9 Exclusive Networks SQL Interview Questions (Updated 2024)
At Exclusive Networks, SQL is often used for analyzing sales data to identify trends and in cybersecurity client engagemenets, espeically when securing client's databaseses. That's why Exclusive Networks almost always asks SQL coding questions during interviews for Data Science and Data Engineering positions.
So, to help you ace the Exclusive Networks SQL interview, we'll cover 9 Exclusive Networks SQL interview questions – able to solve them?
9 Exclusive Networks SQL Interview Questions
SQL Question 1: Find the Top Purchasing Customers
For "Exclusive Networks", a major activity that adds significant value to the business is purchasing high-end networking products. The "power users", or "VIP users", or "whale users" in this context would be those customers who consistently purchase a high volume of products or contribute significantly to sales revenue.
Your task is to write a SQL query, that will identify the top five customers making the highest total purchases in terms of sales value in a given year.
Example Input:
| order_id | customer_id | order_date | product_id | quantity | unit_price_usd |
|---|---|---|---|---|---|
| 3251 | 34 | 01/15/2021 00:00:00 | 101 | 8 | 699.00 |
| 4928 | 12 | 03/29/2021 00:00:00 | 202 | 2 | 1299.00 |
| 8842 | 89 | 03/02/2021 00:00:00 | 303 | 1 | 2999.00 |
| 2336 | 34 | 07/05/2021 00:00:00 | 403 | 3 | 499.00 |
| 4873 | 67 | 11/14/2021 00:00:00 | 102 | 5 | 799.00 |
Example Input:
| customer_id | first_name | last_name |
|---|---|---|
| 34 | John | Doe |
| 12 | Jane | Smith |
| 89 | Simon | Brown |
| 67 | Ashley | Johnson |
Answer:
Here is the SQL query which will solve this problem:
This query firstly joins the and tables based on the . It then filters out the orders placed in the year 2021. For each customer, it calculates the total purchase value by multiplying the quantity of each product with its unit price, and then summing them up. It finally orders the customers based on the total purchase value in descending order and limits the output to the top 5 customers. This serves to identify the power users or VIP customers based on their purchases.
To practice a related customer analytics question on DataLemur's free online SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:
SQL Question 2: Calculate monthly average sales per product
You are an IT specialist for Exclusive Networks and you've been given a dataset of product sales. Each row in the dataset represents one sale and has information about the product, the salesperson who made the sale, the date of the sale, and the price at which the product was sold.
Your task is to write a SQL query that uses a window function to calculate the monthly average sales price for each product.
Here is an example of what the table looks like:
Example Input:
| sale_id | salesperson_id | sale_date | product_id | price |
|---|---|---|---|---|
| 1 | 101 | 01/07/2022 | 202 | 5000 |
| 2 | 102 | 01/14/2022 | 203 | 7000 |
| 3 | 101 | 02/13/2022 | 202 | 5500 |
| 4 | 101 | 02/17/2022 | 203 | 7500 |
| 5 | 102 | 03/06/2022 | 202 | 5200 |
Your query should output a table with columns for the month, product_id, and the average sale price for that product in that month.
Answer:
This query first extracts the month portion from then uses a window function () to calculate the average sale price per product () for each month. The query also sorts the results by and for easier viewing.
The window function is useful here because it retains the original row data, unlike a GROUP BY operation. This allows us to obtain both individual sale data and aggregated data (avg_sale_price) in the same query.
For more window function practice, try this Uber SQL Interview Question within DataLemur's online SQL coding environment:
SQL Question 3: What's a database view?
Views are a lot like virtual tables, where you can take a base table and customize it (such as by hiding some data from non-admin users, or removing some random columns/rows based on business requirements).
Here's the PostgreSQL syntax for creating a view based on data in the table:
SQL Question 4: Finding Clients with Large Regular Transactions
Exclusive Networks is interested in identifying customers who regularly make high-value orders. They define a high-value order to be one that is greater than $10,000. Your task is to filter out the customers who have made more than 5 such orders in the past year.
Example Input:
| order_id | customer_id | order_date | order_value ($) |
|---|---|---|---|
| 8761 | 545 | 07/18/2021 | 15,000 |
| 6342 | 545 | 08/22/2021 | 10,500 |
| 9023 | 545 | 09/16/2021 | 11,250 |
| 7112 | 545 | 10/20/2021 | 12,750 |
| 8891 | 545 | 12/12/2021 | 14,000 |
| 4302 | 545 | 01/28/2022 | 9,000 |
| 9872 | 365 | 03/10/2022 | 10,500 |
| 4572 | 838 | 04/05/2022 | 15,500 |
Example Output:
| customer_id |
|---|
| 545 |
Answer:
This PostgreSQL query filters the table to find the of customers who have completed over 5 orders valued more than $10000 in the year 2022. The clause allows us to filter according to a condition that relies on the result of an aggregate function, in this case, .
SQL Question 5: What does it mean to use a UNIQUE constraint in a database?
A UNIQUE constraint ensures that all values in a column are different. It is often used in conjunction with other constraints, such as NOT NULL, to ensure that the data meets certain conditions.
For example, if you had Exclusive Networks employee data stored in a database, here's some constraints you'd use:
In the Exclusive Networks employee example, the UNIQUE constraint is applied to the "email" field to ensure that each employee has a unique email address. This helps to ensure the integrity of the data in the database and prevents errors that could occur if two employees had the same email address.
SQL Question 6: Average Sales per Product
Given our "Exclusive Networks" company operates in tech distribution, in this scenario, let's say that an interviewer might want to assess your knowledge on using the average function to determine economic insights.
To test your skills, here's the question:
What is the average sales per product for all the products sold by "Exclusive Networks" in the year 2020?
Please consider the data on two tables: "products" and "sales".
Example Input:
| product_id | product_name | price |
|---|---|---|
| 101 | Cisco Firewall | 1200 |
| 102 | Palo Alto Firewall | 1800 |
| 103 | Fortinet Firewall | 1500 |
| 104 | Juniper Router | 800 |
| 105 | Cisco Router | 900 |
Example Input:
| sale_id | product_id | quantity | sale_date |
|---|---|---|---|
| 201 | 101 | 5 | 01/15/2020 |
| 202 | 102 | 3 | 02/18/2020 |
| 203 | 102 | 8 | 03/10/2020 |
| 204 | 103 | 10 | 04/20/2020 |
| 205 | 104 | 9 | 05/25/2020 |
| 206 | 105 | 7 | 06/15/2020 |
| 207 | 101 | 8 | 07/17/2020 |
| 208 | 102 | 6 | 08/15/2020 |
| 209 | 103 | 9 | 09/18/2020 |
| 210 | 105 | 8 | 10/20/2020 |
| 211 | 104 | 10 | 11/23/2020 |
| 212 | 101 | 7 | 12/29/2020 |
Answer:
This query joins the products and sales tables with the product_id column, filters out the sales transactions according to the year 2020, and finally, calculates the average sales per product.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for analyzing product sales data or this Amazon Average Review Ratings Question which is similar for calculating averages from product data.
SQL Question 7: What's a correlated sub-query? How does it differ from a non-correlated sub-query?
hile a correlated subquery relies on columns in the main query's FROM clause and cannot function independently, a non-correlated subquery operates as a standalone query and its results are integrated into the main query.
An example correlated sub-query:
This correlated subquery retrieves the names and salaries of Exclusive Networks employees who make more than the average salary for their department. The subquery references the department column in the main query's FROM clause (e1.department) and uses it to filter the rows of the subquery's FROM clause (e2.department).
An example non-correlated sub-query:
This non-correlated subquery retrieves the names and salaries of Exclusive Networks employees who make more than the average salary for the Data Science department (which honestly should be very few people since Data Scientists are awesome and deserve to be paid well).The subquery is considered independent of the main query can stand alone. Its output (the average salary for the Data Science department) is then used in the main query to filter the rows of the Exclusive Networks employees table.
SQL Question 8: Filtering Customer Records
As a data scientist in the Exclusive Networks company, you often have to deal with vast customer records. One day, you get a special task from your manager. You are required to filter out all the customers whose email addresses end with "@exclusivenetworks.com".
You have the following table where customer records are stored:
Example Input:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 1234 | John | Doe | johndoe@exclusivenetworks.com |
| 5678 | Jane | Doe | janedoe@othermail.com |
| 9101 | Jack | Smith | jacksmith@exclusivenetworks.com |
| 1121 | Jill | Johnson | jilljohnson@exclusivenetworks.com |
| 3141 | Robert | Brown | robertbrown@othermail.com |
You need to write a SQL query which will retrieve the customer_id, first_name and last_name of all those customers whose email ends with "@exclusivenetworks.com".
Also explain briefly as to how your SQL query is working.
Answer:
The SQL query can be designed in PostgreSQL as follows:
This SQL query works by using the LIKE command in PostgreSQL to filter out the records which satisfy the condition. Here, "%" is a special character known as a wildcard that can represent zero, one or multiple characters. So, any string followed by '@exclusivenetworks.com' will be selected by this query. Hence, it filters out the customers whose email addresses end with "@exclusivenetworks.com".
SQL Question 9: Analyze Customer and Sales Data
As part of your job in Exclusive Networks, you are tasked to analyze customer behavior and their corresponding sales data. Two tables are provided; the table, containing details about the customers, and another table, , containing transaction details.
Your job is to write a SQL query to get the total sales for each customer along with the customer details. Include only those customers who have made at least one transaction.
Example Input:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 101 | John | Doe | john.doe@email.com |
| 102 | Jane | Smith | jane.smith@email.com |
| 103 | Jim | Brown | jim.brown@email.com |
| 104 | Jill | Johnson | jill.johnson@email.com |
Example Input:
| transaction_id | customer_id | sales_amount | transaction_date |
|---|---|---|---|
| 501 | 101 | 150.0 | 06/25/2022 00:00:00 |
| 502 | 101 | 200.0 | 07/02/2022 00:00:00 |
| 503 | 103 | 300.0 | 06/27/2022 00:00:00 |
| 504 | 104 | 250.0 | 06/29/2022 00:00:00 |
| 505 | 104 | 150.0 | 07/03/2022 00:00:00 |
Answer:
The above PostgreSQL query will execute the required task. It joins the and tables on the and then groups the result by (and also the other fields of the customers table to avoid grouping error) to calculate the total sales amount for each customer. The clause is used to filter only those customers who have made at least one transaction.
Because join questions come up frequently during SQL interviews, take a stab at an interactive SQL join question from Spotify:
Preparing For The Exclusive Networks SQL Interview
The best way to prepare for a Exclusive Networks SQL interview is to practice, practice, practice.
In addition to solving the earlier Exclusive Networks SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Google, Facebook, Microsoft and Amazon.
Each problem on DataLemur has multiple hints, step-by-step solutions and most importantly, there's an interactive SQL code editor so you can right in the browser run your SQL query answer and have it checked.
To prep for the Exclusive Networks SQL interview it is also wise to solve interview questions from other tech companies like:
But if your SQL query skills are weak, forget about diving straight into solving questions – go learn SQL with this DataLemur SQL Tutorial.
This tutorial covers things like creating summary stats with GROUP BY and CASE/WHEN/ELSE statements – both of which pop up often during SQL job interviews at Exclusive Networks.
Exclusive Networks Data Science Interview Tips
What Do Exclusive Networks Data Science Interviews Cover?
In addition to SQL interview questions, the other types of problems to practice for the Exclusive Networks Data Science Interview are:
- Stats Interview Questions
- Python or R Programming Questions
- Data Case Study Questions
- ML Modelling Questions
- Behavioral Based Interview Questions
How To Prepare for Exclusive Networks Data Science Interviews?
The best way to prepare for Exclusive Networks Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG & startups
- A Crash Course on Python, SQL & ML
- Great Reviews (900+ 5-star reviews on Amazon)