8 AvidXchange SQL Interview Questions (Updated 2024)
At AvidXchange, SQL is used frequently for analyzing payment process data for efficiency improvements, and for finding fraud in Accounts Payable transactions. Unsurprisingly this is why AvidXchange typically asks SQL questions during interviews for Data Analyst, Data Science, and BI jobs.
So, to help you prepare for the AvidXchange SQL interview, here’s 8 AvidXchange SQL interview questions – able to answer them all?
8 AvidXchange SQL Interview Questions
SQL Question 1: Analyze Power Users for AvidXchange
We would like to identify our power users, who are the customers that frequently process payments through our system. A power user is defined as a customer who has processed more than 100 payments in a month. Write a SQL query to analyse purchase database to find these power users.
Assuming we have a table with the following schema:
Example Input:
| payment_id | customer_id | process_date | amount |
|---|---|---|---|
| 101 | 765 | 2022-05-23 00:00:00 | 200.55 |
| 102 | 234 | 2022-05-24 00:00:00 | 534.32 |
| 103 | 765 | 2022-05-25 00:00:00 | 300.10 |
| 104 | 765 | 2022-05-26 00:00:00 | 100.00 |
| 105 | 980 | 2022-05-26 00:00:00 | 543.21 |
The resultant data should return the customer_id's who have processed more than 100 payments in any given month and overall volume of payments they processed in that month.
Example Output:
| month | year | customer_id | payment_count | total_volume |
|---|---|---|---|---|
| 5 | 2022 | 765 | 132 | 10000.21 |
Answer:
You can write the SQL query using a combination of DATE_TRUNC, COUNT, GROUP BY, and HAVING. It would look something like this:
This SQL query works by grouping the data by month (obtained by DATE_TRUNC function) and customer_id, then it counts the number of payments made by each customer in every month, and sums up the total payment amount in each month. It then filters for customers who made more than 100 payments in any given month.
To practice another SQL customer analytics question where you can solve it interactively and have your SQL code instantly executed, try this Walmart Labs SQL Interview Question:
SQL Question 2: Analyze Monthly Payments
Given a table detailing payments made by customers for AvidXchange's financial software, write a SQL query to analyze the monthly trends in payments.
Assume the payments table has the following columns: (unique identifier for the payment), (identifier for the customer), (date the payment was made), and (amount of payment).
Your task is to write a SQL query to find the total payment for each customer each month, and the percentage change from the previous month. If there were no payments in the previous month, treat the percentage change as the full amount (or 100%).
Example Input:
| payment_id | customer_id | payment_date | amount |
|---|---|---|---|
| 4321 | 111 | 08/10/2022 | 250 |
| 5678 | 111 | 08/25/2022 | 200 |
| 9021 | 222 | 08/18/2022 | 300 |
| 3567 | 111 | 09/12/2022 | 350 |
| 7891 | 222 | 09/30/2022 | 500 |
| 4567 | 111 | 10/10/2022 | 100 |
Example Output:
| yr | mth | customer_id | total_payment | percentage_change |
|---|---|---|---|---|
| 2022 | 8 | 111 | 450 | 100.00% |
| 2022 | 8 | 222 | 300 | 100.00% |
| 2022 | 9 | 111 | 350 | -22.22% |
| 2022 | 9 | 222 | 500 | 66.67% |
| 2022 | 10 | 111 | 100 | -71.43% |
| 2022 | 10 | 222 | 0 | -100.00% |
Answer:
In the given SQL code, we use the window function to retrieve the previous month's total payment for each customer_id. Then, percentage change is calculated by comparing it with the current month's total payment. In case of no previous month’s payment, the percentage change is set to 100%. The result is then ordered by year, month and customer id.
p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 3: DBMS transactions are expected to follow the ACID properties. What are they, and what does each property mean?
To ensure the reliability and integrity of data, a database management system (DBMS) strives to maintain the ACID properties: Atomicity, Consistency, Isolation, and Durability. To illustrate these concepts, consider the following examples of how ACID properties apply to banking transactions:
- Atomicity: A transaction is either completed in full or not at all. For example, if a customer is transferring money between accounts, the transaction should either transfer the entire amount or none at all.
- Consistency: A transaction is only allowed to complete if it follows all rules and constraints within the database. For example, if a customer is withdrawing money from an account, the transaction should only be allowed to proceed if there are sufficient funds available. Otherwise, the transaction is rejected.
- Isolation: Concurrent transactions are kept separate from each other, so that the changes made by one transaction cannot be seen by another transaction until the first one is complete. This helps prevent conflicts, such as two customers attempting to withdraw money from the same account at the same time.
- Durability: Once a transaction has been committed and completed, the changes made by the transaction are permanently stored in the database and will not be lost even if the database or system crashes. For example, if a customer makes a deposit, the transaction should be durable so that the deposit is not lost in the event of a system failure.
SQL Question 4: Find the total payment amount for each client per month
AvidXchange is focused on automating invoice and payment processes. Let's assume that they have records of payments they've administered on behalf of their clients. The data set contains each payment's unique identifier, the client who made the payment, the date of the payment, and the amount of the payment.
Find the total amount each client paid per month.
Example Input:
| payment_id | client_id | payment_date | amount |
|---|---|---|---|
| 52001 | 111 | 2022-06-20 | 500 |
| 78599 | 222 | 2022-06-8 | 300 |
| 53001 | 111 | 2022-06-15 | 200 |
| 63215 | 222 | 2022-07-12 | 100 |
| 45701 | 333 | 2022-07-24 | 250 |
Example Output:
| month | client | total_amount |
|---|---|---|
| 6 | 111 | 700 |
| 6 | 222 | 300 |
| 7 | 222 | 100 |
| 7 | 333 | 250 |
Answer:
This PostgreSQL query will display the total amount each client paid per month. It extracts the month from the payment_date using the function, groups the rows by the month and the client_id, and then sums up the amount for each group. The function is an aggregate function that calculates the total amount of payments for each client in each month. The statement is utilized to group the payments by the month and client_id. Finally, the result is ordered by month and client_id.
SQL Question 5: What is a self-join?
A self-join is a type of JOIN where a table is joined to itself. To execute a self-join, you must include the table name twice in the FROM clause and assign a different alias to each instance. You can then join the two copies of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.
One common use case for self-joins is to compare data within a single table. For example, you might use a self-join to compare the salaries of employees within the same department, or to identify pairs of products that are frequently purchased together (like in this real Walmart SQL interview question)[https://datalemur.com/questions/frequently-purchased-pairs].
For a more concrete example, imagine you had website visitor data for AvidXchange, exported from the company's Google Analytics account. To help the web-dev team, you needed to analyze pairs of pages for UX or navigational issues. As part of that analysis, you wanted to produce all pairs of URLs, but needed to exclude pairs where both URLs were the same since that is not a valid pair.
You could use the following self-join:
This query retrieves the url of each page () along with the url of the page that referred to it (). The self-join is performed using the , which identifies the id of the page that referred the visitor to the current page, and excludes any pages that referred to themselves (i.e., data anomalies since pages shouldn't refer to themself).
SQL Question 6: Analyzing customers' purchases and payments
The 'Customer' table in the AvidXchange database records all customers' information, including , and .
Example Input:
| customer_id | customer_name | region |
|---|---|---|
| 1001 | John Smith | West |
| 1002 | Sarah Johnson | East |
| 1003 | James Williams | North |
| 1004 | Patricia Brown | South |
The 'Purchases' table registers all transactions made by these customers, tagged by , , and .
Example Input:
| purchase_id | customer_id | item_id | amount |
|---|---|---|---|
| 1501 | 1001 | 5001 | 100.00 |
| 1502 | 1002 | 5002 | 150.00 |
| 1503 | 1001 | 5002 | 200.00 |
| 1504 | 1003 | 5001 | 75.00 |
| 1505 | 1002 | 5001 | 145.00 |
The 'Payments' table records all payments made by these customers for their purchases, tagged by , , and .
Example Input:
| payment_id | customer_id | purchase_id | payment_date |
|---|---|---|---|
| 2001 | 1001 | 1501 | 06/08/2022 |
| 2002 | 1002 | 1502 | 06/10/2022 |
| 2003 | 1001 | 1503 | 06/18/2022 |
| 2004 | 1003 | 1504 | 07/26/2022 |
| 2005 | 1002 | 1505 | 07/05/2022 |
Write a PostgreSQL query that will generate a new table showing each customer's , , total of their purchases, and the count of their .
Answer:
A PostgreSQL solution is given below:
This query joins the , , and table on and . It groups by and to give a sum of the purchase and a count of the by each customer. The final results are ordered by .
Because join questions come up so often during SQL interviews, take a stab at this Snapchat Join SQL question:
SQL Question 7: How do the and window functions differ from each other?
As the name implies, the window function ranks each row within your window/partition. If two rows have the same rank, the next number in the ranking will be the previous rank plus the number of duplicates. For example, if you've got three records tied for 5th place, they'll get the values 5, 6, and 7, and the next row after this 3-way tie will have a rank of 8.
The function assigns a distinct rank to each row within a partition based on the provided column value with no gaps. This function will assign the same rank to two rows if they have the same rank, and give the next row the next rank number. To make this more concrete, imagine you had three records at rank 5 – then, the next rank would be 6.
SQL Question 8: Calculation of Statistics from Transaction Records
At AvidXchange, you have the following table of transaction records for each client in the table. The column represents the transaction amount, the represents the date of the transaction, and the represents the client making the transaction:
Example Input:
Write a SQL query to calculate and round to the nearest whole number the following information for each month and each client:
- The total transaction amount
- The average transaction amount
- The amount of the largest transaction
- The amount of the smallest transaction
The result should then order by client then month. Note: Use the function to truncate the date down to the month level.
Example Output:
Answer:
This query first groups by both the client and the month of the transaction date. It then rounds and calculates the total, average, max, and min amount for each of these categories using the respective aggregate functions (, , , ). The results are then ordered by client and the month of the transaction date.
To practice a very similar question try this interactive Stripe Repeated Payments Question which is similar for handling transaction data or this Uber User's Third Transaction Question which is similar for using transaction data with a window function.
AvidXchange SQL Interview Tips
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the AvidXchange SQL interview is to solve as many practice SQL interview questions as you can!
In addition to solving the above AvidXchange SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Netflix, Google, and Amazon.
Each SQL question has hints to guide you, detailed solutions and crucially, there's an interactive SQL code editor so you can right online code up your query and have it graded.
To prep for the AvidXchange SQL interview it is also a great idea to solve SQL questions from other tech companies like:
In case your SQL query skills are weak, forget about going right into solving questions – go learn SQL with this free SQL tutorial.
This tutorial covers things like working with string/text data and math functions like ROUND()/CEIL() – both of which show up frequently in AvidXchange SQL interviews.
AvidXchange Data Science Interview Tips
What Do AvidXchange Data Science Interviews Cover?
Besides SQL interview questions, the other question categories tested in the AvidXchange Data Science Interview are:
- Statistics Interview Questions
- Coding Questions in Python or R
- Product Data Science Interview Questions
- ML Interview Questions
- Behavioral & Resume-Based Questions
How To Prepare for AvidXchange Data Science Interviews?
To prepare for AvidXchange Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from tech companies like Google & Microsoft
- a refresher on SQL, Product-Sense & ML
- over 900+ 5-star reviews on Amazon