logo

8 Verint Systems SQL Interview Questions (Updated 2024)

Updated on

April 25, 2024

Verint Systems employees write SQL queries daily for analyzing customer interaction data for insights, and managing financial databases for fraud detection. That's the reason behind why Verint Systems typically asks SQL problems during interviews for Data Analyst, Data Science, and BI jobs.

To help prep you for the Verint Systems SQL interview, here's 8 Verint Systems SQL interview questions in this article.

8 Verint Systems SQL Interview Questions

SQL Question 1: Calculate the Monthly Average Response Time

Given a dataset of support tickets, write a SQL query to calculate the monthly average time it takes for a ticket to be closed. Use a window function in your solution.

Let's create the sample data for this problem:

Example Input:
ticket_idcreated_dateclosed_dateclosed
12022-01-012022-01-05true
22022-01-032022-01-06true
32022-01-102022-01-18true
42022-02-012022-02-06true
52022-02-032022-03-03true

For example, for January 2022, the average response time is the average of (5-1), (6-3), and (18-10) = (4+3+8)/3 = 5 days.

Expected Output
month_yearavg_response_time(days)
2022-015
2022-0218

Answer:

Here's a PostgreSQL query that solves this problem:


What this query does is that it first calculates the response time for each ticket in a subquery and creates a new column "response_time". Date_trunc function is used to truncate the date to month-year format. Then, it calculates the average response time for each month using the AVG function and groups the results by month.

Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur

DataLemur Window Function SQL Questions

SQL Question 2: Analyzing Customer Support Interactions

Verint Systems is a company that specializes in customer engagement and business intelligence platforms. Let's suppose Verint has a database that maintains records of customer support interactions.

Your task is to design a database model that can analyze customer interactions and identify the support issues that are taking the longest time to resolve. For this model, consider two factors: the time it takes from when a ticket is opened to when it is closed, and the number of interactions that happen before a ticket is closed.

The pertinent tables in the database could be and . Here are examples of how these tables might look:

Example Input:
ticket_idcustomer_idopen_dateclose_date
100012301/01/202201/03/2022
100145601/01/202201/05/2022
100278901/01/202201/02/2022
100312301/04/202201/08/2022
Example Input:
interaction_idticket_iddatemessage
5500100001/01/2022"Initial Issue"
5501100001/02/2022"Follow up"
5502100101/01/2022"Initial Issue"
5503100101/03/2022"Follow up"
5504100101/04/2022"Follow up"
5505100201/01/2022"Initial Issue"
5506100301/05/2022"Initial Issue"

Write a PostgreSQL query that, given a ticket id, returns the ticket id, the total number of days taken to resolve the ticket, and the number of interactions for the ticket.

Answer:


This query first joins the and tables on the column. It then filters the results to only those rows where the is the given ticket id. It groups the results by and , and selects the , the difference between the and as , and the count of for each ticket as . It will return the ticket id, the total number of days taken to resolve the ticket, and the number of interactions for the ticket.

SQL Question 3: What are the different kinds of joins in SQL?

In SQL, a join is used to combine rows from different tables based on a shared key or set of keys, resulting in a single merged table of data.

There are four distinct types of JOINs: , , , and .

(INNER) JOIN: Retrieves records that have matching values in both tables involved in the join.


LEFT (OUTER) JOIN: Retrieves all the records/rows from the left and the matched records/rows from the right table.


RIGHT (OUTER) JOIN: Retrieves all the records/rows from the right and the matched records/rows from the left table.


FULL (OUTER) JOIN: Retrieves all the records where there is a match in either the left or right table.


Verint Systems SQL Interview Questions

SQL Question 4: Filter Customer Records Based on Contract Status and Subscription Type

Verint Systems manages a database of their customers that includes their contract status and the type of subscription they have. They are interested in identifying potential clients for an upgrade campaign which they are planning for. For this campaign, they want to target customers who are on 'Active' contract status and are subscribed to the 'Basic' package. Write a SQL query to filter customer records for this specific condition.

Example Input:
customer_idnamecontract_statussubscription_type
101John SmithActiveBasic
102Michael JohnsonInactivePremium
103Amanda DavisActivePremium
104Maria RodriguezActiveBasic
105David MartinezInactiveBasic
Example Output:
customer_idnamecontract_statussubscription_type
101John SmithActiveBasic
104Maria RodriguezActiveBasic

Answer:


With the above query, PostgreSQL will first use the clause to identify the desired table, i.e., . Then, it will use the clause to choose the columns it needs from that table. The clause is used to filter the records under the chosen columns. The conditions in 'WHERE' clause use the logical operator 'AND' to ensure both conditions are met, i.e., is 'Active' and is 'Basic'. It will return details of customers who are both on 'Active' contract and have 'Basic' subscription.

SQL Question 5: What sets UNION apart from UNION ALL?

The operator combines two or more results from multiple SELECT queries into a single result. If it encounters duplicate rows, the multiple copies are removed (so there's only one instance of each would-be duplicate in the result set). Here's an example of a operator which combines all rows from and (making sure each row is unique):


The operator is similar to the operator but it does NOT remove duplicate rows!

SQL Question 6: Avg_rating_of_Products_Per_Month

Verint Systems is a company offering customer engagement and cybersecurity solutions. Suppose in a scenario, the company has an reviews database where customers provide ratings for different products. The goal is to write a SQL query that will provide an average rating of each product per month.

Here are the sample tables:

Example Input:
review_iduser_idsubmit_dateproduct_idstars
10110012021-05-102014
10210022021-07-202025
10310032021-05-172013
10410012021-07-222024
10510032021-07-302015
Example Output:
monthproduct_idavg_stars
52013.50
72024.50
72015.00

Answer:


In this query, we are getting the month from the using the function. We then group the results by the month and and calculate the average rating (). The results are ordered by month and to provide better readability.

SQL Question 7: What's a database view, and what's it used for?

Database views are virtual tables based on the results of a SQL statement. They're just like vanilla tables, except views allow you to create simplified versions of tables or hide sensitive data from certain users.

In PostgreSQL, you can create a view by using the command. Here's an example for the table:


SQL Question 8: Filter Customer Records

You are working as a data analyst at Verint Systems. You are given a task to filter down the customer records database to find customers whose email addresses end with '@verint.com'. You are also supposed to provide the number of customers that match this criteria.

Below is the representation of the customer record:

Sample Input:
customer_idfirst_namelast_nameemail_addresssign_up_date
5689JohnDoejohn.doe@verint.com01/05/2021
5642JaneSmithjane.smith@gmail.com06/10/2021
5821MikeWilliamsmike.williams@verint.com08/22/2020
5962EmilyClarkemily.clark@hotmail.com05/01/2020
6032ChrisJohnsonchris.johnson@verint.com04/18/2019
Example Output:
emailcount
@verint.com3

Answer:


The above SQL query filters the customer's email addresses using the LIKE keyword and the special character '%' which denotes any number of characters. It returns the count of customers which have email addresses ending with '@verint.com'.

How To Prepare for the Verint Systems SQL Interview

The best way to prepare for a Verint Systems SQL interview is to practice, practice, practice. In addition to solving the earlier Verint Systems SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies. DataLemur Question Bank

Each SQL question has hints to guide you, detailed solutions and crucially, there is an online SQL coding environment so you can easily right in the browser your SQL query answer and have it graded.

To prep for the Verint Systems SQL interview you can also be helpful to solve SQL problems from other tech companies like:

In case your SQL foundations are weak, don't worry about going right into solving questions – improve your SQL foundations with this SQL tutorial for Data Analytics.

Interactive SQL tutorial

This tutorial covers SQL concepts such as transforming strings with CONCAT()/LOWER()/TRIM() and UNION vs. joins – both of these pop up frequently in Verint Systems SQL assessments.

Verint Systems Data Science Interview Tips

What Do Verint Systems Data Science Interviews Cover?

In addition to SQL query questions, the other topics tested in the Verint Systems Data Science Interview are:

Verint Systems Data Scientist

How To Prepare for Verint Systems Data Science Interviews?

To prepare for Verint Systems Data Science interviews read the book Ace the Data Science Interview because it's got:

  • 201 interview questions sourced from FAANG tech companies
  • a refresher on Stats, ML, & Data Case Studies
  • over 900+ 5-star reviews on Amazon

Ace the Data Science Interview by Nick Singh Kevin Huo