10 McCormick SQL Interview Questions (Updated 2024)

At McCormick, SQL is essential for analyzing sales trends for various spices, allowing the company to understand customer preferences and adjust their products accordingly. They also use SQL to optimize their supply chain by checking the availability of materials from different suppliers, ensuring they can meet production demands without delays, which is why McCormick uses SQL problems in interviews for Data Science and Data Engineering positions.

So, to help you prep, we've collected 10 McCormick SQL interview questions – how many can you solve?

10 McCormick SQL Interview Questions

SQL Question 1: Finding VIP Customers at McCormick

McCormick is a food manufacturing company and the customer database contains customers who have made different types and quantities of purchases over time. A VIP customer, in this context, could be someone who has made higher value purchases or more frequent purchases.

In this question, we will identify the VIP users as those who have made purchases with a total cost that is above a certain threshold within the last year.

Given two tables - one containing the details of the customers and one containing the details of transactions made by these customers - write a SQL query to fetch the details of the VIP customers (customers who made more than $5000 worth of purchases in the last year).

Example Input:

Example Input:

Answer:

In this query, we first filter out the transactions that happened in the last year and then group by the customer_id. We calculate the total amount spent by each customer within this filtered and grouped set. If this sum is greater than $5000, we select that customer's ID. Finally, we use this list of customer IDs to get the details of these customers from the customer table.

To solve a similar VIP customer analysis question on DataLemur's free interactive coding environment, try this Microsoft SQL Interview problem:

Discover the latest news releases from McCormick to see how they are enhancing flavors and innovating in the spice and seasoning industry! Keeping up with McCormick's updates can provide insights into how a leading brand is responding to consumer tastes and trends.

SQL Question 2: Top 3 Department Salaries

Imagine you had a table of McCormick employee salary data. Write a SQL query to find the top 3 highest paid employees within each department.

McCormick Example Input:

Example Input:

Example Output:

You can solve this problem and run your code right in DataLemur's online SQL environment:

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 solution above is tough, you can find a detailed solution here: Top 3 Department Salaries.

SQL Question 3: What is the purpose of the UNIQUE constraint?

The UNIQUE constraint is used to ensure the uniqueness of the data in a column or set of columns in a table. It prevents the insertion of duplicate values in the specified column or columns and helps to ensure the integrity and reliability of the data in the database.

For example, say you were on the Marketing Analytics team at McCormick and were doing some automated keyword research:

Your keyword database might store SEO data like this:

In this example, the UNIQUE constraint is applied to the "keyword" field to ensure that each keyword is unique. This helps to ensure the integrity of the data in the database and prevents errors that could occur if two rows had the same keyword.

SQL Question 4: Calculate Month-over-Month Average Review Star Rating

McCormick, a multinational food company, has a database that captures all the user reviews for their products. Each review comes with a star rating. For each product, they want to see how their average review star rating changes month by month.

Example Input:

Expected Output:

Answer:

To solve the problem we can use the function to get the month from the and then group by the product_id and month to get the average stars for each product per month.

This query will give the average review star rating for each product for each month. The statement groups the data by product and month, and the generates the average star rating for each group. The will present the result in ascending order first by month and then by product.

To practice a related window function SQL problem on DataLemur's free interactive coding environment, try this Google SQL Interview Question:

SQL Question 5: When would you use the function?

The function is used to remove NULLs, and replace them with another value.

For example, say you were a Data Analyst at McCormick and were doing a customer analytics project to see who the most marketing-engaged customers were, and had access to the below table.

mccormick_customers:

Before you could procede, you had to remove the NULLs, and replace them with the default value (not_active for email, and not_opted_in for SMS). To do this, you'd run the following query:

This would get you the following output:

SQL Question 6: Analyze Sales of McCormick Spices

As part of McCormick's marketing team, your task is to analyze the previous month's sales data to identify trends and make further recommendations. Specifically, you need to find out the total quantity sold and average unit price for each product, but only for the customers who are located in 'New York' and whose total purchase amount last month exceeded 1000 dollars.

Sample Input:

Sample Input:

Sample Input:

Example Output:

Answer:

The above query joins the , , and tables and applies the filtering conditions on the city and the total purchase amount. It calculates the total quantity and average unit price for each product from the filtered result and orders by total quantity in descending order.

SQL Question 7: 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 McCormick employees, and their salaries, job titles, and performance review data. Here's some examples of SQL constraints you could implement:

NOT NULL: This constraint could be used to ensure that certain columns in the employee table, such as the employee's first and last name, cannot contain NULL values.

UNIQUE: This constraint could be used to ensure that the employee ID is unique. This would prevent duplicate entries in the employee table.

PRIMARY KEY: This constraint could be used to combine the NOT NULL and UNIQUE constraints to create a primary key for the employee table. The employee ID could serve as the primary key.

FOREIGN KEY: This constraint could be used to establish relationships 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.

CHECK: This constraint could be used to ensure that certain data meets specific conditions. For example, you could use a CHECK constraint to ensure that salary values are always positive numbers.

DEFAULT: This constraint could be used to specify default values for certain columns. For example, you could use a DEFAULT 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. Sure, let's create a click-through-rate related SQL interview question for a company such as McCormick. Let's assume that McCormick has an e-commerce site where they sell their spices and seasonings.

SQL Question 8: Calculate Ad Click-through and Checkout Conversion Rate

You are given two Postgres tables - and that track the user interactions with digital ads and their cart status for McCormick's online spice store.

table:

table:

The question is to calculate the click-through conversion rate per product - this is defined as the number of users who clicked an ad, and subsequently checkout the same product, divided by the total number of users who clicked the ad of the same product.

Answer:

This query first joins any matched records from the and tables based on the and . The use of ensures that all from table are present in the output. Then, it calculates the conversion rate as the ratio of distinct users who both clicked and checked out the same product to all the distinct users who clicked the product ad.

To solve a similar problem about calculating rates, try this TikTok SQL Interview Question within DataLemur's interactive coding environment:

SQL Question 9: Filtering Customer Records

As a data analyst at McCormick, you are tasked with the responsibility of customer profiling. You have been asked to identify all customers whose first name starts with 'J' and resides in 'California'. The ultimate aim is to launch a targeted advertising campaign for a new product.

Here's a sample of the data you have in the table:

Example Input:

Write a SQL query that selects the , and of customers whose first name starts with and are residing in .

Answer:

Here, we are using along with a pattern (), which would return all customer names starting with the letter 'J'. The is a wildcard that matches any characters following the letter 'J'. This query filters the table for customers whose first name starts with 'J' and are living in 'California'.

SQL Question 10: What sets relational and NoSQL databases apart?

While both types of databases are used to store data (obviously), there's some key differences in how they store and organize data.

Relational databases try to represent the world into neat little tables, with rows and columns. Non-relational (NoSQL) databases use a variety of data models to represent data, including document, key-value, columnar, and graph storage formats.

While the exact types of NoSQL databases is beyond the scope of a Data Analyst and Data Scientist SQL interview at McCormick, it's good to know that companies generally choose to use NoSQL databases:

• when dealing with unstructured or semi-structured data
• when the database needs to be scaled horizontally easily
• when the data is non-relational (like storing social network data which makes more sense in a graph format)

Preparing For The McCormick SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the McCormick SQL interview is to solve as many practice SQL interview questions as you can! In addition to solving the above McCormick SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Netflix, Airbnb, and Amazon.

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 is an online SQL code editor so you can right in the browser run your SQL query and have it checked.

To prep for the McCormick SQL interview you can also be useful to solve SQL problems from other food and facilities companies like:

• Ingredion SQL questions
• J.M. Smucker SQL questions
• Campbell Soup SQL questions
• Constellation Brands SQL questions

But if your SQL skills are weak, forget about diving straight into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.

This tutorial covers topics including aggreage functions like MIN()/MAX() and manipulating date/time data – both of which pop up frequently in SQL interviews at McCormick.

McCormick Data Science Interview Tips

What Do McCormick Data Science Interviews Cover?

Beyond writing SQL queries, the other types of problems tested in the McCormick Data Science Interview include:

• AB Testing & Experimentation Questions
• Python or R Coding Questions
• Product Data Science Interview Questions
• Machine Learning Questions
• Behavioral Interview Questions centered on McCormick company values

How To Prepare for McCormick Data Science Interviews?

To prepare for McCormick Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions sourced from companies like Microsoft, Google & Amazon
• a crash course on SQL, Product-Sense & ML
• over 1000+ 5-star reviews on Amazon

Also focus on the behavioral interview – prep for that using this guide on behavioral interview questions.