10 Verint Systems SQL Interview Questions (Updated 2024)

Data Analysts & Data Scientists at Verint Systems code up SQL queries all the time as part of their job. They use SQL for data extraction from large databases for security analytics and customer engagement insights. It's also utilized in handling structured customer interaction data for intelligent self-service solutions. That's why Verint Systems asks prospective hires SQL interview questions.

Thus, to help you prep for the Verint Systems SQL interview, here’s 10 Verint Systems SQL interview questions in this article.

10 Verint Systems SQL Interview Questions

SQL Question 1: Fetching the 'Power Users' in Verint Systems

Verint Systems is a company that provides actionable intelligence solutions. An important part of their business might be users regularly participating in community forums they run, answering other users' questions, and buying their products very frequently.

Your task is to write a SQL query that will fetch the 'power users' from the user database of Verint systems. 'Power Users' are the users who bought more than 50 products and answered more than 200 queries on the community forum in the last month.

Example Input:

Example Input:

Example Input:

Answer:

We will join the two tables on user id (buyer_id = user_id and responder_id = user_id), and then group by the user id to get the counts. Lastly, we filter the users who bought more than 50 products and answered more than 200 queries.

Following this query, we will have a list of 'power users', their user_id and username. Each of these users bought more than 50 products and answered more than 200 queries on the community forum during June of 2022. The first join is between the users and the products tables to get users who purchased more than 50 products, then we join with the forum replies table to get users who answered more than 200 queries.

To solve a similar power-user data analysis problem question on DataLemur's free interactive coding environment, try this Microsoft Teams Power User SQL Interview Question:

SQL Question 2: Top 3 Department Salaries

Given a table of Verint Systems employee salary data, write a SQL query to find the top three highest paid employees within each department.

Verint Systems Example Input:

Example Input:

Example Output:

Try this problem interactively on DataLemur:

Answer:

We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.

If the code above is tough, you can find a detailed solution here: Top 3 Department Salaries.

SQL Question 3: Could you explain what a self-join is and provide examples of when it might be used?

A self-join is a type of JOIN where a table is joined to itself. To execute a self-join, you must include the table name twice in the FROM clause and assign a different alias to each instance. You can then join the two copies of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.

One common use case for self-joins is to compare data within a single table. For example, you might use a self-join to compare the salaries of employees within the same department, or to identify pairs of products that are frequently purchased together (like in this real Walmart SQL interview question)[https://datalemur.com/questions/frequently-purchased-pairs].

For a more concrete example, imagine you had website visitor data for Verint Systems, exported from the company's Google Analytics account. To help the web-dev team, you needed to analyze pairs of pages for UX or navigational issues. As part of that analysis, you wanted to produce all pairs of URLs, but needed to exclude pairs where both URLs were the same since that is not a valid pair.

You could use the following self-join:

This query retrieves the url of each page () along with the url of the page that referred to it (). The self-join is performed using the , which identifies the id of the page that referred the visitor to the current page, and excludes any pages that referred to themselves (i.e., data anomalies since pages shouldn't refer to themself).

SQL Question 4: Analysis of Software Usage

As per the business operations of Verint Systems, which specializes in Actionable Intelligence® solutions, you are asked to analyze the usage of their software products by different clients over time.

Verint has a table that logs each usage of a software product with a , by , and . Another table stores the details of each product with , and .

This is a two-fold question:

Part A: Write a SQL query that returns the total usage for each software product in each month of the year 2022.

Part B: Write another SQL query to rank the products for each month based on the total usage, under each product type.

Example Input:

Example Input:

Answer:

Part A:

This query joins the table with the table on , and for each month of the year 2022, it returns the total usage of each product.

Part B:

This query follows the pattern of the previous query, but introduces a window function (RANK) to rank the products for each month based on the total usage, under each product type.

p.s. Window functions show up pretty frequently during SQL interviews, so practice the 27+ window function questions on DataLemur

SQL Question 5: What is the role of the constraint in SQL?

The constraint is used to establish a relationship between two tables in a database. This ensures the referential integrity of the data in the database.

For example, if you have a table of Verint Systems customers and an orders table, the customer_id column in the orders table could be a that references the id column (which is the primary key) in the Verint Systems customers table.

SQL Question 6: Calculating Average Daily Sales for Different Products

For a company like Verint Systems, which provides actionable intelligence solutions around the world, one possible question could involve calculating the average daily sales for different products.

Say Verint Systems wants to identify how well their products are performing on a daily basis. They want to find the average daily sales quantity of each product over the last 30 days.

You have been given access to the sales table, which contains records of every item sold each day. Write a SQL query to calculate the average daily sales for each product.

Example Input:

Example Output:

Answer:

This PostgreSQL query retrieves the product_id and the average quantity sold for each product from the table where the sale_date is within the last 30 days. By grouping by product_id, it calculates the average on a per-product basis.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for requiring sales aggregation per product or this Wayfair Y-on-Y Growth Rate Question which is similar for requiring daily sales analysis.

SQL Question 7: What are the similarities and differences between a clustered index and non-clustered index?

Here is an example of a clustered index on the column of a table of Verint Systems customer transactions:

This creates a clustered index on the column, which will determine the physical order of the data rows in the table.

Here is an example of a non-clustered index on the column of the same table:

This will create a non-clustered index on the column, which will not affect the physical order of the data rows in the table.

In terms of query performance, a clustered index is usually faster for searches that return a large number of records, while a non-clustered index is faster for searches that return a small number of records. However, updates to a clustered index are slower, as they require the data rows to be physically rearranged, while updates to a non-clustered index are faster, as they only require the index data structure to be updated.

SQL Question 8: Analyzing Click-through rates for Verint Systems.

Verint Systems Inc. is a global provider of Actionable Intelligence® solutions for customer engagement optimization, security intelligence, and fraud, risk, and compliance. Now consider a scenario where they are running an ad campaign having multiple Ad IDs for various product categories in different locations and they keep track of total impressions (number of times an ad is displayed) and total clicks received on each ad by product category and location. They want to analyze the effectiveness of the campaign by calculating the click-through rate which is the ratio of users who click on a specific link to the number of total users who view the ad (impressions).

Example Input:

Verint wants to know the click-through rate for each product category, location, and overall.

Answer:

This SQL query calculates the click-through rate for each product category in each location. It uses the formula ((clicks/impressions)*100) to get the click-through rate. The clicks and impressions columns are casted to decimal to allow for decimal division, otherwise, integer division would truncate results to whole numbers. The result is also rounded to two decimal places for better readability. The UNION ALL statement combines this result with a similar calculation done on the total clicks and impressions, giving us a summary line for all product categories and all locations.

To practice another question about calculating rates, try this TikTok SQL Interview Question within DataLemur's interactive SQL code editor:

SQL Question 9: Average Response Time by Month for Each Product

Verint Systems sells multiple products and has a team dedicated to answering customer inquiries related to each product. To better manage their efficiency, they want to find out the average response time of their support team for each product per month. Let's assume the support team logs every inquiry they respond to in a SupportLogs table.

Considering every inquiry has a and a , with this information, we can calculate the time taken to respond to each inquiry. The task is to create an SQL query that groups the average response time by month and product.

Example Input

Example Output:

Answer:

This query extracts the month from the and groups the data by this and the . The function is used to calculate the average response time for each group. The function is used to calculate the response time in hours for each record before the average is taken. Finally, the result is ordered by month and product for easier interpretation.

SQL Question 10: How does the constraint function, and in what scenarios might it be useful?

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. The CHECK constraint is often used with other constraints, such as NOT NULL or UNIQUE, to ensure that data meets certain conditions. You may want to use a CHECK constraint in your database if you want to maintain the quality and reliability of your data by ensuring that it meets specific criteria.

For example, you might use a CHECK constraint to ensure that a column contains only positive numbers, or that a date is within a certain range.

Verint Systems SQL Interview Tips

The key to acing a Verint Systems SQL interview is to practice, practice, and then practice some more! In addition to solving the above Verint Systems SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Google, Facebook, Microsoft and Amazon.

Each DataLemur SQL question has hints to guide you, step-by-step solutions and best of all, there is an online SQL coding environment so you can right in the browser run your query and have it checked.

To prep for the Verint Systems SQL interview it is also useful to practice SQL questions from other tech companies like:

• Zendesk SQL questions

• Five9 SQL questions

• Freshworks SQL questions

• NICE SQL questions

In case your SQL foundations are weak, forget about going right into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Scientists & Analysts.

This tutorial covers SQL concepts such as math functions in SQL and aggregate functions – both of which show up frequently during Verint Systems SQL interviews.

Verint Systems Data Science Interview Tips

What Do Verint Systems Data Science Interviews Cover?

Besides SQL interview questions, the other types of questions covered in the Verint Systems Data Science Interview include:

• Stats Interview Questions
• Python Pandas or R Coding Questions
• Product-Sense Questions
• Machine Learning Questions
• Behavioral Interview Questions

How To Prepare for Verint Systems Data Science Interviews?

I'm a tad biased, but I think the optimal way to prep for Verint Systems Data Science interviews is to read my book Ace the Data Science Interview.

The book covers 201 interview questions sourced from Microsoft, Amazon & startups. It also has a crash course covering Stats, SQL & ML. And finally it's vouched for by the data community, which is how it's gotten to be an Amazon best-seller with over 1000+ 5-star reviews.