8 Concentrix SQL Interview Questions (Updated 2024)
Data Science, Data Engineering and Data Analytics employees at Concentrix use SQL for analyzing customer interaction data for business intelligence, such as sentiment analysis of customer feedback to improve customer satisfaction. It is also used for managing databases for client service efficiency optimization, like streamlining customer support workflows, which is why Concentrix often asks SQL questions during job interviews.
To help you practice for the Concentrix SQL interview, we've collected 8 Concentrix SQL interview questions – scroll down to start solving them!
8 Concentrix SQL Interview Questions
SQL Question 1: Identify Top Spending Customers of Concentrix
Concentrix is a multinational customer services company that provides a range of services such as technology solutions, analytics, and consulting. As a data analyst, your task is to identify the top 5 customers who have spent the most amount of money on Concentrix services in the past 30 days.
The company tracks its customer interactions using two tables in its database.
Example Input:
| customer_id | customer_name |
|---|---|
| 1 | John Doe |
| 2 | Sarah Connor |
| 3 | Luke Skywalker |
| 4 | Bruce Wayne |
| 5 | Anakin Skywalker |
Example Input:
| transaction_id | customer_id | transaction_date | amount |
|---|---|---|---|
| 1 | 1 | 2022-08-01 | 500.00 |
| 2 | 2 | 2022-08-03 | 400.00 |
| 3 | 3 | 2022-08-20 | 600.00 |
| 4 | 1 | 2022-08-21 | 500.00 |
| 5 | 5 | 2022-08-25 | 700.00 |
| 6 | 2 | 2022-08-30 | 400.00 |
| 7 | 1 | 2022-08-31 | 500.00 |
Answer:
The following PostgreSQL query will give us the list of top 5 customers who spent the most amount of money on Concentrix services within the last 30 days.
The above query joins the customers and transactions tables on customer_id. The WHERE clause is used to filter out transactions that took place more than 30 days ago. Then, we group by customer_name and calculate the sum of transaction amounts for each customer. Finally, we order the customers in descending order of total_spent and limit the output to the top 5 customers.
To practice a similar power-user data analysis problem question on DataLemur's free interactive coding environment, try this recently asked Microsoft SQL interview question:
SQL Question 2: Employees Earning More Than Managers
Given a table of Concentrix employee salaries, write a SQL query to find employees who make more than their direct boss.
Concentrix Example Input:
| employee_id | name | salary | department_id | manager_id |
|---|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 | |
| 2 | Daniel Rodriguez | 2230 | 1 | 10 |
| 3 | Olivia Smith | 8000 | 1 | 8 |
| 4 | Noah Johnson | 6800 | 2 | 8 |
| 5 | Sophia Martinez | 1750 | 1 | 10 |
| 8 | William Davis | 7000 | 2 | NULL |
| 10 | James Anderson | 4000 | 1 | NULL |
Example Output:
| employee_id | employee_name |
|---|---|
| 3 | Olivia Smith |
This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.
You can solve this question interactively on DataLemur:
Answer:
First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.
If the solution above is tough, you can find a step-by-step solution here: Employees Earning More Than Managers.
SQL Question 3: What's the difference between and clause?
The clause is used to filter the groups created by the clause. It's similar to the clause, but it is used to specify conditions on the groups created by the clause, rather than on the individual rows of the table.
For example, say you were analyzing salaries for analytics employees at Concentrix:
This query retrieves the total salary for each Analytics department at Concentrix and groups the rows by the specific department (i.e. "Marketing Analytics", "Business Analytics", "Sales Analytics" teams).
The clause then filters the groups to include only Concentrix departments where the total salary is greater than $1 million.
SQL Question 4: Analyzing Call Center Data
Concentrix, being a business services company, would have call center data. An interview question could involve the analysis of call and agent performance using window functions.
Suppose you are given a database of records for calls received by Concentrix, and you are to calculate the average call duration per agent each month. Also figure out the rank of each agent based on the average call duration within a specific month.
Example Input:
| call_id | agent_id | call_duration | call_start_time |
|---|---|---|---|
| 1 | 101 | 250 | 2022-06-01 09:00:00 |
| 2 | 102 | 300 | 2022-06-02 10:00:00 |
| 3 | 101 | 400 | 2022-06-03 11:00:00 |
| 4 | 103 | 350 | 2022-06-30 15:00:00 |
| 5 | 102 | 310 | 2022-07-01 09:00:00 |
| 6 | 103 | 400 | 2022-07-02 09:50:00 |
| 7 | 101 | 480 | 2022-07-03 08:00:00 |
| 8 | 102 | 280 | 2022-07-30 14:00:00 |
Expected Output:
| mth | agent | avg_call_duration | rank |
|---|---|---|---|
| 6 | 101 | 325.0 | 2 |
| 6 | 102 | 300.0 | 3 |
| 6 | 103 | 350.0 | 1 |
| 7 | 101 | 480.0 | 1 |
| 7 | 102 | 295.0 | 3 |
| 7 | 103 | 400.0 | 2 |
Answer:
The following SQL script will compute the desired analysis:
Explanation: The script first extracts the month from each call's start time and calculcates the average of call durations by agent for each month using a window function. Then it orders these averages to rank the agents within each month, also using a window function. The 'PARTITION BY' clause is used to group the records appropriately before applying the window function, and the 'ORDER BY' clause is used to set the ranking order. The DESC keyword ensures that the agent with the highest average call duration gets the top rank.
p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: What's the main difference between ‘BETWEEN’ and ‘IN’ operators?
While both the and operators are used to filter data based on some criteria, selects for values within a given range, whereas for it checks if the value is in a given list of values.
For example, say you had a table called , which had the salary of the employee, along with the country in which they reside.
To find all employees who made between 120k, you could use the operator:
To find all employees that reside in the US or Canada, you could use the operator:
SQL Question 6: Filter the customer records
Concentrix has a large customer database. The company wants to filter its customer records based on their location (city and country), their registration date, and whether they are a VIP customer or not. The company is particularly interested in VIP customers who are based in the United States and have registered in the last three months.
Write a SQL query that filters the customer records based on these parameters.
Example Input:
| customer_id | first_name | last_name | city | country | register_date | is_vip |
|---|---|---|---|---|---|---|
| 1001 | John | Smith | San Francisco | United States | 07/10/2022 | true |
| 1002 | Sarah | Brown | Manchester | United Kingdom | 05/15/2022 | false |
| 1003 | Michael | Taylor | New York | United States | 08/01/2022 | true |
| 1004 | Emily | Wilson | Paris | France | 06/20/2022 | true |
| 1005 | David | Johnson | Los Angeles | United States | 04/12/2022 | false |
| 1006 | Emma | Moore | Chicago | United States | 07/28/2022 | true |
Answer:
This query filters for VIP customers based in the United States who registered within the last three months. We use the expression to capture all dates within the last three months. The operator is used to check if a column's value is equal to the specified value, and the operator is used to combine multiple conditions.
SQL Question 7: Can you explain what SQL constraints are, and why they are useful?
Constraints are just rules your DBMS has to follow when updating/inserting/deleting data.
Say you had a table of Concentrix products and a table of Concentrix customers. Here's some example SQL constraints you'd use:
NOT NULL: This constraint could be used to ensure that certain columns in the product and customer tables, such as the product name and customer email address, cannot contain NULL values.
UNIQUE: This constraint could be used to ensure that the product IDs and customer IDs are unique. This would prevent duplicate entries in the respective tables.
PRIMARY KEY: This constraint could be used to combine the NOT NULL and UNIQUE constraints to create a primary key for each table. The product ID or customer ID could serve as the primary key.
FOREIGN KEY: This constraint could be used to establish relationships between the Concentrix product and customer tables. For example, you could use a foreign key to link the customer ID in the customer table to the customer ID in the product table to track which products each customer has purchased.
CHECK: This constraint could be used to ensure that certain data meets specific conditions. For example, you could use a CHECK constraint to ensure that Concentrix product prices are always positive numbers.
DEFAULT: This constraint could be used to specify default values for certain columns. For example, you could use a DEFAULT constraint to set the customer registration date to the current date if no value is provided when a new customer is added to the database.
SQL Question 8: Calculate the Average Handling Time of Calls per Agent
You work at Concentrix, a multinational that specializes in customer engagement and improving business performance. You have been tasked with monitoring agents' performance in the call center department. The key performance indicator here is the Average Handling Time (AHT) per agent.
The Average Handling Time is calculated as the total handling time (talk time + hold time + after call work time) divided by the total number of calls handled.
Using the table, write a SQL query to calculate the AHT per agent for the month of August 2021.
Example Input:
| call_id | agent_id | call_date | talk_time_seconds | hold_time_seconds | after_call_work_seconds | resolved |
|---|---|---|---|---|---|---|
| 6241 | 127 | 08/05/2021 09:10:25 | 1560 | 120 | 240 | true |
| 7203 | 256 | 08/11/2021 13:45:45 | 2240 | 300 | 360 | true |
| 5202 | 127 | 08/14/2021 15:03:00 | 1450 | 150 | 300 | false |
| 6034 | 256 | 08/25/2021 08:26:11 | 1980 | 240 | 420 | true |
| 4189 | 783 | 08/19/2021 11:48:00 | 1720 | 120 | 240 | false |
Example Output:
| ** agent_id** | avg_handling_time_seconds |
|---|---|
| 127 | 1705 |
| 256 | 2200 |
| 783 | 1860 |
Answer:
This SQL query first selects all of the calls that occurred in August 2021. Then, for each agent, it calculates the average handling time (in seconds) by summing the talk time, hold time and after-call work time for each call, and then dividing by the total number of calls. This provides an indication of each agent's efficiency and effectiveness in handling calls.
Preparing For The Concentrix SQL Interview
The best way to prepare for a Concentrix SQL interview is to practice, practice, practice. In addition to solving the earlier Concentrix SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.
Each DataLemur SQL question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and most importantly, there's an interactive coding environment so you can right online code up your SQL query answer and have it checked.
To prep for the Concentrix SQL interview it is also helpful to solve SQL questions from other consulting and professional service companies like:
But if your SQL coding skills are weak, don't worry about going right into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.
This tutorial covers things like sorting results with ORDER BY and advantages of CTEs vs. subqueries – both of which pop up frequently in Concentrix SQL assessments.
Concentrix Data Science Interview Tips
What Do Concentrix Data Science Interviews Cover?
In addition to SQL interview questions, the other topics to prepare for the Concentrix Data Science Interview include:
- AB Testing & Experimentation Questions
- Python Pandas or R Coding Questions
- Product Analytics Questions
- ML Modelling Questions
- Behavioral Interview Questions
How To Prepare for Concentrix Data Science Interviews?
To prepare for the Concentrix Data Science interview have a deep understanding of the company's values and company principles – this will be important for acing the behavioral interview. For technical interviews get ready by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from Facebook, Google, & Amazon
- A Refresher on Python, SQL & ML
- Amazing Reviews (1000+ 5-star reviews on Amazon)