10 SPS Commerce SQL Interview Questions (Updated 2024)

Updated on

March 2, 2024

At SPS Commerce, SQL is crucial for analyzing retail performance metrics and managing complex data relationships within the supply chain network. That's why SPS Commerce asks SQL query questions in interviews for Data Science, Data Engineering and Data Analytics jobs.

As such, to help you prepare for the SPS Commerce SQL interview, here’s 10 SPS Commerce SQL interview questions – able to solve them?

10 SPS Commerce SQL Interview Questions

SQL Question 1: Identifying Power Users at SPS Commerce

SPS Commerce is a supply chain software company that helps businesses in achieving their goals with retail solutions. One of their key performance indicators (KPI) could be the number of transactions processed per customer. For this scenario, a power user or VIP user would be considered as a user who makes the most transactions.

Assume you have access to the table of SPS Commerce's product which includes the fields 'transaction_id', 'customer_id', 'transaction_date' and 'amount'. Identify the power users who have made more than 100 transactions in the last year.

Example Input:


This query identifies the power users by counting the number of transactions each customer has made over the past year. Any user with more than 100 transactions appears in the result set, which is ordered in descending order by the number of transactions to highlight the top power users.

To work on another SQL customer analytics question where you can code right in the browser and have your SQL query instantly executed, try this Walmart Labs SQL Interview Question: Walmart SQL Interview Question

SQL Question 2: User Monthly Activity

SPS Commerce wishes to understand user activity better and maintain monthly active user counts for each of their products. We define an active user for a month as a user who has submitted a review on a product within that month.

Write a SQL query in PostgreSQL that generates a report showing the number of unique active users for each product, per month.

Here are the tables for the user review data:

Example Input:
617112306/08/2022 00:00:0050001
780226506/10/2022 00:00:0069852
529336206/18/2022 00:00:0050001
635219207/26/2022 00:00:0069852
451798107/05/2022 00:00:0069852

We want to output a table in the following format:

Example Output:


Here's a PostgreSQL query:

This query works by first converting the timestamp to a month number using the function. It then groups the results by both and .

The within each group gives us the number of unique active users for each product per month. This value is selected as .

The clause then ensures the final result table is sorted first by month, and then by product_id for easy reading and comparison.

To solve a related window function SQL problem on DataLemur's free interactive SQL code editor, solve this Google SQL Interview Question: Google SQL Interview Question

SQL Question 3: What's a stored procedure?

Stored procedures are a lot like functions in programming. They're used to encapsulate and organize business logic into one unit of code, and they can accept multiple input parameters and return multiple output values.

For example, if you were a Data Analyst at SPS Commerce working on a HR analytics project, you might create a stored procedure to calculate the average salary for a given department:

To call this stored procedure and find the average salary for the Data Analytics department you'd write the following query:

SPS Commerce SQL Interview Questions

SQL Question 4: Retailer Relationship Analysis

As a retail-focused company, SPS Commerce is interested in understanding the relationship between retailers and suppliers. Specifically, they are interested in understanding the span of product categories that a supplier provides to each retailer, and the total dollar amount of transactions occurring within each of these relationships.

For this task, we have 3 relevant tables: ,, and .

table has columns and .

table has columns , , .

table has columns , , , , .

Example Input:
Example Input:
103SuperStuffSporting Goods
Example Input:


Here is a SQL query that will provide a breakdown of each retailer, the suppliers that they work with, and the total amount of transaction.

This query does a JOIN on the , , and tables, and then groups the results by , , and . The function is used to calculate the total sales for each grouping. The results are ordered by and then by in descending order. This will give the company a rundown of supplier-retailer relationships and the value of transactions for each.

SQL Question 5: What's the difference between window functions and ?

While both and are used to rank rows, the key difference is in how they deal with ties.

RANK(): When there's a tie, leaves a gap in the ranking. For example, if three rows are tied for 2nd place, the RANK() function will assign a rank of 2 to the first of these rows, a rank of 3 to the 2nd row in the tie, and a rank of 4 to the the 3rd tie.

DENSE_RANK(): For ties, does not leave a gap in the ranking. Instead, it assigns the same rank to all tied rows, and then makes the next row 1 bigger. Confusing, I know, but here's an example to make it more clear: if three rows are tied for 3rd place, the function will assign a rank of 3 to all three rows, and then assign a rank of 4 to the next row.

Suppose we had data on how many deals different salespeople at SPS Commerce closed, and wanted to rank the salespeople.

The result of this query would be:


As you can see, the function assigns a rank of 1 to the first row (Akash), a rank of 2 to the second row (Brittany), and so on. In contrast, the , gives both Akash and Brittany a rank of 1, since they are tied, then moves on to rank 2 for Carlos.

SQL Question 6: Retailer transaction filtering

Suppose SPS Commerce is conducting an analysis of its retailer transactions to identify the transactions of retailers who have been active during the year 2022 but have not made any purchases for the last two months. Clearly, the and tables are defined with the below schemas.

Example Input:
211Retailer A01/05/2020
578Retailer B02/01/2021
705Retailer C06/15/2022
909Retailer D12/20/2019
368Retailer E07/26/2021
Example Input:

The date provided by the transaction table is in 'MM/DD/YYYY' format.

Write a SQL command that will return the and of retailers who have done transactions in 2022, but who have not made any transactions in the last two months.


In the above query, we first filter out the retailer ID's from the transactions table which have made transactions in the year 2022. Then from that set, we are excluding the retailers who have made transactions in the last two months. This will give us all the retailer's ID's who have not made transactions in the last two months but were previously active in 2022. We then use these ID's to filter out retailer data from the retailers table.

SQL Question 7: What is the purpose of the SQL constraint ?


A UNIQUE constraint ensures that all values in a column are different. This provides uniqueness for the column(s) and helps identify each row uniquely. Unlike primary key, there can be multiple unique constraints defined per table.

SQL Question 8: Average number of transactions per vendor

SPS Commerce is a cloud-based supply chain management company which facilitates the trading of consumer goods among suppliers and retailers. For this role, you'll often need to work with transaction data. Given a table of transactions, find the average number of transactions per vendor.

Sample Input:
Example Output:


This SQL query counts the number of transactions for each vendor (GROUP BY vendor_id) and returns the vendor_id along with this count value. Average (AVG) is generally used when we have to calculate a single value that represents the "typical" value from multiple different values (such as the average rating or price). In this scenario, we're counting how many transactions each vendor has, so we use COUNT(*) instead.

To practice a very similar question try this interactive Twitter Histogram of Tweets Question which is similar for requiring SQL grouping or this Walmart Histogram of Users and Purchases Question which is similar for involving transaction analysis.

SQL Question 9: Finding Customers from Minneapolis

As an e-commerce company, SPS Commerce interacts with customers from various cities around the globe. For this exercise, the company wants to filter their customer records data to find all customers living in Minneapolis.

The task is to write an SQL query to extract all customer records where the city is 'Minneapolis'. The customer records are stored in a table called 'Customers'.

Example Input:
105MaryJonesmjones@example.comSan Francisco
Example Output:


The SQL query provided will scan the table 'Customers' and return all rows where the 'City' column value matches the string 'Minneapolis'. Thus, the answer will be customers living in Minneapolis.

SQL Question 10: How do you determine which records in one table are not present in a second table?

To find records in one table that aren't in another, you can use a and check for values in the right-side table.

Here is an example using two tables, SPS Commerce employees and SPS Commerce managers:

This will return all rows from SPS Commerce employees where there is no matching row in managers based on the column.

You can also use the operator in PostgreSQL and Microsoft SQL Server to return the records that are in the first table but not in the second. Here is an example:

This will retrieve all rows from employees that do not appear in managers. The operator works by retreivingthe rows that are returned by the first query, but not by the second.

Please note that is not supported by all DBMS systems, such as MySQL and Oracle (however, you can use the operator to achieve a similar outcome).

Preparing For The SPS Commerce SQL Interview

The best way to prepare for a SPS Commerce SQL interview is to practice, practice, practice. Beyond just solving the earlier SPS Commerce SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Microsoft, Google, Amazon, and tech startups. DataLemur SQL and Data Science Interview Questions

Each exercise has multiple hints, full answers and most importantly, there's an online SQL code editor so you can right in the browser run your SQL query answer and have it graded.

To prep for the SPS Commerce SQL interview you can also be a great idea to practice SQL questions from other tech companies like:

However, if your SQL foundations are weak, forget about going right into solving questions – go learn SQL with this free SQL tutorial.

DataLemur SQL Tutorial for Data Science

This tutorial covers SQL topics like handling timestamps and LEAD/LAG window functions – both of these come up often in SQL interviews at SPS Commerce.

SPS Commerce Data Science Interview Tips

What Do SPS Commerce Data Science Interviews Cover?

In addition to SQL query questions, the other topics to practice for the SPS Commerce Data Science Interview are:

SPS Commerce Data Scientist

How To Prepare for SPS Commerce Data Science Interviews?

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

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