interview Tips
What Do Church & Dwight Data Science Interviews Cover?
Beyond writing SQL queries, the other types of questions to practice for the Church & Dwight Data Science Interview are:
- Statistics & Probability Questions
- Coding Questions in Python or R
- Product Analytics Questions
- ML Modelling Questions
- Behavioral Based Interview Questions
Stay ahead of the curve with Church & Dwight's latest announcements and press releases!
How To Prepare for Church & Dwight Data Science Interviews?
I think the optimal way to prep for Church & Dwight Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
It solves 201 data interview questions taken from FAANG & startups. The book's also got a crash course on SQL, AB Testing & ML. And finally it's helped thousands of people land their dream job in data, which is why it's got over 1000+ 5-star reviews on Amazon.
While the book is more technical, it's also key to prepare for the Church & Dwight behavioral interview. A good place to start is by reading the company's values and company principles.