11 AvePoint SQL Interview Questions (Updated 2024)
Data Analysts and Data Engineers at AvePoint write ad-hoc SQL queries almost every single workday. They use SQL for analyzing customer data to optimize software solutions, and managing large datasets that come from managing multi-cloud solutions. That's why AvePoint LOVES to ask folks interviewing at the company SQL interview problems.
So, to help you prepare for the AvePoint SQL interview, we've curated 11 AvePoint SQL interview questions in this blog.
11 AvePoint SQL Interview Questions
SQL Question 1: Analyze Monthly Average Rating per Product
AvePoint is interested in understanding the average rating per product on a monthly basis. Write a SQL query that calculates the average rating (stars) per product for each calendar month.
Given the following table , analyze the reviews for each product on a monthly basis.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-06-08 | 50001 | 4 |
| 7802 | 265 | 2022-06-10 | 69852 | 4 |
| 5293 | 362 | 2022-06-18 | 50001 | 3 |
| 6352 | 192 | 2022-07-26 | 69852 | 3 |
| 4517 | 981 | 2022-07-05 | 69852 | 2 |
Answer:
The above query first identifies the month of each review using the function. It then groups by both month (mth) and product_id, and calculates the average (avg_stars) for each group. The final result is sorted by month and product_id.
In the output, a company can now view the average star rating each product received per month. This will help in understanding if certain products consistently receive higher (or lower) ratings, and if there were any particular months when the ratings were exceptionally high (or low).
To practice a related window function SQL problem on DataLemur's free online SQL code editor, solve this Google SQL Interview Question:
SQL Question 2: Highly-Paid Employees
Imagine you had a table of AvePoint employee salaries. Write a SQL query to find the employees who earn more than their own manager.
AvePoint 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, while her manager William Davis earns only 7,800.
Code your solution to this question and run your code right in DataLemur's online SQL environment:
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 hard to understand, you can find a detailed solution with hints here: Employees Earning More Than Managers.
SQL Question 3: Name the different types of joins in SQL. What does each one do?
A join in SQL allows you to retrieve data from multiple tables and combine it into a single set of results.
In SQL, there are four different types of JOINs. To demonstrate each kind, imagine you had two database tables, an advertising campaigns table which had information on Google Ads keywords and how much was bid for each keyword, and a sales table, which has data on how many products were sold and which Google Ads keyword drove that sale.
: An INNER JOIN retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.
: A LEFT JOIN retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.
: A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.
: A FULL OUTER JOIN retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.
SQL Question 4: Customer Subscription Analysis
AvePoint is a tech company that offers cloud solutions to manage and migrate data. Let's say AvePoint has a subscription-based product and we have access to the customer subscription data. The business would like a review of their customer status on this particular product over monthly intervals. They want to understand the number of new subscribers, the number of subscribers cancelled, and the total number of active subscribers each month.
The tables we have access to are and .
Example Input:
| customer_id | signup_date | first_name | last_name |
|---|---|---|---|
| 123 | 01/07/2021 | John | Doe |
| 265 | 08/10/2021 | Jane | Smith |
| 362 | 01/02/2022 | Steven | Brown |
Example Input:
| subscription_id | customer_id | start_date | end_date |
|---|---|---|---|
| 50001 | 123 | 01/07/2021 | 01/12/2021 |
| 69852 | 123 | 02/01/2022 | null |
| 50001 | 265 | 08/10/2021 | 12/25/2021 |
| 69852 | 265 | 01/15/2022 | null |
| 50001 | 362 | 01/02/2022 | 06/23/2022 |
Example Output:
| month_year | new_subscribers | cancellations | total_active_subscribers |
|---|---|---|---|
| 07/2021 | 2 | 0 | 2 |
| 08/2021 | 1 | 0 | 3 |
| 09/2021 | 0 | 0 | 3 |
| 10/2021 | 0 | 0 | 3 |
| 11/2021 | 0 | 0 | 3 |
| 12/2021 | 0 | 2 | 1 |
| 01/2022 | 0 | 0 | 1 |
| 02/2022 | 0 | 0 | 1 |
| 03/2022 | 0 | 0 | 1 |
| 04/2022 | 0 | 0 | 1 |
| 05/2022 | 0 | 0 | 1 |
| 06/2022 | 0 | 0 | 0 |
Answer:
This SQL query uses data from the table to track customer subscriptions over time. It uses the function to treat null values as the current date, which implies that these subscriptions are still active. The statement distinguishes between new, cancelled, and active subscriptions. The result is a monthly overview of AvePoint's customer subscription status.
SQL Question 5: What distinguishes an inner join from a full outer join?
A full outer join returns all rows from both tables, including any unmatched rows, whereas an inner join only returns rows that match the join condition between the two tables.
For a tangible example, suppose you had a table of AvePoint orders and AvePoint customers.
Here's a SQL inner join using the orders and customers tables:
This query will return rows from the orders and customers tables that have matching values. Only rows with matching values will be included in the results.
Here is an example of a using the orders and customers tables:
This query will return all rows from both the orders and customers tables, including any rows that do not have matching values. Any rows with null values for either table will be included in the results.
SQL Question 6: Filter Customers Based on Subscription Status and Location
AvePoint is interested in finding out more about their customers for better target marketing. They would like to filter their customer database based on the subscription status and location of the customers.
The subscription status can be 'Active', 'Inactive', or 'Cancelled'. The locations of interest are 'USA', 'Canada', and 'Mexico'. Write an SQL query that can filter out all the customers who are either 'Active' subscribers from 'USA' or 'Inactive' subscribers from 'Canada' and 'Mexico'. Exclude 'Cancelled' subscribers.
Example Input:
| customer_id | name | subscription_status | location |
|---|---|---|---|
| 101 | John | Active | USA |
| 102 | Emma | Inactive | USA |
| 103 | Robert | Cancelled | USA |
| 104 | Olivia | Active | Canada |
| 105 | Michael | Inactive | Mexico |
Example Output:
| customer_id | name | subscription_status | location |
|---|---|---|---|
| 101 | John | Active | USA |
| 105 | Michael | Inactive | Mexico |
Answer:
This will provide us with the list of customers who are either 'Active' subscribers in the 'USA', or 'Inactive' subscribers in 'Canada' or 'Mexico', excluding the ones who have 'Cancelled' their subscriptions. By filtering the customers this way, AvePoint can target their marketing strategies more effectively.
SQL Question 7: What's a database view, and what's it used for?
Database views are created to provide customized, read-only versions of your data that you can query just like a regular table. So why even use one if they're so similar to a regular table?
Views are advantageous for several reasons:
- views allow you to create a simpler versions of your data for specific users (such as hiding extraneous columns/rows from business analysts since they're relics of the Data Engineering pipelines setup)
- views help you comply with data security requirements by hiding sensitive data from certain users (important for regulated industries like govermnet and healthcare!)
- views can improve performance for complicated queries by pre-computing the results and caching them in a view (which is often faster than re-executing the original query)
SQL Question 8: Calculate the average usage per user on a monthly basis for AvePoint's cloud service
As a data analyst at AvePoint, you have been asked to investigate the usage patterns of the company's cloud service. Write a SQL query to calculate the average monthly usage per user (in GB) from January to December 2022.
Example Input:
| usage_id | user_id | usage_month | usage_year | usage_gb |
|---|---|---|---|---|
| 342 | 101 | 01/01/2022 | 2022 | 50 |
| 501 | 202 | 01/01/2022 | 2022 | 60 |
| 678 | 101 | 02/01/2022 | 2022 | 55 |
| 790 | 202 | 02/01/2022 | 2022 | 45 |
| 999 | 303 | 02/01/2022 | 2022 | 30 |
Example Output:
| month | year | avg_usage_gb |
|---|---|---|
| 1 | 2022 | 55 |
| 2 | 2022 | 43.33 |
Answer:
In this query, we use the function to get the month from the timestamp. The function is used to calculate the average usage in gigabytes (GB) per user for each month. The clause groups the data by month and year to provide monthly averages. The clause restricts the data to the year 2022.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating averages over a period or this Facebook Active User Retention Question which is similar for examining monthly usage activities.
SQL Question 9: Calculate Click-Through-Rate for AvePoint Website
AvePoint, a technology company, wants to analyze the effectiveness of their digital product display for online customers. They want to calculate the click-through-rate (CTR) - the percentage of customers who viewed a product and also added it to their cart. Assume there are two actions: 'product_view' and 'add_to_cart'. You have given two tables – 'actions' and 'users'. Please write a SQL query to calculate the CTR for the month of August 2022.
Example Input:
| action_id | user_id | action_type | action_time | product_id |
|---|---|---|---|---|
| 1627 | 111 | product_view | 2022-08-01 12:15:00 | 41226 |
| 3642 | 222 | product_view | 2022-08-05 14:25:00 | 73823 |
| 2241 | 333 | product_view | 2022-08-12 09:20:00 | 41226 |
| 8762 | 444 | product_view | 2022-08-20 17:10:00 | 49772 |
| 3941 | 111 | add_to_cart | 2022-08-01 13:00:00 | 41226 |
Example Input:
| user_id | join_date |
|---|---|
| 111 | 2020-07-12 |
| 222 | 2021-05-06 |
| 333 | 2021-08-05 |
| 444 | 2022-08-01 |
Answer:
Above query firstly filters out the 'product_view' and 'add_to_cart' actions in the month of August 2022. Then, it calculates the CTR by dividing the count of 'add_to_cart' actions by the count of 'product_view' actions, and then multiplying the result by 100 to get a percentage.
To practice a related SQL interview question on DataLemur's free interactive SQL code editor, try this SQL interview question asked by Facebook:
SQL Question 10: 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 a concrete example, suppose you were a Data Scientist on the Marketing Analytics team at AvePoint. A task you would encounter freqently would be to calculate the conversion rate for AvePoint's ads over a certain time period, for which you would write the following stored procedure:
To use this conversion rate stored procedure, you could call it like this:
SQL Question 11: Find Customers in US offices
AvePoint is a global technology company that provides software solutions for data migration, management, and protection in Microsoft 365. As a database specialist, we would like you to help in filtering their customer records.
AvePoint has offices worldwide, each office can have many customers, but each customer is only associated with one office. Your task is to write an SQL query that filters out all customers that belong to AvePoint offices located in the United States. Let's assume for simplicity that all US offices have an address that contain the string 'USA'.
Below are example input and output tables.
Example Input:
| office_id | office_address |
|---|---|
| 001 | 525 Washington Blvd, USA |
| 002 | 4 Yonge Street, Canada |
| 003 | 279 W 44th Street, USA |
| 004 | 7-22-34 Roppongi, Japan |
Example Input:
| customer_id | name | office_id |
|---|---|---|
| 8591 | John Doe | 001 |
| 7204 | Jane Doe | 002 |
| 5323 | Max Smith | 003 |
| 6023 | Sam Taylor | 004 |
Example Output:
| customer_id | name | office_id |
|---|---|---|
| 8591 | John Doe | 001 |
| 5323 | Max Smith | 003 |
Answer:
In this query, we are first joining the customers and offices table based on the office id, and then filtering out the customers where the address of the office contains 'USA'. The '%' on both sides of 'USA' is used as a wildcard to match any characters before or after 'USA'.
Preparing For The AvePoint SQL Interview
The best way to prepare for a AvePoint SQL interview is to practice, practice, practice.
In addition to solving the above AvePoint SQL interview questions, you should also solve the 200+ DataLemur interview questions which come from companies like Netflix, Google, and Amazon.
Each interview question has hints to guide you, full answers and most importantly, there is an interactive SQL code editor so you can right in the browser run your SQL query and have it executed.
To prep for the AvePoint SQL interview it is also wise to solve SQL problems from other tech companies like:
But if your SQL foundations are weak, don't worry about jumping right into solving questions – strengthen your SQL foundations with this free SQL for Data Analytics course.
This tutorial covers things like filtering with LIKE and filtering data with boolean operators – both of these come up frequently during AvePoint SQL interviews.
AvePoint Data Science Interview Tips
What Do AvePoint Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories covered in the AvePoint Data Science Interview are:
- Statistics and Probability Questions
- Coding Questions in Python or R
- Open-Ended Data Case Studies
- Machine Learning and Predictive Modeling Questions
- Resume-Based Behavioral Questions
How To Prepare for AvePoint Data Science Interviews?
I'm a tad biased, but I think the best way to prep for AvePoint Data Science interviews is to read the book Ace the Data Science Interview.
The book solves 201 interview questions sourced from Facebook, Google, & Amazon. It also has a refresher on Python, SQL & ML. And finally it's helped a TON of people, which is how it's gotten to be an Amazon best-seller with over 1000+ 5-star reviews.