8 MSC Industrial Direct SQL Interview Questions (Updated 2024)
At MSC Industrial Direct, SQL is used to analyze sales patterns to forecast demand accurately, helping the team understand which products are likely to be in high demand during specific seasons. They also manage supply chain data with SQL to optimize inventory levels, ensuring they have the right amount of stock on hand to meet customer needs, this is why MSC Industrial Direct asks SQL questions in interviews for Data Analytics, Data Science, and Data Engineering jobs.
Thus, to help you prep, here's 8 MSC Industrial Direct SQL interview questions – can you answer each one?
8 MSC Industrial Direct SQL Interview Questions
SQL Question 1: Identify Top Buyers at MSC Industrial Direct
MSC Industrial Direct is a distributor of industrial tools and supplies. The and tables in their database record details about every purchase made by users.
The table is structured as follows:
| purchase_id | user_id | purchase_date | product_id | amount_paid |
|---|---|---|---|---|
| 3154 | 234 | 06/08/2022 00:00:00 | 57001 | 300.00 |
| 1142 | 897 | 06/10/2022 00:00:00 | 75002 | 500.00 |
| 5132 | 764 | 06/18/2022 00:00:00 | 57001 | 250.00 |
| 7215 | 417 | 07/26/2022 00:00:00 | 75002 | 350.00 |
| 2317 | 641 | 07/05/2022 00:00:00 | 75002 | 400.00 |
The table is structured as follows:
| user_id | first_name | last_name | join_date |
|---|---|---|---|
| 234 | John | Doe | 01/01/2020 00:00:00 |
| 897 | Jane | Smith | 01/01/2021 00:00:00 |
| 764 | Emily | Johnson | 01/01/2020 00:00:00 |
| 417 | David | Williams | 01/01/2021 00:00:00 |
| 641 | Jack | Brown | 01/01/2020 00:00:00 |
Your task is to write a query to identify the top 5 users who have made the highest total purchases in the past month. The result should list the user_id, first_name, last_name, and total amount spent.
Hint: You will need to use the and functions.
Answer:
This query firstly selects users in the purchases table who made purchases within the last month. It then sums the amount paid by each user and joins with the users table to get the user details. The results are grouped by user and arranged in descending order of total amount spent. The at the end ensures only the top 5 users are returned.
To work on another SQL customer analytics question where you can code right in the browser and have your SQL query instantly graded, try this Walmart SQL Interview Question:
Discover how MSC Industrial Direct is leveraging data analytics to improve efficiency in their operations! Understanding MSC's strategies can give you a better perspective on how data-driven decisions are enhancing productivity in the industrial sector.
SQL Question 2: 2nd Largest Salary
Suppose there was a table of MSC Industrial Direct employee salary data. Write a SQL query to find the 2nd highest salary among all employees.
MSC Industrial Direct Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
You can solve this interview question and run your code right in the browser:
Answer:
You can find a step-by-step solution here: 2nd Highest Salary.
SQL Question 3: Can you explain what SQL constraints are, and why they are useful?
Constraints are just rules your DBMS has to follow when updating/inserting/deleting data.
Say you had a table of MSC Industrial Direct products and a table of MSC Industrial Direct customers. Here's some example SQL constraints you'd use:
NOT NULL: This constraint could be used to ensure that certain columns in the and tables, such as the product name and customer email address, cannot contain NULL values.
UNIQUE: This constraint could be used to ensure that the product IDs and customer IDs are unique. This would prevent duplicate entries in the respective tables.
PRIMARY KEY: This constraint could be used to combine the and constraints to create a primary key for each table. The product ID or customer ID could serve as the primary key.
FOREIGN KEY: This constraint could be used to establish relationships between the MSC Industrial Direct product and customer tables. For example, you could use a foreign key to link the customer ID in the table to the customer ID in the table to track which products each customer has purchased.
CHECK: This constraint could be used to ensure that certain data meets specific conditions. For example, you could use a constraint to ensure that MSC Industrial Direct product prices are always positive numbers.
DEFAULT: This constraint could be used to specify default values for certain columns. For example, you could use a constraint to set the customer registration date to the current date if no value is provided when a new customer is added to the database.
SQL Question 4: Sales and Quantity Analysis over Time
MSC Industrial Direct is interested in analyzing their sales over time. They would like to see the total sales and total quantity sold for each product grouped by month and year.
Using the table below as your source, can you help write a SQL query that calculates the total sales and quantity sold for each product id per month-year? Also, construct a window function to calculate the running total sales for each product over all time.
Sample Input:
| sale_id | product_id | sale_date | quantity | net_sales |
|---|---|---|---|---|
| 1 | A100 | 01/03/2021 | 5 | 250 |
| 2 | B200 | 01/05/2021 | 3 | 900 |
| 3 | A100 | 02/01/2021 | 2 | 100 |
| 4 | B200 | 03/01/2021 | 1 | 300 |
| 5 | C300 | 04/01/2021 | 4 | 400 |
Example Output:
| year_month | product_id | total_quantity | total_sales | running_total_sales |
|---|---|---|---|---|
| 2021-01 | A100 | 5 | 250 | 250 |
| 2021-01 | B200 | 3 | 900 | 900 |
| 2021-02 | A100 | 2 | 100 | 350 |
| 2021-03 | B200 | 1 | 300 | 1200 |
| 2021-04 | C300 | 4 | 400 | 400 |
Answer:
This query groups the sales data by year-month and product id, and then sums up the quantities sold and net sales for each group. It uses a window function, , to calculate the running total of net sales for each product over all time, partitioned by product and sorted by date. The clause in the window function ensures that the running total includes all rows from the start of the table to the current row.
p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: What are the similarities and difference between relational and NoSQL databases?
While both types of databases are used to store data (no duh!), relational databases and non-relational (also known as NoSQL databases) differ in a few important ways:
Data model: Relational databases use a data model consisting of tables and rows, while NoSQL databases use a variety of data models, including document, key-value, columnar, and graph storage formats.
Data integrity: Relational databases use structured query language (SQL) and enforce strict data integrity rules through the use of foreign keys and transactions. NoSQL databases may not use SQL and may have more relaxed data integrity rules.
Structure: Relational databases store data in a fixed, structured format, while NoSQL databases allow for more flexibility in terms of data structure.
ACID compliance: Relational databases are typically into shrooms and are ACID-compliant (atomic, consistent, isolated, and durable), while NoSQL databases may not be fully ACID-compliant (but they try their best... and it's effort that counts...or at least that's what my gym teacher told me!)
SQL Question 6: Analyzing Product Sales and Returns
MSC Industrial Direct, a distributor of industrial accessories and supplies, keeps track of all its sales records. You have been asked to create a database design for tracking the sales and returns of its products.
Part A: Create the table structure and relationships for keeping track of product sales, returns and other relevant product details.
Part B: Write a SQL query to calculate the total sales and returns for each product for a given year.
Sample Tables:
Example Input:
| product_id | product_name | description |
|---|---|---|
| 1001 | Drill | High-speed steel drill |
| 1002 | Hammer | Industrial hammer |
| 1003 | Wrench | Adjustable wrench |
Example Input:
| sales_id | product_id | purchase_date | quantity |
|---|---|---|---|
| 6572 | 1001 | 01/15/2022 | 200 |
| 9324 | 1002 | 02/20/2022 | 100 |
| 6793 | 1003 | 03/25/2022 | 75 |
Example Input:
| return_id | product_id | return_date | quantity |
|---|---|---|---|
| 4517 | 1001 | 03/10/2022 | 20 |
| 2981 | 1002 | 04/05/2022 | 10 |
| 9723 | 1003 | 05/01/2022 | 5 |
Answer:
This PostgreSQL query joins the , , and tables on and filters the returns based on the date range of 1 year from the purchase date for each product. The results are further filtered for the year 2022 with the function. The function is used to calculate the total sales and returns for each product. The function is used to handle NULL values that can arise if a product has no returns in the given year. The query finally calculates the net sales for each product.
SQL Question 7: What's a database view?
A database view is a virtual table that is created based on the results of a SELECT statement, and provides you a customized, read-only version of your data that you can query just like a regular table.
Views in SQL can help you enforce data security requirements by hiding sensitive data from certain users, and can improve performance for some queries by pre-computing the results for an intermediate step and storing them in a view (which can be faster than executing the intermediate query each time). However, their read-only nature means that on any underlying update, the view has to be re-computed.
SQL Question 8: Calculate the Average Order Quantity Per Business
MSC Industrial Direct is a distributor of industrial tools and supplies. As part of ongoing business analysis, they are interested in understanding the average quantity of items ordered by each business client within a given year. They have a table, 'orders', that contains information about each order placed by their clients.
Create a SQL query to calculate the average quantity of items ordered per business in the year 2022.
Example Input:
| order_id | business_id | order_date | product_id | quantity |
|---|---|---|---|---|
| 1051 | 1132 | 02/05/2022 00:00:00 | 30001 | 5 |
| 1620 | 1236 | 03/01/2022 00:00:00 | 49872 | 7 |
| 3793 | 1132 | 04/07/2022 00:00:00 | 30001 | 6 |
| 3632 | 1812 | 05/18/2022 00:00:00 | 49872 | 3 |
| 9017 | 2381 | 06/09/2022 00:00:00 | 49872 | 2 |
Example Output:
| business_id | avg_quantity |
|---|---|
| 1132 | 5.50 |
| 1236 | 7.00 |
| 1812 | 3.00 |
| 2381 | 2.00 |
Answer:
In PostgreSQL:
This query first filters for orders made in the year 2022. It then groups the data by business id, and calculates the average order quantity for each business.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for needing to analyze item quantities or this Alibaba Compressed Mean Question which is similar for calculating average item orders.
How To Prepare for the MSC Industrial Direct SQL Interview
The best way to prepare for a MSC Industrial Direct SQL interview is to practice, practice, practice. Besides solving the above MSC Industrial Direct SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Microsoft, Google, Amazon, and tech startups.
Each problem on DataLemur has hints to guide you, full answers and crucially, there's an interactive SQL code editor so you can right in the browser run your query and have it checked.
To prep for the MSC Industrial Direct SQL interview you can also be useful to solve interview questions from other industrial and electrical distribution companies like:
In case your SQL coding skills are weak, don't worry about diving straight into solving questions – go learn SQL with this free SQL tutorial.
This tutorial covers topics including filtering with LIKE and cleaning text data – both of which come up often during SQL job interviews at MSC Industrial Direct.
MSC Industrial Direct Data Science Interview Tips
What Do MSC Industrial Direct Data Science Interviews Cover?
Beyond writing SQL queries, the other types of questions to prepare for the MSC Industrial Direct Data Science Interview include:
- Probability & Stats Questions
- Python Pandas or R Coding Questions
- Product Analytics Questions
- ML Interview Questions
- Behavioral Based Interview Questions
How To Prepare for MSC Industrial Direct Data Science Interviews?
To prepare for the MSC Industrial Direct Data Science interview make sure you have a strong understanding of the company's cultural values – this will be clutch for acing the behavioral interview. For technical interviews prepare by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG, tech startups, and Wall Street
- A Crash Course on Python, SQL & ML
- Amazing Reviews (1000+ 5-star reviews on Amazon)