11 Tenable SQL Interview Questions (Updated 2024)
At Tenable, SQL is typically used for extracting and analyzing vulnerability data from cybersecurity threat databases. Because of this, Tenable LOVES to ask SQL problems during interviews for Data Science, Data Engineering and Data Analytics jobs.
So, to help you practice for the Tenable SQL interview, we'll cover 11 Tenable SQL interview questions – able to answer them all?
11 Tenable SQL Interview Questions
SQL Question 1: Identify VIP Users For Tenable
Tenable is a cybersecurity company that provides vulnerability management services. They rely on users continually testing their networks for vulnerabilities. Therefore, for Tenable, VIP users can be defined as those users who run the most vulnerability scans on their networks within a given month.
Given a database that logs all vulnerability scans, please write a SQL query to identify top 5 users who have run the most vulnerability scans within the last month.
Example Input:
| scan_id | user_id | scan_date | scan_result |
|---|---|---|---|
| 134391 | 989 | 09/05/2022 00:00:00 | Successful |
| 167892 | 675 | 09/10/2022 00:00:00 | Successful |
| 142903 | 909 | 09/18/2022 00:00:00 | Failed |
| 163502 | 989 | 09/26/2022 00:00:00 | Successful |
| 145117 | 675 | 09/05/2022 00:00:00 | Failed |
Example Output:
| user_id | count_scans |
|---|---|
| 989 | 2 |
| 675 | 2 |
| 909 | 1 |
Answer:
The SQL query should be something like this:
This query is first restricting the data to only the last month with the WHERE clause. It then groups by user_id and counts the number of scans each user has run. The result is then ordered in descending order to get the users with the most scans at the top, and finally the LIMIT clause restricts the result to the top 5 scanning users.
To practice a super-customer analysis question on DataLemur's free interactive coding environment, try this Microsoft Azure Cloud SQL Interview Question:
SQL Question 2: Calculate the Monthly Average Vulnerabilities per Asset.
Tenable, Inc. is a cybersecurity company that provides vulnerability management products. One of their products is used by businesses to identify and fix vulnerabilities in assets such as servers, laptops, mobile devices, etc. Each asset can have multiple vulnerabilities, and each vulnerability is assigned a severity level.
As a Data Analyst at Tenable, you are asked to generate a report that shows the average number of vulnerabilities per asset per month, including both resolved and not resolved vulnerabilities. To calculate this average, you should use the total number of vulnerabilities divided by the unique count of assets in each month.
Here are the two relevant tables:
Table:
| asset_id | asset_name | asset_type |
|---|---|---|
| 1001 | Server 1 | Server |
| 1002 | Laptop 1 | Laptop |
| 1003 | Mobile Device 1 | Mobile Device |
| 1004 | Server 2 | Server |
| 1005 | Laptop 2 | Laptop |
Table (Example Input):
| vulnerability_id | asset_id | found_date | severity_level | status |
|---|---|---|---|---|
| 7001 | 1001 | 06/10/2022 | High | Not Resolved |
| 8002 | 1002 | 06/15/2022 | Low | Resolved |
| 7003 | 1003 | 07/18/2022 | Medium | Not Resolved |
| 7004 | 1001 | 07/22/2022 | High | Resolved |
| 7005 | 1005 | 07/28/2022 | Low | Not Resolved |
The Expected Output:
| month | average_vulnerabilities_per_asset |
|---|---|
| 06 | 2.00 |
| 07 | 1.50 |
Answer:
This will require a PostgreSQL query that incorporates a window function (the function applied over a defined window). Here is a sample query to calculate the average vulnerabilities per asset per month:
In this SQL query, the window function is used twice. The first usage counts the total number of vulnerabilities for each month, and the second counts the different assets for each month. Dividing the two counts gives the average number of vulnerabilities per asset for each month. The result is ordered by month.
For more window function practice, try this Uber SQL Interview Question on DataLemur's online SQL coding environment:
SQL Question 3: What's the purpose of the the command?
combines the results from two or more SELECT statements, but only returns the rows that are exactly the same between the two sets.
For example, let's use to find all of Tenable's Facebook video ads with more than 10k views that are also being run on YouTube:
SQL Question 4: Customer Vulnerability Report Generation in Tenable
Tenable, Inc. is a cybersecurity company that provides vulnerability management solutions. As a database designer, consider that Tenable maintains a database in which it stores information about its various customers, the different software applications they use (referred to as the 'assets') and any identified vulnerabilities associated with each asset.
Your task is to design this database and subsequently, write a query that can generate a report showcasing the identified vulnerabilities for each customer.
Sample Input:
| customer_id | customer_name |
|---|---|
| 1 | Intel Corp |
| 2 | Adobe Inc |
| 3 | Microsoft Corp |
Sample Input:
| asset_id | asset_name | customer_id |
|---|---|---|
| 101 | Photoshop | 2 |
| 102 | Windows | 3 |
| 103 | Surface Pro | 3 |
| 104 | McAfee | 1 |
Sample Input:
| vulnerability_id | asset_id | vulnerability_title | severity |
|---|---|---|---|
| 1001 | 101 | XSS Vulnerability | High |
| 1002 | 101 | Arbitrary Code Execution | Medium |
| 1003 | 103 | Privilege Escalation | Low |
| 1004 | 102 | Torjan Virus Vulnerability | Medium |
Answer:
This query should return a table where each row represents a vulnerability associated with a given customer's asset. The table will have four columns: , , , and . This information typically enables a cybersecurity company like Tenable to track the vulnerabilities affecting its client's software assets and prioritize their resolution based on their severity.
SQL Question 5: In the context of database schema design, can you give an example of a one-to-one relationship vs. a one-to-many relationship?
In database schema design, a one-to-one relationship between two entities is characterized by each entity being related to a single instance of the other. An example of this is the relationship between a US citizen and their social-security number (SSN) - each citizen has one SSN, and each SSN belongs to one person.
On the other hand, a one-to-many relationship is when one entity can be associated with multiple instances of the other entity. A teacher's relationship with their classes is an example of this - a teacher can teach many classes, but each class is only associated with one teacher.
SQL Question 6: Average Severity Score of Vulnerabilities per Asset
As a security-focused company, Tenable aims to manage, measure and reduce cybersecurity risk. In this context, they track various vulnerabilities found in different assets and their severity. Assuming we have a database that tracks every vulnerability for each asset in the system, write a SQL query to find the average severity of vulnerabilities for each asset.
Example Input:
| vulnerability_id | asset_id | found_date | severity_score |
|---|---|---|---|
| 1001 | 10 | 2022-06-08 | 7 |
| 1002 | 15 | 2022-06-10 | 5 |
| 1003 | 10 | 2022-06-18 | 6 |
| 1004 | 20 | 2022-07-26 | 8 |
| 1005 | 15 | 2022-07-05 | 5 |
Answer:
The following PostgreSQL query will solve the problem:
This query uses the AVG() function to calculate the average severity score of vulnerabilities for each asset. It first groups the rows in the table by the asset_id using GROUP BY clause, and then for each group, it calculates the average value of the severity_score using AVG() function.
For example, for asset_id 10, it'll calculate the average of severity scores 7 and 6, which is 6.5. For asset_id 15, it'll calculate the average of 5 and 5, which is 5. And for asset_id 20, as there is only one record, the average score would be the same as the score of that vulnerability, which is 8.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for computing averages or this Alibaba Compressed Mean Question which is similar for dealing with data analysis.
SQL Question 7: What's the difference and a ?
For all practical purposes, and do NOT produce the same results.
While both are similar in that they combine two tables, you can think of joins as increasing the width of the resulting table (you'll have more columns in the result set for a left/inner/right join), whereas a union is used to combine rows which increases the height of the result set but keeps the column count the same.
If your familiar with set operations, you can think of a as set addition, whereas a is set multiplication.
SQL Question 8: Calculate Click-through-to-Conversion Rates
Tenable has been running digital marketing campaigns to boost the sales of its new security software. Each ad leads the viewer to a product page. If interested, the viewer can add the product to their cart. Tenable is curious about the conversion rates of these ad campaigns, i.e., the click-through-to-add-to-cart rates.
Using the provided sample tables, write a PostgreSQL query to calculate the click-through-to-conversion rate for each campaign. Define the click-through-to-conversion rate as the ratio of the number of viewers who added the product to their cart after viewing the product page divided by the total number of viewers who clicked to view the product page.
Example Input:
| ad_id | user_id | click_date | product_id |
|---|---|---|---|
| 301 | 123 | 2022-06-08 | 50001 |
| 204 | 123 | 2022-06-10 | 69852 |
| 207 | 362 | 2022-06-19 | 50001 |
| 101 | 981 | 2022-07-05 | 69852 |
Example Input:
| cart_id | user_id | add_date | product_id |
|---|---|---|---|
| 501 | 123 | 2022-06-09 | 50001 |
| 304 | 362 | 2022-06-20 | 50001 |
| 107 | 981 | 2022-07-06 | 69852 |
Answer:
In this query, we start by creating 2 Common Table Expressions (CTEs), , where we count the number of ad clicks for each product, and , where we count the number of adds to cart for each product. Then we join the and based on the , and then calculate the conversion rate. The result is the click-through-to-conversion rate for each product_id.
To practice a similar problem on DataLemur's free online SQL code editor, solve this Meta SQL interview question:
SQL Question 9: Find the Average Severity Level of Vulnerabilities By Product
Tenable is a cybersecurity company that provides vulnerability management services. One key aspect of Tenable's work is identifying vulnerabilities in products and giving them a severity level.
Given a table, please identify the average severity of vulnerabilities identified over a given period per software product.
Example Input:
| report_id | report_date | product_name | vulnerability_severity |
|---|---|---|---|
| 1 | 01/01/2022 | Product_A | 5 |
| 2 | 01/15/2022 | Product_B | 3 |
| 3 | 02/01/2022 | Product_A | 4 |
| 4 | 02/15/2022 | Product_B | 2 |
| 5 | 03/01/2022 | Product_A | 1 |
Example Output:
| month | product_name | avg_severity |
|---|---|---|
| 1 | Product_A | 5.00 |
| 1 | Product_B | 3.00 |
| 2 | Product_A | 4.00 |
| 2 | Product_B | 2.00 |
| 3 | Product_A | 1.00 |
Answer:
In this query, the function is used to get the month from the field. The aggregate function finds the average for each product () on each month. The clause groups by both and . The clause sorts the output first by and then by in descending order, showing the product with the highest average severity first for each month.
SQL Question 10: Can you explain the purpose of UNION?
The UNION operator combines the results from multiple SELECT statements into a single result set.
Here's an example of using the UNION operator to combine the results of two SELECT statements that retrieve data from tables of Tenable's Facebook ads and their Google ads:
This statement would return a combined result set of both Facebook and Google ads that have a spend greater than $200. The result set would include the following columns: ad_id, ad_name, ad_type, impressions, clicks, and spend.
Note that the two SELECT statements within the UNION must have the same number of columns and the columns must have similar data types. In this example, both SELECT statements have the same number of columns and the data types of the columns are all compatible.
SQL Question 11: Analyze Customer Records and Subscriptions
As a data analyst at Tenable, you are tasked to analyze the customer records. You must determine how many unique products each customer has bought, and the total amount spent per customer. These records are stored in two tables - and .
Table:
| customer_id | first_name | last_name |
|---|---|---|
| 5001 | John | Doe |
| 5002 | Alice | Smith |
| 5003 | Bob | Jane |
| 5004 | Jane | Roe |
| 5005 | Mary | Brown |
Table:
| purchase_id | customer_id | product_id | amount |
|---|---|---|---|
| 1001 | 5001 | 2001 | 150.50 |
| 1002 | 5001 | 2002 | 99.99 |
| 1003 | 5002 | 2003 | 120.00 |
| 1004 | 5003 | 2001 | 150.50 |
| 1005 | 5004 | 2002 | 99.99 |
| 1006 | 5004 | 2002 | 99.99 |
| 1007 | 5005 | 2003 | 120.00 |
| 1008 | 5001 | 2003 | 120.00 |
Now, using the data from these two tables, write a SQL query to determine the per customer expenditure and how many unique products each customer has purchased.
Answer:
Here is the PostgreSQL query:
In this query, we are joining table with table on the common column . With the use of we calculate the number of unique products each customer has bought. calculates the total amount spent by each customer. We are grouping the results by so that we can get the results per customer.
Since join questions come up routinely during SQL interviews, take a stab at this Spotify JOIN SQL question:
Tenable SQL Interview Tips
The key to acing a Tenable SQL interview is to practice, practice, and then practice some more!
Beyond just solving the earlier Tenable SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Facebook, Google, and VC-backed startups.
Each SQL question has hints to guide you, step-by-step solutions and most importantly, there is an interactive coding environment so you can right in the browser run your query and have it executed.
To prep for the Tenable SQL interview it is also useful to solve SQL problems from other tech companies like:
But if your SQL query skills are weak, don't worry about jumping right into solving questions – go learn SQL with this free SQL tutorial.
This tutorial covers SQL concepts such as aggregate window functions and rank window functions – both of which show up routinely in Tenable interviews.
Tenable Data Science Interview Tips
What Do Tenable Data Science Interviews Cover?
Beyond writing SQL queries, the other types of questions to prepare for the Tenable Data Science Interview are:
- Probability & Statistics Questions
- Python Pandas or R Coding Questions
- Product-Sense and Business Case Questions
- ML Modelling Questions
- Resume-Based Behavioral Questions
How To Prepare for Tenable Data Science Interviews?
The best way to prepare for Tenable Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG (FB, Apple, Amazon, Netflix, Google)
- A Refresher on SQL, AB Testing & ML
- Great Reviews (900+ 5-star reviews on Amazon)