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11 Qualys SQL Interview Questions (Updated 2024)

Updated on

March 2, 2024

At Qualys, SQL is used frequently for analyzing vulnerability data across different networks to help their customers reduce their cybersecurity risk. It shouldn't surprise you that Qualys typically asks SQL problems during interviews for Data Analyst, Data Science, and BI jobs.

So, to help you study for the Qualys SQL interview, we'll cover 11 Qualys SQL interview questions – able to answer them all?

11 Qualys SQL Interview Questions

SQL Question 1: Identify the Top Performing Customers for Qualys

Qualys is a provider of cloud security, compliance, and related services, and hence it's likely that its most important users are those who frequently run security scans. You have been given the task to identify such power users.

Let's say all the scans users are running are stored in a table. This table contains information about the user who ran the scan (), when it was run (), the scan type () and the number of vulnerabilities found (). "Power users" can be defined as those users who run scans more than average and find more vulnerabilities than average.

Now, create a SQL query that returns a list of such power users along with the number of scans they have run and vulnerabilities they have found.

Example Input:
scan_iduser_idscan_datescan_typevulnerabilities
439721002/01/2021'Web App'16
847565302/02/2021'Network'20
374221002/03/2021'Web App'12
579393202/03/2021'Network'19
896421002/04/2021'Web App'18
Example Output:
user_idscan_counttotal_vulnerabilities
210346

Answer:


This query first groups the table by and then counts number of scans and sums up vulnerabilities for each user. It only selects those users, who run scans more than the average scan count and find more vulnerabilities than the average found by all users.

To solve a similar VIP customer analysis question on DataLemur's free interactive SQL code editor, try this Microsoft Azure Cloud SQL Interview Question: Microsoft SQL Interview Question: Super Cloud Customer

SQL Question 2: Calculate the Average Vulnerability Score by Month

Suppose Qualys, a provider of cloud security, compliance and related services, stores vulnerability scan data and you are asked to write a SQL query to calculate the average vulnerability score for each month for each detected threat.

The table in their database has the following columns: (unique identifier for each scan), (unique identifier for each detected threat), (date the scan was run), and (severity score of the detected threat, with 10 being very severe and 0 being not severe).

Example Input
scan_idthreat_idscan_datescore
001ABC1232022-01-028
002DEF4562022-01-035
003DEF4562022-01-157
004ABC1232022-02-109
005GHI7892022-02-206

Calculate the average score for each threat on a monthly basis.

Example Output:
monththreatavg_score
1ABC1238.00
1DEF4566.00
2ABC1239.00
2GHI7896.00

Answer:


This SQL query uses a window function to partition the data by and the month of (extracted using the function). It then computes the average score within each partition (). The clause is used to sort the results by month and threat.

Pro Tip: Window functions are a popular SQL interview topic, so practice every window function problem on DataLemur

SQL Interview Questions on DataLemur

SQL Question 3: What is a primary key?

The primary key of a table is a column or set of columns that serves as a unique identifier for each row. It ensures that all rows are distinct and does not allow null values.

For example, say you had stored some Facebook ad campaign data that Qualys ran:


The CampaignID column is used to uniquely identify each row in the table, and the constraint ensures that there are no duplicate CampaignID values. This helps to maintain the accuracy of the data by preventing duplicate rows. The primary key is also an important part of the table because it enables you to easily identify and reference specific campaigns in your Facebook Ad data. You can use it to join to other tables in the database, such as a table with data on the results of the campaigns.

Qualys SQL Interview Questions

SQL Question 4: Analyzing Vulnerabilities in Qualys' Systems

As a cybersecurity firm, Qualys regularly scans all its systems to detect any new vulnerabilities. For each identified vulnerability, the company generates a unique vulnerability ID, logs the system ID where the vulnerability was found, the severity of the vulnerability, and the detected date.

Design a database table capturing this information. Then, write a SQL query in PostgreSQL that returns a count of all 'Severe' vulnerabilities detected in the last 30 days, grouped by the affected system.

Here are some sample data:

Table:

vulnerability_idsystem_iddetection_dateseverity
871106/08/2022 00:00:00Moderate
2512206/10/2022 00:00:00Severe
993307/18/2022 00:00:00Moderate
3221107/28/2022 00:00:00Severe
4227207/30/2022 00:00:00Severe

Your task is to return a table in this format:

Expected Output:

system_idsevere_vulnerabilities
11
22

Answer:


This query filters the "vulnerabilities" table to only include rows where the vulnerability was marked 'Severe' and was detected within the last month. The clause groups these vulnerabilities by system, and the in the clause counts the total number of severe vulnerabilities for each one, exactly fulfilling the question requirement.

SQL Question 5: What does the SQL command do?

is used to combine the output of multiple statements into one big result!

For a concrete example, say you were doing an HR Analytics project for Qualys and needed to analyze both Qualys's employees and contractors who were hired after 2022 started. You could use in the following way:


SQL Question 6: Filter Customers for Cybersecurity Checks

As a Cybersecurity company, Qualys needs to frequently check their customer's security status. Assume Qualys has a customer records database and wants to filter customers that have not updated their security patches for two months or more, and customers who are using any of their five main products.

Given the and tables, provide a query that will return the list of customers who fit this criteria.

Example Input
customer_idlast_patch_dateproduct_id
12022-06-08101
22022-08-10102
32022-04-18103
42022-05-26104
52022-07-05105
Example Input
product_idproduct_name
101"Qualys Cloud Platform"
102"Qualys AssetInventory"
103"Qualys VMDR"
104"Qualys Policy Compliance"
105"Qualys Patch Management"

Answer


This will return a list of customer IDs, the name of the product they're using, and their last patch date, only if their last patch date is more than two months ago and they're using one of the main five Qualys products. The connects the and tables on the field. The clause checks both conditions.

SQL Question 7: Have you ever had to optimize a slow SQL query? How did you do it?

Here's some strategies that can generally speed up a slow SQL query:

  • Only query the columns you actually need
  • Index the columns used in the query
  • Use the right kind of JOIN (be explicit about inner vs. outer joins)
  • Use the right data types (for example INT vs BIGINT can save you disk space and memory)

While there's an entire industry dedicated to database performance tuning , for Data Analyst and Data Science interviews at Qualys, knowing the above basics should be more than enough to ace the SQL interview! Data Engineers on the other hand should know more about the command and understand a bit more about a query-execution plan.

SQL Question 8: Calculate the Click-Through-Rate for Qualys Ads

Given a table tracking clicks on ads, a table tracking occurrences of ads served, and a table tracking occasions where a clicked-on ad led to viewing a product detail page, write a SQL query to calculate the overall Click-Through-Rate (CTR) and the Product View-Through-Rate (PVTR) - the ratio of ads clicked to ads served, and the ratio of ads leading to product views to ads clicked respectively. CTR and PVTR need to be calculated for each ad campaign for the month of July.

Example Input:
click_iduser_idclick_datetimecampaign_id
10145107/04/2022 14:12:031001
10296807/09/2022 16:32:211002
10378407/14/2022 12:33:451001
10425607/20/2022 18:00:001002
10571007/29/2022 09:08:101001
Example Input:
ad_iduser_idad_datetimecampaign_id
90145107/04/2022 14:11:331001
90296807/09/2022 16:30:121002
90378407/14/2022 12:30:121001
90489007/20/2022 18:00:001001
90512307/29/2022 09:00:001002
Example Input:
view_iduser_idview_datetimecampaign_id
80145107/04/2022 14:15:121001
80296807/09/2022 16:40:451002
80371007/29/2022 09:25:501001

Answer:


In this block of SQL, the window of time is limited to the month of July. In the first clause, the total number of ads served and the total number of ads clicked is determined for each campaign. In the second clause, the total number of ads clicked and the total number of product views is also calculated for each campaign. The final statement merges these two derived tables and calculates the CTR and PVTR for each campaign by dividing the appropriate counts.

To solve a related problem on DataLemur's free online SQL coding environment, solve this Meta SQL interview question: Facebook App CTR SQL Interview question

SQL Question 9: Analyzing Vulnerability Scan Data

Qualys, as a provider of cloud security, compliance and related services, largely deals with security vulnerability data. Suppose Qualys has a table named that logs each vulnerability scan performed on a client's system.

Each row represents a single scan, detailing the client (given by ), the date when the scan was carried out (), the type of vulnerability scan (), and the total vulnerabilities found ().

We want to find out the highest number of vulnerabilities found in a single scan for each client, per scan type.

Example Input:

scan_idclient_idscan_datescan_typevulnerabilities_found
00157608/07/2022Network254
00257608/10/2022Network244
00342308/15/2022Web35
00442308/16/2022Web40
00557608/20/2022Web78
00642308/25/2022Web33

Example Output:

client_idscan_typemax_vulnerabilities
576Network254
576Web78
423Web40

Answer:


This query groups the rows by and . For each group created, it finds and returns the row with the highest number of , as determined by the aggregate function . The clause at the end simply orders the output by for clarity.

SQL Question 10: Can you explain the distinction between a clustered and a non-clustered index?

Clustered indexes have a special characteristic in that the order of the rows in the database corresponds to the order of the rows in the index. This is why a table can only have one clustered index, but it can have multiple non-clustered indexes.

The main difference between clustered and non-clustered indexes is that the database tries to maintain the order of the data in the database to match the order of the corresponding keys in the clustered index. This can improve query performance as it provides a linear-access path to the data stored in the database.

SQL Question 11: Find Customers with Email

Given the table, find all the customer records where the email domain is .

Example Input:
customer_idfirst_namelast_nameemail
27JohnSmithjohnsmith@qualys.com
34JaneDoejanedoe@gmail.com
63MarkDavismarkdavis@qualys.com
74CynthiaJohnsoncynthiajohnson@yahoo.com
83SarahPowellsarahpowell@qualys.com
Example Output:
customer_idfirst_namelast_nameemail
27JohnSmithjohnsmith@qualys.com
63MarkDavismarkdavis@qualys.com
83SarahPowellsarahpowell@qualys.com

Answer:


This SQL query will return all the records from the table where the column ends with . In PostgreSQL, the keyword is used to match text string patterns. The symbol in the clause is a wildcard character that matches any sequence of characters. So, matches any string that ends with .

How To Prepare for the Qualys SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Qualys SQL interview is to solve as many practice SQL interview questions as you can! In addition to solving the above Qualys SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Microsoft, Google, Amazon, and tech startups. DataLemur SQL and Data Science Interview Questions

Each SQL question has hints to guide you, step-by-step solutions and crucially, there's an online SQL code editor so you can easily right in the browser your SQL query and have it executed.

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

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

DataLemur SQL tutorial

This tutorial covers SQL concepts such as GROUP BY and filtering data with WHERE – both of these pop up routinely in SQL job interviews at Qualys.

Qualys Data Science Interview Tips

What Do Qualys Data Science Interviews Cover?

In addition to SQL query questions, the other types of questions to prepare for the Qualys Data Science Interview are:

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

Qualys Data Scientist

How To Prepare for Qualys Data Science Interviews?

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  • 201 interview questions sourced from FAANG, tech startups, and Wall Street
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