8 Post Holdings SQL Interview Questions (Updated 2024)
At Post Holdings, SQL is essential for analyzing customer dietary preferences, which helps the company adjust their products to meet consumer needs and trends. They also use SQL to optimize supply chain operations by tracking inventory levels and ensuring timely deliveries from suppliers, which is why Post Holdings asks SQL problems during interviews for Data Science, Data Engineering, and Data Analytics jobs.
Thus, to help prep you for the Post Holdings SQL interview, here's 8 Post Holdings SQL interview questions – can you solve them?
8 Post Holdings SQL Interview Questions
SQL Question 1: Analyzing Sales
As a data analyst at Post Holdings, you have been given two tables - and . The table has information about each purchase including its , , and . The table contains product information such as , , , and . Your task is to write a SQL query to analyze for each product, the total quantity sold, and the total sales for each quarter of 2022, using appropriate window functions.
Example Input:
| sales_id | product_id | sale_date | quantity |
|---|---|---|---|
| 101 | 1 | 01/08/2022 | 20 |
| 102 | 2 | 01/05/2022 | 35 |
| 103 | 1 | 02/10/2022 | 25 |
| 104 | 3 | 03/15/2022 | 15 |
| 105 | 2 | 04/02/2022 | 40 |
Example Input:
| product_id | product_name | category | price |
|---|---|---|---|
| 1 | Product A | Category X | 5 |
| 2 | Product B | Category Y | 8 |
| 3 | Product C | Category Z | 10 |
Example Output:
| quarter | product_name | total_quantity | total_sales |
|---|---|---|---|
| 1 | Product A | 45 | 225 |
| 1 | Product B | 35 | 280 |
| 1 | Product C | 15 | 150 |
| 2 | Product B | 40 | 320 |
Answer:
This answer uses PostgreSQL's window functions to summarize sales data per product and per quarter. The function is used to get the first date of each quarter, and ensures the total quantity and total sales calculations are done per product for each quarter. The function is used in the where clause to filter out sales from 2022. The result set is ordered by quarter and total sales in descending order to identify top-performing products in each quarter.
p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
Explore Post Holdings' press releases to stay informed about their recent developments and strategic initiatives in the food sector! Understanding Post Holdings' actions can give you a clearer picture of how companies are navigating the competitive landscape of food production.
SQL Question 2: Employee Salaries Higher Than Their Manager
Given a table of Post Holdings employee salary data, write a SQL query to find employees who make more money than their direct manager.
Post Holdings Example Input:
| employee_id | name | salary | department_id | manager_id |
|---|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 | |
| 2 | Daniel Rodriguez | 2230 | 1 | 10 |
| 3 | Olivia Smith | 8000 | 1 | 8 |
| 4 | Noah Johnson | 6800 | 2 | 8 |
| 5 | Sophia Martinez | 1750 | 1 | 10 |
| 8 | William Davis | 7000 | 2 | NULL |
| 10 | James Anderson | 4000 | 1 | NULL |
Example Output:
| employee_id | employee_name |
|---|---|
| 3 | Olivia Smith |
This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.
Test your SQL query for this interview question directly within the browser on DataLemur:
Answer:
First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.
If the code above is tough, you can find a step-by-step solution with hints here: Well Paid Employees.
SQL Question 3: What are SQL constraints, and can you give some examples?
In a database, constraints are rules that the DBMS (database management system) follows when performing operations such as inserting, updating, or deleting data.
For example, consider a table of employee records at Post Holdings. Some constraints that you might want to implement include:
- NOT NULL: This constraint ensures that certain columns, such as the employee's first and last name, cannot be NULL.
- UNIQUE: This constraint ensures that each employee has a unique employee ID.
- PRIMARY KEY: This constraint combines the NOT NULL and UNIQUE constraints to create a primary key for the employee table. The primary key is a column or set of columns that uniquely identifies each row in the table.
- FOREIGN KEY: This constraint establishes a relationship between the employee 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 department table to track which department each employee belongs to.
- DEFAULT: This constraint specifies a default value for a column in case no value is specified when a new row is inserted into the table.
SQL Question 4: Product Sales and Distribution by Region
As a business analyst for the Post Holdings, you are tasked with keeping track of the company's sales and stock distribution across various regions in the country. Post Holdings has a wide variety of products in different categories. The company wants to know which product categories are most popular in each region based on the sales data.
A database has been designed to capture all the necessary information. Below are two of the key tables:
Sample Input:
| sale_id | product_id | region_id | sold_date | quantity_sold |
|---|---|---|---|---|
| 101 | 1001 | 1 | 2022/07/01 | 10 |
| 102 | 1002 | 1 | 2022/07/01 | 32 |
| 103 | 1003 | 2 | 2022/07/01 | 20 |
| 104 | 1001 | 2 | 2022/07/01 | 15 |
| 105 | 1002 | 3 | 2022/07/01 | 12 |
Sample Input:
| product_id | product_name | category |
|---|---|---|
| 1001 | Cornflakes | Cereal |
| 1002 | Honey Bunches of Oats | Cereal |
| 1003 | Snickers Protein Bar | Protein Bar |
Based on the and tables, write a SQL query to find out the total quantity of each product category sold in each region for the month of July.
Answer:
This query first joins the and tables on the field. The WHERE clause filters for the sales data from the month of July. The query then groups the results by and and calculates the sum of for each grouping, displaying the total quantity of each product category sold in each region.
SQL Question 5: What's the major difference between and ?
The clause serves as a filter for the groups created by the clause, similar to how the clause filters rows. However, is applied to groups rather than individual rows.
For example, say you were a data analyst at Post Holdings trying to understand how sales differed by region:
This query retrieves the total sales for all products in each region, and uses the clause to only sales made after January 1, 2023. The rows are then grouped by region and the clause filters the groups to include only those with total sales greater than $400,000.
SQL Question 6: Calculate the Average Quantity of Products Sold
Post Holdings is a consumer packaged goods holding company. We'll be interested in the average quantity of each product sold over time.
You are given the table, which logs every single sale made by the company. Each row represents a unique sale and contains the quantity of the product sold. Can you write a SQL query to find the average quantity sold per product_id from the table grouped by the month of ?
Example Input:
| sale_id | product_id | sale_date | quantity |
|---|---|---|---|
| 101 | 2001 | 01/05/2023 | 5 |
| 102 | 2002 | 01/10/2023 | 2 |
| 103 | 2001 | 01/15/2023 | 3 |
| 104 | 2001 | 02/05/2023 | 4 |
| 105 | 2002 | 02/10/2023 | 6 |
Example Output:
| month | product_id | avg_quantity |
|---|---|---|
| 1 | 2001 | 4.00 |
| 1 | 2002 | 2.00 |
| 2 | 2001 | 4.00 |
| 2 | 2002 | 6.00 |
Answer:
This SQL statement uses the AVG function to calculate the average quantity of each product sold, grouped by the month of sale_date and product_id. The EXTRACT function is used to get the month part from the sale_date column. The resulting table shows the average quantity of each product sold per month.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating top products based on sales data or this Amazon Average Review Ratings Question which is similar for calculating averages based on product data.
SQL Question 7: Can you explain the meaning of database denormalization?
Database denormalization is when you add redundancy to a database, and break typical normalization rules (codified by the 1st, 2nd, 3rd normal forms).
Denormalization is typically used to improve the performance of a database, particularly when the database is being for OLAP (Online Analytical Processing) purposes. By denormalizing a database, you can reduce the number of joins that are required to retrieve data, which can greatly improve the speed of queries since joins are costly and slow. However, denormalization can also introduce some problems, such as increased data redundancy and the need for more complex update and delete operations since data has been duplicated into multiple tables.
In general, denormalization should be used with caution and only after careful consideration of the trade-offs involved. It's typically better to start with a well-normalized database design then denormalize only if your database isn't scaling as well as you want.
SQL Question 8: Combining and Analyzing Customer and Product Tables
You have been provided with two tables, and . The table contains customer-related information which includes the customer id, first name and last name. The table contains purchasing information collected from transactions.
The table looks like this:
Example Input:
| customer_id | first_name | last_name |
|---|---|---|
| 4556 | John | Doe |
| 9098 | Jane | Doe |
| 2753 | Bob | Smith |
| 0192 | Alice | Johnson |
| 6701 | Charlie | Brown |
The table looks like this:
Example Input:
| purchase_id | customer_id | product_id | purchase_date | quantity |
|---|---|---|---|---|
| 3301 | 4566 | 68842 | 02/15/2023 | 1 |
| 9205 | 9098 | 50009 | 05/23/2023 | 2 |
| 4280 | 2753 | 69852 | 03/30/2023 | 1 |
| 5281 | 6701 | 50001 | 01/17/2023 | 3 |
| 8290 | 0192 | 69852 | 04/13/2023 | 2 |
Please write a SQL query to bring together the and tables into one. You should keep all the information from both tables. Then, from this combined table, select the customers that have bought 2 or more products, along with their first name, last name, and the total quantity of products they have purchased.
Answer:
In PostgreSQL, your SQL query would look something like this:
This query first executes a operation to bring together the and tables. The keyword is used specify the as the column that should be used for the join. Next, it performs grouping on and fields, so that we get a sum of quantity for each customer. Finally, the clause allows us to filter out groups that have purchased less than 2 items.
Since join questions come up frequently during SQL interviews, take a stab at this Snapchat SQL Interview question using JOINS:
Post Holdings SQL Interview Tips
The best way to prepare for a Post Holdings SQL interview is to practice, practice, practice. In addition to solving the above Post Holdings SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like FAANG tech companies and tech startups.
Each DataLemur SQL question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and most importantly, there's an interactive SQL code editor so you can right in the browser run your SQL query answer and have it checked.
To prep for the Post Holdings SQL interview it is also wise to practice SQL questions from other food and facilities companies like:
- McCormick SQL questions
- Ingredion SQL questions
- J.M. Smucker SQL questions
- Campbell Soup SQL questions
However, if your SQL query skills are weak, don't worry about going right into solving questions – improve your SQL foundations with this SQL interview tutorial.
This tutorial covers things like window functions like RANK() and ROW_NUMBER() and LEAD/LAG – both of which show up routinely in SQL job interviews at Post Holdings.
Post Holdings Data Science Interview Tips
What Do Post Holdings Data Science Interviews Cover?
Beyond writing SQL queries, the other types of problems to prepare for the Post Holdings Data Science Interview are:
- Probability & Statistics Questions
- Python or R Programming Questions
- Business Sense and Product-Sense Questions
- ML Modelling Questions
- Behavioral Interview Questions focussed on Post Holdings cultural values
How To Prepare for Post Holdings Data Science Interviews?
To prepare for Post Holdings Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from Facebook, Google, & Amazon
- a crash course covering SQL, Product-Sense & ML
- over 1000+ reviews on Amazon & 4.5-star rating
Also focus on the behavioral interview – prepare for it using this list of common Data Scientist behavioral interview questions.