8 SUSE SQL Interview Questions (Updated 2024)
At SUSE S.A., SQL is used all the damn time for analyzing data generated from Suse's large fleet of servers and containers . For this reason SUSE typically asks SQL questions during interviews for Data Science, Data Engineering and Data Analytics jobs.
As such, to help you study for the SUSE SQL interview, this blog covers 8 SUSE S.A. SQL interview questions – can you solve them?
8 SUSE S.A. SQL Interview Questions
SQL Question 1: Identify Power Users based on Product Licenses Activation
SUSE is an open-source software company that delivers reliable, software-defined infrastructure and application delivery solutions for Cloud, Hybrid Cloud, and Enterprise applications. They have a diverse user base, with individuals at different usage levels.
Management at SUSE desires to understand which of their customers could be considered "power users" - individuals or businesses that frequently activate one or multiple software licenses indicating a high level of engagement and potentially higher value to the business.
Using the following sample data of software license activation records, can you write an SQL query to identify users who have activated more than 5 unique product licenses over the last 30 days? The IDs of these customers will be compared to other business metrics for further analysis.
Example Input:
| activation_id | user_id | activation_date | product_id |
|---|---|---|---|
| 101 | 123 | 2022-11-01 | 50001 |
| 102 | 265 | 2022-11-02 | 50001 |
| 103 | 123 | 2022-11-03 | 50002 |
| 104 | 192 | 2022-11-04 | 50003 |
| 105 | 981 | 2022-11-05 | 50004 |
| 106 | 123 | 2022-11-06 | 50005 |
| 107 | 123 | 2022-11-07 | 50006 |
| 108 | 123 | 2022-11-08 | 50007 |
| 109 | 123 | 2022-11-09 | 50008 |
Answer:
This SQL query initially groups the license activation records in the last 30 days by user_id and counts the distinct product_ids per user. Then, from these results, it filters to only return user_ids who have activated more than 5 unique products in the last 30 days. This list of user_ids represents the 'power users'.
To solve a related super-user data analysis question on DataLemur's free interactive coding environment, try this Microsoft Teams Power User SQL Interview Question:
SQL Question 2: Analyzing software purchase trends with Window Functions
SUSE, a software company, is interested in determining the most popular software among its customers over the last month. Specifically, they would like to know the number of clients that acquired each software in every week. To make this analysis, they maintain a 'purchases' table with the following format:
Example Input:
| purchase_id | client_id | purchase_date | software_id |
|---|---|---|---|
| 6121 | 124 | 2022-01-01 | 5010 |
| 7110 | 264 | 2022-01-02 | 6990 |
| 6593 | 302 | 2022-01-05 | 5010 |
| 7812 | 182 | 2022-01-09 | 6990 |
| 9197 | 967 | 2022-01-09 | 6995 |
Assuming each row to represent a single purchase where a client_id has bought a software_id on a specific purchase_date, please write an SQL query that returns the week of the year (as an integer from 1 - 53), the software_id and the number of clients that bought that software, for each week.
Answer:
Here is the SQL query to solve this problem:
This query extracts the week of the year from the purchase_date using the EXTRACT function of PostgreSQL. It then takes the software_id and counts the distinct client_id's corresponding to each software_id for that week, thus giving the number of clients buying each software in every week of the year. The result is then grouped by week_of_year and the software_id, finally it is sorted by the week of the year.
To practice a related window function SQL problem on DataLemur's free online SQL coding environment, solve this Google SQL Interview Question:
SQL Question 3: Why are stored procedures useful for analysts?
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 SUSE 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:
SQL Question 4: Calculate Average Product Usage Time
As a database administrator at SUSE, you have been tasked with analyzing the utilization of their Linux operating system by different clients. Each client is assigned an ID, and the system tracks each login session with a start time and end time. Your job is to write a SQL query that finds the average usage time per client in hours. Assume that the usage_time table logs data daily.
Consider the following example input and output:
Example Input:
| usertime_id | client_id | start_time | end_time |
|---|---|---|---|
| 1001 | 200 | 01/01/2022 08:00:00 | 01/01/2022 10:30:00 |
| 1002 | 200 | 02/01/2022 09:00:00 | 02/01/2022 11:00:00 |
| 1003 | 300 | 01/01/2022 07:00:00 | 01/01/2022 09:30:00 |
| 1004 | 300 | 02/01/2022 07:30:00 | 02/01/2022 10:00:00 |
Example Output:
| client_id | avg_usage_in_hours |
|---|---|
| 200 | 2.25 |
| 300 | 2.75 |
Answer:
This PostgreSQL query uses the function to get the difference between the end_time and start_time in seconds. This value is divided by 3600 to convert it into hours. The function is used to get the average usage time for each client. Grouping by client_id ensures that the average is calculated separately for each client. It is important to note that calculating time differences can vary between different SQL flavors. In this example, PostgreSQL is considered.
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for "calculating total utilization time" or this Microsoft Teams Power Users Question which is similar for "identifying users with highest activity".
SQL Question 5: Can you explain what / SQL commands do?
The / operator is used to remove to return all rows from the first SELECT statement that are not returned by the second SELECT statement.
Note that is available in PostgreSQL and SQL Server, while MINUS is available in MySQL and Oracle (but don't stress about knowing which DBMS supports what exact commands since the interviewers at SUSE should be lenient!).
For a tangible example in PostgreSQL, suppose you were doing an HR Analytics project for SUSE, and had access to SUSE's contractors and employees 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 never were a employee using this query:
Sure, here's a question for joining customer and product details table.
SQL Question 6: Retrieve Customer and their Product Details
As a data analyst for SUSE, you have been tasked with creating a report which shows each customer and their purchased product details. You have following tables:
- table which includes customer details.
- table which includes product details.
- table which includes purchase records linking customer and product.
Write a SQL query to retrieve Customer Name, Customer Email, Product Name, and Product Price for each purchase.
Example Input:
| customer_id | name | |
|---|---|---|
| 1 | John Doe | john.doe@example.com |
| 2 | Jane Smith | jane.smith@example.com |
| 3 | Michael White | michael.white@example.com |
Example Input:
| product_id | product_name | price |
|---|---|---|
| 100 | SUSE Linux Enterprise Server | 500 |
| 200 | SUSE Manager | 700 |
| 300 | SUSE Linux Enterprise Desktop | 300 |
Example Input:
| order_id | customer_id | product_id |
|---|---|---|
| 1001 | 1 | 100 |
| 1002 | 2 | 200 |
| 1003 | 3 | 300 |
Example Output should like this:
| customer_name | customer_email | product_name | product_price |
|---|---|---|---|
| John Doe | john.doe@example.com | SUSE Linux Enterprise Server | 500 |
| Jane Smith | jane.smith@example.com | SUSE Manager | 700 |
| Michael White | michael.white@example.com | SUSE Linux Enterprise Desktop | 300 |
Answer:
You can use the clause twice in the SQL query to join , and tables.
This query first joins and tables on and then joins the result with table on . This results in a new table that includes customer name, customer email, product name, and product price for each purchase.
Because joins come up so often during SQL interviews, try this interactive Snapchat Join SQL question:
SQL Question 7: How do the 'BETWEEN' and 'IN' commands differ?
The and operators are both used to filter data based on certain criteria, but they work in different ways. is used to select values within a range, while is used to select values that match a list.
For instance, if you have a table called that contains the salary of each employee, along with which country they reside in, you could use the operator to find all employees who make between 160k:
To find all employees that reside in France and Germany, you could use the operator:
SQL Question 8: Product Pricing Analysis
SUSE has a range of software products, and each product is sold at a different price point. They keep a record in a table named that contains the , , , and of each sale. They want to find the average, minimum, maximum, and total revenue of each product's sale, and also want to round the average price to 2 decimal places. They also want to find the square root of the average price and the modulus of the total revenue when divided by 1000 for each product.
Please write a SQL query that returns an output table with the , , , , , , and for each product.
Example Input:
| sale_id | product_id | sale_date | price |
|---|---|---|---|
| 1 | 101 | 12/01/2021 | $2500 |
| 2 | 102 | 12/02/2021 | $3500 |
| 3 | 101 | 12/03/2021 | $3000 |
| 4 | 103 | 12/04/2021 | $4000 |
| 5 | 102 | 12/05/2021 | $3200 |
Answer:
This query gets the average, minimum, maximum, and sum of the for each in the table. It also rounds the average price to two decimal places, calculates the square root of the average price, and determines the modulus of the total revenue when divided by 1000. These results are then grouped by . The ROUND() function is used to round numbers to a specified number of decimal places, the SQRT() function to calculate the square root, and the MOD() function to find the modulus after division by 1000.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for analyzing product sales and revenue or this Alibaba Compressed Mean Question which is similar for calculating average and rounding them to certain decimal places.
SUSE SQL Interview Tips
The key to acing a SUSE SQL interview is to practice, practice, and then practice some more!
In addition to solving the above SUSE SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Google, Uber, and Microsoft.
Each SQL question has hints to guide you, full answers and best of all, there's an interactive coding environment so you can instantly run your SQL query and have it graded.
To prep for the SUSE SQL interview you can also be wise to solve SQL problems from other tech companies like:
However, if your SQL skills are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this DataLemur SQL Tutorial.
This tutorial covers SQL topics like math functions and INTERCEPT/EXCEPT – both of these come up routinely in SUSE SQL assessments.
SUSE S.A. Data Science Interview Tips
What Do SUSE Data Science Interviews Cover?
In addition to SQL interview questions, the other topics to prepare for the SUSE Data Science Interview are:
- Probability & Stats Questions
- Python or R Coding Questions
- Product-Sense and Business Case Questions
- Machine Learning and Predictive Modeling Questions
- Behavioral & Resume-Based Questions
How To Prepare for SUSE Data Science Interviews?
To prepare for SUSE Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from FAANG (FB, Apple, Amazon, Netflix, Google)
- a refresher covering Python, SQL & ML
- over 900+ reviews on Amazon & 4.5-star rating