10 Palo Alto Networks SQL Interview Questions (Updated 2024)
At Palo Alto Networks, SQL is used across the company for analyzing network security data and cybersecurity-related data. That's why Palo Alto Networks often tests SQL query questions during interviews for Data Analyst, Data Science, and BI jobs.
So, if you want to ace the SQL Interview, we've curated 10 Palo Alto Networks SQL interview questions to practice, which are similar to recently asked questions at Palo Alto Networks – can you solve them?
10 Palo Alto Networks SQL Interview Questions
SQL Question 1: Analyzing Power Users of Palo Alto Network's Products
Palo Alto Networks provides protection to hundreds of thousands of companies. One of their keys to success is understanding their power users - users who make frequent and high-value purchases. For the sake of this exercise, let's define a 'power user' as a customer who has purchased more than 10 different products (uniqueness determined by product_id) and whose total purchase value exceeds $10,000.
The company has a table that model some hypothetical data that contains the following columns:
- sale_id (int) – The unique identifier of a sale.
- user_id (int) – The unique identifier of a user.
- purchase_date (timestamp) – The date when the product was purchased.
- product_id (int) – The unique identifier of a product.
- price (decimal) - The price of the product when it was sold.
Your task is to write a SQL query that can identify these power users. The output should include user_ids and total purchase value of all power users, sorted in descending order by total purchase value.
Example Input:
| sale_id | user_id | purchase_date | product_id | price |
|---|---|---|---|---|
| 1001 | 300 | 01/01/2022 00:00:00 | 500 | 200.00 |
| 1002 | 305 | 01/03/2022 00:00:00 | 505 | 800.00 |
| 1003 | 300 | 02/01/2022 00:00:00 | 501 | 250.00 |
| 1004 | 310 | 02/07/2022 00:00:00 | 502 | 150.00 |
| 1005 | 300 | 02/15/2022 00:00:00 | 503 | 350.00 |
| 1006 | 305 | 02/20/2022 00:00:00 | 506 | 1100.00 |
| 1007 | 300 | 03/01/2022 00:00:00 | 504 | 200.00 |
Answer:
The above SQL query first creates a derived table where for each record, it computes the number of distinct products each user has purchased using the window function. Then, it filters for users who purchased more than 10 different products and also calculates the total purchase value for each user who meets the criteria. Finally, the query retains the results for users whose total purchase value exceeds $10,000 and sort the results by total purchase value in descending order.
To solve another question about calculating rates, try this TikTok SQL Interview Question on DataLemur's interactive coding environment:
SQL Question 2: Calculate the daily average issue response time.
As a network security company, Palo Alto Networks regularly deals with issues raised by its customers. For this scenario, assume that each issue has a unique id, a start time when the issue was reported, and an end time when the issue was resolved. All times are recorded in UTC.
Your task is to calculate the daily average response time for issues. Average response time for a day is defined as the average of the time differences (in minutes) between the end time and the start time of each issue reported that day.
Use the table for this problem.
Example Input:
| issue_id | start_time | end_time |
|---|---|---|
| 1001 | 2022-07-01 08:30:00 | 2022-07-01 09:30:00 |
| 1002 | 2022-07-01 09:00:00 | 2022-07-01 09:45:00 |
| 1003 | 2022-07-02 10:00:00 | 2022-07-02 11:00:00 |
| 1004 | 2022-07-02 11:00:00 | 2022-07-02 12:30:00 |
| 1005 | 2022-07-03 11:00:00 | 2022-07-03 14:00:00 |
Example Output:
| date | average_response_time |
|---|---|
| 2022-07-01 | 52.50 |
| 2022-07-02 | 75.00 |
| 2022-07-03 | 180.00 |
Answer:
This query first calculates the difference between end_time and start_time in minutes using . We then group these time differences by day and calculate the average. Finally, we order the result by .
To solve a similar problem on DataLemur's free interactive SQL code editor, try this Facebook SQL Interview question:
SQL Question 3: What's a foreign key?
A foreign key is a column or group of columns in a table that refers to the primary key in another table. The foreign key constraint helps maintain referential integrity between the two tables. The table with the foreign key is called the child table, while the table with the candidate key is called the parent or referenced table.
For example, consider a database with two tables: and customer_idcustomer_idcustomer_id` column in Palo Alto Networks customers table.
SQL Question 4: Calculate Click-Through-Rate for Palo Alto Networks Ads
Suppose that Palo Alto Networks wants to assess the effectiveness of its recent digital ads campaign. The company tracks two main user activities; the number of times an ad has been viewed () and the number of times a viewed ad leads to a click (). The click-through-rate (CTR) can be calculated by dividing the number of ad clicks by the number of ad views.
Given two tables, and , with each row in representing a single view of an ad and each row in representing a single click on an ad, determine the overall click-through-rate for Palo Alto Networks ads.
Example Input:
| view_id | user_id | view_date | ad_id |
|---|---|---|---|
| 12345 | 555 | 06/04/2022 00:00:00 | 1001 |
| 23456 | 666 | 06/05/2022 00:00:00 | 1002 |
| 34567 | 777 | 06/06/2022 00:00:00 | 1003 |
| 45678 | 888 | 06/07/2022 00:00:00 | 1004 |
Example Input:
| click_id | user_id | click_date | ad_id |
|---|---|---|---|
| 54321 | 555 | 06/04/2022 00:00:00 | 1001 |
| 65432 | 666 | 06/05/2022 00:00:00 | 1002 |
Answer:
This SQL query first separately counts the total number of views and clicks from and tables respectively. It then does a cross join between these derived sub-queries to calculate the overall click-through-rate (CTR) by dividing the count of total clicks by the count of total views and multiplying by 100 to get the percentage. Please note that we cast to FLOAT to perform the division correctly.
To practice a related SQL interview question on DataLemur's free online SQL code editor, solve this Meta SQL interview question:
SQL Question 5: How do you identify records in one table that aren't in another?
To locate records in one table that are absent from another, you can use a and then look for values in the right-side table.
For example, say you exported Palo Alto Networks's CRM (Customer Relationship Management) database, and had a table of sales leads, and a second table of companies.
Here's an example of how a query can find all sales leads that are not associated with a company:
This query returns all rows from the sales leads table, along with any matching rows from the companies table. If there is no matching row in the companies table, values will be returned for all of the right table's columns. The clause then filters out any rows where the column is , leaving only sales leads that are NOT associated with a company.
SQL Question 6: Average Selling Price Per Product Category
Palo Alto Networks, being a global cybersecurity leader, offers a variety of products in different categories. The company would like to know the average selling price for each product category over a specific period, for strategic decision making.
Consider the following tables and . The table has information on product id, name and their respective categories. The table records each sale with specific details including sales price, product id and date of sale.
Example Input:
| product_id | product_name | category |
|---|---|---|
| 1 | Firewall A | Firewall |
| 2 | Antivirus B | Antivirus |
| 3 | Intrusion Prevention C | Intrusion Prevention |
| 4 | Firewall D | Firewall |
| 5 | Antivirus E | Antivirus |
Example Input:
| sale_id | product_id | sale_date | sale_price |
|---|---|---|---|
| 1001 | 1 | 2022-01-01 | 2000 |
| 1002 | 2 | 2022-01-10 | 1500 |
| 1003 | 3 | 2022-02-15 | 3000 |
| 1004 | 4 | 2022-02-20 | 2500 |
| 1005 | 5 | 2022-03-01 | 1800 |
Example Output:
| category | average_sale_price |
|---|---|
| Firewall | 2250 |
| Antivirus | 1650 |
| Intrusion Prevention | 3000 |
Answer:
To solve this problem, we would need to first join the and table on to gather product categories and respective prices in one table. Then, we apply the clause on product category and use the function to calculate the average sale price per category.
This returns the average sale price for each product category, which can guide strategic business decisions in the areas of sales and product development.
To practice another question about calculating rates, try this TikTok SQL question on DataLemur's interactive coding environment:
SQL Question 7: Can you explain the meaning of database denormalization?
Denormalization is a technique used to improve the read performance of a database, typically at the expense of some write performance.
By adding redundant copies of data or grouping data together in a way that does not follow normalization rules, denormalization improves the performance and scalability of a database by eliminating costly join operations, which is important for OLAP use cases that are read-heavy and have minimal updates/inserts.
SQL Question 8: Filter customer records based on email domain
At Palo Alto Networks, different customers can be distinguished based on their email domain. Suppose we are interested in finding all customers from our customer database who have a specific email provider. For example, a recent marketing campaign focused on and we want to examine its effectiveness.
For this reason, create a SQL query that filters all customers from our table who have an email that ends with .
Example Input:
| customer_id | name | signup_date | |
|---|---|---|---|
| 1 | John Doe | john.doe@gmail.com | 2018-05-15 |
| 2 | Jane Doe | jane.doe@yahoo.com | 2019-06-20 |
| 3 | Mary Johnson | mary.j@gmail.com | 2020-02-05 |
| 4 | James Smith | james.smith@google.com | 2017-11-30 |
| 5 | Adam Edwards | adam.e@gmail.com | 2021-08-10 |
Answer:
Example Output:
| customer_id | name | signup_date | |
|---|---|---|---|
| 1 | John Doe | john.doe@gmail.com | 2018-05-15 |
| 3 | Mary Johnson | mary.j@gmail.com | 2020-02-05 |
| 5 | Adam Edwards | adam.e@gmail.com | 2021-08-10 |
The query solution uses the keyword to filter customers who signed up using a email. The wildcard character is used to match any sequence of characters before . As a result, the query will return all customers with a gmail account.
To practice a similar SQL problem on DataLemur's free online SQL coding environment, solve this Meta SQL interview question:
SQL Question 9: Analyzing Customer Order History
As a database administrator at Palo Alto Networks, you have been tasked with analyzing the customer order history. You have two tables at your disposal - and .
Your task is to write a SQL query that joins the two tables to produce a report that summarises the number of orders made by each customer over the past year. More specifically, the result should include each customer's id, name and the total number of orders they made in the past year.
Example Input:
| customer_id | first_name | last_name |
|---|---|---|
| 1001 | John | Doe |
| 1002 | Jane | Doe |
| 1003 | Sandra | Albert |
Example Input:
| order_id | customer_id | order_date |
|---|---|---|
| 2001 | 1001 | 2021-09-10 |
| 2002 | 1001 | 2021-11-15 |
| 2003 | 1002 | 2022-02-20 |
| 2004 | 1001 | 2022-04-28 |
| 2005 | 1003 | 2022-05-12 |
Answer:
This query uses a LEFT JOIN to combine the two tables, matches rows based on the customer_id field, and filters out records where the order_date is not within the past year. The COUNT function is used to calculate the total number of orders per customer. The GROUP BY clause is used to group the result set by customer details.
To practice a similar SQL problem on DataLemur's free online SQL code editor, attempt this Facebook SQL Interview question:
SQL Question 10: Can you explain the purpose of the constraint and give an example of when you might 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 Palo Alto Networks'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.
Palo Alto Networks SQL Interview Tips
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews.
Besides solving the earlier Palo Alto Networks SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like FAANG tech companies and tech startups.
Each DataLemur SQL question has hints to guide you, detailed solutions and crucially, there's an interactive coding environment so you can instantly run your SQL query answer and have it executed.
To prep for the Palo Alto Networks SQL interview you can also be helpful to solve interview questions from other tech companies like:
But if your SQL skills are weak, forget about diving straight into solving questions – strengthen your SQL foundations with this free SQL for Data Analytics course.
This tutorial covers SQL topics like window functions like RANK() and ROW_NUMBER() and filtering on multiple conditions using AND/OR/NOT – both of these show up routinely during Palo Alto Networks interviews.
Palo Alto Networks Data Science Interview Tips
What Do Palo Alto Networks Data Science Interviews Cover?
For the Palo Alto Networks Data Science Interview, beyond writing SQL queries, the other types of questions to practice:
- Probability & Stats Questions
- Python or R Programming Questions
- Business Sense and Product-Sense Questions
- Machine Learning and Predictive Modeling Questions
- Behavioral Interview Questions
Debating between Cybersecurity and Data Science? Read about the skills required and career paths each role opens up for you.
How To Prepare for Palo Alto Networks Data Science Interviews?
The best way to prepare for Palo Alto Networks Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from companies like Google, Tesla, & Goldman Sachs
- A Refresher on Product Analytics, SQL & ML
- Amazing Reviews (900+ reviews, 4.5-star rating)