11 Atoss SQL Interview Questions (Updated 2024)

Updated on

March 3, 2024

At Atoss, SQL is used frequently for extracting and analyzing workforce management datasets and reporting insights back to HR leaders. That's the reason behind why Atoss frequently asks SQL coding questions in interviews for Data Science, Data Engineering and Data Analytics jobs.

Thus, to help you practice for the Atoss SQL interview, we've collected 11 Atoss SQL interview questions – able to answer them all?

11 Atoss SQL Interview Questions

SQL Question 1: Identify VIP Customers for Atoss

Atoss is a company that provides workforce management solutions. A crucial activity for them is customers using their software on a daily basis. In the below exercise you have been given a sample of Atoss's User Activity table. The task is to identify the top 10 users (customer_id) that have logged in the most frequently in the past 30 days.

Example Input:

101A1001Login08/15/2022 00:00:00
102A1002Login08/18/2022 00:00:00
103A1001Login08/20/2022 00:00:00
104A1003Login08/22/2022 00:00:00
105A1001Login08/25/2022 00:00:00
106A1002Login08/28/2022 00:00:00
107A1001Login08/30/2022 00:00:00
108A1004Login08/31/2022 00:00:00

Example Output:



Here's a SQL query to solve this problem using PostgreSQL:

The query first filters the table's rows where the column is 'Login' and the is within the last 30 days. It then groups the result by and provides a count of the activity_id's for each , which is the number of logins. The result is then ordered by in descending order and limited to the 10 VIP customers who logged in the most.

To practice a related customer analytics question on DataLemur's free online SQL coding environment, try this Microsoft Azure Cloud SQL Interview Question: Microsoft SQL Interview Question: Super Cloud Customer

SQL Question 2: Employee Attendance Analysis

Assume that Atoss is a company where employees log in and out every day, and the HR department wants to analyze the attendance of employees to identify any issues. Specifically, they would like to know for each employee, their average working hours in the last 7 days.

Let's start by providing the example input for the table:

Example Input:
111008/01/2022 8:00:0008/01/2022 16:00:00
211008/02/2022 8:00:0008/02/2022 16:00:00
311008/03/2022 8:00:0008/03/2022 17:00:00
411108/01/2022 9:00:0008/01/2022 18:00:00
511108/02/2022 9:00:0008/02/2022 18:00:00
611108/03/2022 9:30:0008/03/2022 18:30:00

Here is an example of the output that we should get:

Example Output:

We want to calculate the average working hours for each employee in the last 7 days. Here is the PostgreSQL query that would give us the desired output:


This PostgreSQL command calculates the average working hours for each employee for the last 7 days. The function EXTRACT is used to get the difference of the logout_time and login_time in seconds which is then divided by 3600 to get the result in hours. The AVG function along with the OVER clause is used to create a moving average for each employee, using data from the current row and the previous six rows.

For more window function practice, solve this Uber SQL problem on DataLemur's online SQL code editor:

Uber Window Function SQL Interview Question

SQL Question 3: How does a left join differ from a right join?

Both types of joins in SQL help you retrieve data from multiple tables and merge the results into a single table.

To demonstrate the difference between a left join versus a right join, imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.

A 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.

Atoss SQL Interview Questions

SQL Question 4: Calculating Average Employee Salary in Atoss

As an analyst at Atoss, a company that deals with human resource details, you are asked to calculate the average salary of employees based on their departments to see the financial disparity among different departments.

Example Input:
Example Input:


Here, we are joining the employees and departments tables on the department_id, and grouping our results by the department name. The function is used to find the average salary of each department.

This output should give us a list of departments along with their average salaries. This information can be used by decision-makers in the company to revise salaries or to analyze the expenditure on each department.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating maximums within groups or this Amazon Average Review Ratings Question which is similar for calculating averages within groups.

SQL Question 5: What's the SQL command do, and can you give an example?

The SQL command merges the results of multiple statements and keeps only those rows that are present in all sets.

For example, say you were doing an HR Analytics project for Atoss, and had access to Atoss's employees and contractors data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables. You could use operator to find all contractors who also show up in the employees table:

SQL Question 6: Calculate Click-Through Conversion Rates

Atoss operates a digital marketplace that sells a wide range of software products. They use digital ads to attract users to their website, and they are interested in understanding their click-through conversion rates. The click-through conversion rate is calculated as the number of users who add a product to their cart after viewing it divided by the total number of views for each product.

Atoss has given you two data sets. The first data set, , captures each individual view of a product:

  • : A unique identifier for each view
  • : The id for the user making the view
  • : The id for the product
  • : The date and time when the view was made

The second data set, , captures each time a product is added to a user's cart:

  • : A unique identifier for each add to cart
  • : The id for the user
  • : The id for the product
  • : The date and time when the product was added to the cart

Given these two datasets, write a SQL query that calculates the click-through conversion rate for each product.

Example Input:
11235000106/08/2022 00:00:00
22655000106/10/2022 00:00:00
33626985206/18/2022 00:00:00
41926985207/26/2022 00:00:00
59816985207/05/2022 00:00:00
Example Input:
11235000106/10/2022 00:00:00
23626985207/10/2022 00:00:00
31926985207/28/2022 00:00:00


This query works by joining the and tables together on the user_id and product_id fields. This join allows us to count both the number of views and the number of cart adds for each product. By dividing the count of cart adds by the count of views, we can calculate the click-through conversion rate.

To solve a similar SQL problem on DataLemur's free interactive SQL code editor, solve this Facebook SQL Interview question: Facebook Click-through-rate SQL Question

SQL Question 7: Can you provide a comparison of cross join and natural join?

Cross joins and natural joins are two types of JOIN operations in SQL that are used to combine data from multiple tables. A cross join creates a new table by combining each row from the first table with every row from the second table, and is also known as a cartesian join. On the other hand, a natural join combines rows from two or more tables based on their common columns, forming a new table. One key difference between these types of JOINs is that cross joins do not require common columns between the tables being joined, while natural joins do.

Here's an example of a cross join:

If you have 20 products and 10 colors, that's 200 rows right there!

Here's a natural join example using two tables, Atoss employees and Atoss managers:

This natural join returns all rows from Atoss employees where there is no matching row in managers based on the column.

SQL Question 8: Calculate the Average Usage Duration of Software Products

Atoss, a software company, wants to understand the usage behavior of its clients. Each time a client uses a software product, the usage duration is logged in the table. You are asked to write a SQL query to find the average usage duration of each software product.

Example Input:
1001A23SW111/02/2022 09:00:0011/02/2022 11:00:00
1002B45SW211/02/2022 10:30:0011/02/2022 11:30:00
1003A23SW111/02/2022 13:00:0011/02/2022 15:30:00
1004B45SW211/02/2022 14:30:0011/02/2022 16:00:00
1005C67SW111/02/2022 16:00:0011/02/2022 18:30:00
Example Output:


In the provided query, is used to group the input by . The aggregate function is used to calculate the average difference between and which gives us the average usage duration in hours for each software product.

SQL Question 9: Analyzing Customer Purchases and Corresponding Payments

Given two tables 'CustomerData' and 'PaymentData', write a SQL query to join these tables and display the total amount spent by each customer. Assume that the 'CustomerData' table includes information about customer's ID and name, and the 'PaymentData' table contains information about the customer's ID, purchase ID and the amount spent.

Below are the sample data tables:

Example Input:
1001John Doe
1002Jane Smith
1003Alice Johnson
1004Bob Jackson
Example Input:


The following PostgreSQL command accomplishes this:

This command joins the 'CustomerData' and 'PaymentData' tables on the 'CustomerID' field (which is common to both tables), and groups the result by 'CustomerID' and 'CustomerName'. The SUM function is then used to calculate the total amount spent by each customer. The final result is sorted in descending order of the total spent.

Because join questions come up frequently during SQL interviews, take a stab at this Snapchat SQL Interview question using JOINS: Snapchat JOIN SQL interview question

SQL Question 10: What does the constraint do, and when might you use it?

The CHECK constraint is used to enforce rules on the data in a specific column. If a row is inserted or updated with data that does not follow the CHECK constraint's rule, the operation will fail.

For example, say you had a database that stores ad campaign data from Atoss's Google Analytics account.

Here's what some constraints could look like:

In this example, the constraint is used to ensure that the "budget" and "cost_per_click" fields have positive values. This helps to ensure that the data in the database is valid and makes sense in the context of ad campaigns.

You can also use the constraint to ensure that data meets other specific conditions. For example, you could use a constraint to ensure that the "start_date" is before the "end_date" for each ad campaign.

SQL Question 11: Calculate Power Consumption

Atoss is a company that operates several factories with different numbers of machines. Each machine has a wattage rating which represents the amount of watts it uses every hour. These machines run continuously throughout the day and their total power consumption is of interest to the company.

Atoss has asked you to write a query that can calculate the total power consumed by their machines in a given year (taking into account leap years) for each factory. Also, compute the average power consumption per machine in each factory, and round it to the nearest integer.

Assume that we have a table named that keeps track of the machines in each factory, formatted as follows:

Example Input:


The following SQL query can be used to solve this problem:

Example Output:


In this query, we calculate the total power consumed by each factory's machines in a year by multiplying the wattage per hour with the number of hours in a year. We then compute the average power consumption per machine using the AVG function and round it to the nearest integer. The result is grouped by the factory_id using the GROUP BY clause.

To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating total hourly usage or this Tesla Unfinished Parts Question which is similar for working with factory operations.

Atoss SQL Interview Tips

The best way to prepare for a Atoss SQL interview is to practice, practice, practice. Besides solving the earlier Atoss SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Microsoft, Google, and Facebook. DataLemur Question Bank

Each interview question has multiple hints, detailed solutions and crucially, there's an online SQL coding environment so you can easily right in the browser your query and have it checked.

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

But if your SQL skills are weak, don't worry about jumping right into solving questions – strengthen your SQL foundations with this SQL interview tutorial.

SQL interview tutorial

This tutorial covers SQL concepts such as filtering data with WHERE and CASE/WHEN/ELSE statements – both of which come up routinely in SQL job interviews at Atoss.

Atoss Data Science Interview Tips

What Do Atoss Data Science Interviews Cover?

Beyond writing SQL queries, the other types of problems to practice for the Atoss Data Science Interview are:

  • Statistics and Probability Questions
  • Python Pandas or R Coding Questions
  • Business Sense and Product-Sense Questions
  • ML Modelling Questions
  • Resume-Based Behavioral Questions

Atoss Data Scientist

How To Prepare for Atoss Data Science Interviews?

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