9 PC Connection SQL Interview Questions (Updated 2024)
At PC Connection, SQL is frequently used to analyze customer purchasing behaviors, allowing the team to identify trends and preferences that drive sales. They also use SQL to optimize inventory management for IT products, ensuring they have the right stock on hand to meet customer demand, this is why PC Connection asks SQL coding questions in interviews for Data Science, Data Engineering, and Data Analytics jobs.
So, to help you prepare, here's 9 PC Connection SQL interview questions – how many can you solve?
9 PC Connection SQL Interview Questions
SQL Question 1: Find the Top Buying Customers at PC Connection
PC Connection is a leading direct marketer of business computing solutions to small- and medium-sized businesses, educational and government institutions, and consumers. A common analysis at PC Connection would be to find out the list of power users. Power users can be defined as customers who have made the most purchases. The task is to write a PostgreSQL query to find the top 5 customers who have made the most purchases.
Example Input:
| order_id | customer_id | product_id | purchase_date |
|---|---|---|---|
| 28472 | 1354 | 1002 | 2022-06-11 |
| 50193 | 2342 | 2003 | 2022-07-05 |
| 87293 | 3542 | 1002 | 2022-06-25 |
| 24531 | 2342 | 3004 | 2022-06-28 |
| 98472 | 3542 | 1002 | 2022-07-02 |
| 37492 | 2342 | 2003 | 2022-07-11 |
| 82573 | 1354 | 3004 | 2022-07-15 |
| 14753 | 2342 | 1002 | 2022-07-20 |
| 89572 | 1354 | 3004 | 2022-07-22 |
| 37251 | 3542 | 1002 | 2022-07-28 |
Answer:
This query works by aggregating on the column and counting the number of times a appears, which corresponds to the number of purchases. The clause sorts the output in descending order of . ensures that only the top 5 customers are returned, aligned with the 'power users' concept. The customers with the most number of purchases will be at the top.
To practice a related super-user data analysis question on DataLemur's free online SQL code editor, try this Microsoft Teams Power User SQL Interview Question:
Discover how PC Connection is harnessing the power of artificial intelligence to deliver innovative solutions that drive business success! Understanding PC Connection's approach to AI can provide valuable insights into how technology is being utilized to enhance productivity and streamline operations across various industries.
SQL Question 2: Second Highest Salary
Given a table of PC Connection employee salary data, write a SQL query to find the 2nd highest salary among all employees.
PC Connection Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
Write a SQL query for this problem and run your code right in the browser:
Answer:
You can find a step-by-step solution here: 2nd Highest Salary
SQL Question 3: What does the keyword do?
"The clause in SQL allows you to select records that are unique, eliminating duplicates.
For a tangible example, say you had a table of PC Connection employees:
| first_name | job_title |
|---|---|
| Akash | Data Analyst |
| Brittany | Data Scientist |
| Carlos | Data Engineer |
| Diego | Data Engineer |
| Eva | Data Analyst |
If you were doing an HR Analytics project and you wanted to get all the unique job titles that currently worked at the company, you would write the following SQL query:
The output would give you 3 distinct job titles at PC Connection:
| job_title |
|---|
| Data Analyst |
| Data Scientist |
| Data Engineer |
SQL Question 4: Analyzing Monthly Sales with Window Functions
As a data analyst at PC Connection, one of your tasks is to analyze sales data for each product in every month. Your job is to write a SQL query that calculates the average monthly sales for every product.
The table contains the following columns:
- (integer): the sale's unique identifier
- (integer): the product's unique identifier
- (integer): the number of units sold in this sale
- (datetime): the date and time of the sale
Your query should return a new table with the following columns:
- : the month of the sale (in YYYY-MM format)
- : the product's unique identifier
- : monthly average of quantity sold per product
Example Input:
| sale_id | product_id | quantity | sale_date |
|---|---|---|---|
| 1 | 100 | 5 | 2022-06-15 |
| 2 | 100 | 10 | 2022-06-20 |
| 3 | 200 | 7 | 2022-06-21 |
| 4 | 200 | 2 | 2022-07-01 |
| 5 | 100 | 4 | 2022-07-05 |
Example Output:
| month_id | product_id | avg_monthly_sales |
|---|---|---|
| 2022-06 | 100 | 7.50 |
| 2022-06 | 200 | 7.00 |
| 2022-07 | 100 | 4.00 |
| 2022-07 | 200 | 2.00 |
Answer:
This query first extracts the month from the column and groups by both product_id and month to calculate average sales. The clause in the function uses the statement to calculate the window frame on a per-product per-month basis. We then sort the result by and .
p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: How do you determine which records in one table are not present in a second table?
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 PC Connection'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: Sales Analysis for PC Connection
PC Connection, a key provider of IT solutions and services, required a database design that enables the tracking of its sales performance. They want to understand the number of products sold by product category each month.
Their need can be modeled using two tables: and .
table:
| sale_id | product_id | sale_date |
|---|---|---|
| 1 | 1001 | 09/01/2022 |
| 2 | 3001 | 09/10/2022 |
| 3 | 2001 | 09/18/2022 |
| 4 | 4001 | 10/13/2022 |
| 5 | 3001 | 10/29/2022 |
table:
| product_id | product_category |
|---|---|
| 1001 | Laptops |
| 2001 | Desktops |
| 3001 | Printers |
| 4001 | Software |
The company would like to have a monthly report that shows the volume of sales by each product category. The output should include the month of sale, product category, and the volume of sales.
Answer:
In this case, a JOIN operation is needed to combine the details from both Sales and Products tables. We also need to extract the month from sale_date and group the results by month and product category.
A PostgreSQL version query could look like the following:
This query will give us the number of products sold each month divided by product categories, ordering results by the sale month and the volume of product sales. Hence, enabling the company to track its sales performance by product category on a monthly basis.
SQL Question 7: What's the purpose of a foreign key?
A foreign key is a field in a database table that links to the primary key of another table, establishing a connection between the two tables. For example, let's analyze PC Connection's Google Ads campaigns data:
:
| ad_id | campaign_id | keyword | click_count |
|---|---|---|---|
| 1 | 201 | PC Connection reviews | 120 |
| 2 | 202 | PC Connection pricing | 150 |
| 3 | 101 | buy PC Connection | 65 |
| 4 | 101 | PC Connection alternatives | 135 |
is a foreign key that connects to the of the corresponding Google Ads campaign. This establishes a relationship between the ads and their campaigns, enabling easy querying to find which ads belong to a specific campaign or which campaigns a specific ad belongs to.
The table may also have multiple foreign keys that reference primary keys in other tables. For example, and foreign keys could be used to link each ad to its ad group and the Google Ads account that the campaigns belong to, respectively.
SQL Question 8: Find the average number of units sold for each product
As an analyst for PC Connection, an IT solutions provider, it is your responsibility to determine the average number of units sold for each product each month. The company sells a wide range of IT products, like software, hardware and related services. You have a table of sales data detailing each sale per product in the current year. The table, , includes columns for , , and . Write a SQL query to find the average number of units sold per month for each product.
Example Input:
| sale_id | sale_date | product_id | units_sold |
|---|---|---|---|
| 1257 | 01/02/2022 | 5601 | 15 |
| 6524 | 01/10/2022 | 9904 | 9 |
| 5278 | 01/15/2022 | 5601 | 5 |
| 4982 | 02/21/2022 | 9904 | 13 |
| 3217 | 02/28/2022 | 5601 | 8 |
| 4792 | 02/04/2022 | 5601 | 14 |
| 2098 | 03/12/2022 | 9904 | 11 |
Example Output:
| month | product_id | avg_units_sold |
|---|---|---|
| 1 | 5601 | 10 |
| 1 | 9904 | 9 |
| 2 | 5601 | 11 |
| 2 | 9904 | 13 |
| 3 | 9904 | 11 |
Answer:
This query extracts the month from the field using the function, then groups by both and to compute the average number of units sold for each product per month.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for product sales analysis or this Amazon Average Review Ratings Question which is similar for average calculations by product.
SQL Question 9: Analyzing Customer and Purchase Data
You are given two tables. The first table, , contains information about the customers like , , , , and . The second table, , includes , ,, and for each purchase made by a customer.
Generate a report that shows the purchase details for each customer including their personal details and total purchase amount.
Example Input:
| customer_id | first_name | last_name | date_joined | |
|---|---|---|---|---|
| 1 | John | Doe | johndoe@gmail.com | 01/01/2021 |
| 2 | Jane | Smith | janesmith@gmail.com | 02/05/2021 |
| 3 | Michael | Johnson | michaeljohnson@gmail.com | 03/08/2021 |
| 4 | Emily | Campbell | emilycampbell@gmail.com | 04/11/2021 |
Example Input:
| purchase_id | customer_id | item_id | purchase_date | amount |
|---|---|---|---|---|
| 100 | 1 | 50001 | 06/01/2022 | 200.00 |
| 101 | 2 | 69852 | 06/02/2022 | 150.00 |
| 102 | 3 | 50001 | 06/03/2022 | 100.00 |
| 103 | 4 | 69852 | 06/04/2022 | 250.00 |
Answer:
The following SQL query does the job:
This query joins the table and the table on . It returns the customer personal details along with purchase details. The results are ordered by to group the purchase details of each customer together.
Since join questions come up so often during SQL interviews, take a stab at this Snapchat Join SQL question:
Preparing For The PC Connection SQL Interview
The key to acing a PC Connection SQL interview is to practice, practice, and then practice some more! In addition to solving the above PC Connection SQL interview questions, you should also solve the 200+ DataLemur interview questions which come from companies like Netflix, Airbnb, and Amazon.
Each DataLemur SQL question has hints to guide you, full answers and best of all, there is an online SQL code editor so you can right in the browser run your SQL query and have it executed.
To prep for the PC Connection SQL interview you can also be wise to practice SQL problems from other industrial and electrical distribution companies like:
- Applied SQL questions
- MSC Industrial Direct SQL questions
- Fastenal SQL questions
- Veritiv SQL questions
However, if your SQL skills are weak, forget about jumping right into solving questions – strengthen your SQL foundations with this free SQL tutorial.
This tutorial covers topics including handling strings and RANK() window functions – both of these pop up routinely in PC Connection interviews.
PC Connection Data Science Interview Tips
What Do PC Connection Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories tested in the PC Connection Data Science Interview include:
- AB Testing Questions
- Python or R Coding Questions
- Product Metrics Interview Questions
- ML Interview Questions
- Behavioral & Resume-Based Questions
How To Prepare for PC Connection Data Science Interviews?
To prepare for the PC Connection Data Science interview make sure you have a firm understanding of the company's cultural values – 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 tech companies like Netflix, Google, & Airbnb
- A Crash Course on SQL, Product-Sense & ML
- Amazing Reviews (1000+ 5-star reviews on Amazon)