10 Arrow Electronics SQL Interview Questions (Updated 2024)
Data Analytics, Data Science, and Data Engineering employees at Arrow Electronics write SQL queries to analyze sales data, pinpointing specific market trends that help them understand which products are gaining popularity in different regions. It is also used to extract detailed customer data to create personalized marketing campaigns that align with individual preferences and behaviors, this is the reason why Arrow Electronics asks jobseekers SQL interview problems.
So, to help you prepare, we've collected 10 Arrow Electronics SQL interview questions – can you answer each one?
10 Arrow Electronics SQL Interview Questions
SQL Question 1: Calculate the running total of sales for each product, per month
Arrow Electronics, being a large electronics distributor, holds abundant data regarding its product sales. An important analysis that the company may require is to track the running total of sales for each product on a monthly basis.
Let's use the table for this exercise. For context, every time a product is sold, a new row is created in this table containing the , , , and .
Using this, the question is, "Can you write a SQL query to compute the running total of sales for each product, per month, in 2022?"
Example Input:
| sale_id | product_id | sale_date | sale_amount |
|---|---|---|---|
| 1101 | 108 | 2022/01/05 00:00:00 | 150 |
| 2102 | 105 | 2022/01/10 00:00:00 | 100 |
| 3107 | 108 | 2022/01/15 00:00:00 | 200 |
| 4125 | 109 | 2022/02/01 00:00:00 | 75 |
| 5135 | 105 | 2022/02/05 00:00:00 | 120 |
| 6162 | 109 | 2022/02/15 00:00:00 | 80 |
Example Output:
| mth | product_id | running_total_sales |
|---|---|---|
| 1 | 108 | 350 |
| 1 | 105 | 100 |
| 2 | 108 | 350 |
| 2 | 109 | 75 |
| 2 | 105 | 220 |
| 2 | 109 | 155 |
Answer:
The query above uses a window function to calculate the running total of sales for each product per month. It utilizes the function with clause which calculates the sum of for each according to the ordered . The partition is reset when it encounters a new product id. The function is used to isolate the month and year from . Finally, the result is ordered by month and product id respectively.
p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur
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SQL Question 2: 2nd Highest Salary
Given a table of Arrow Electronics employee salaries, write a SQL query to find the 2nd highest salary at the company.
Arrow Electronics Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
Try this interview question directly within the browser on DataLemur:
Answer:
You can find a detailed solution here: 2nd Highest Salary.
SQL Question 3: Can you explain what SQL constraints are, and why they are useful?
Constraints are just rules for your DBMS to follow when updating/inserting/deleting data.
Say you had a table of Arrow Electronics employees, and their salaries, job titles, and performance review data. Here's some examples of SQL constraints you could implement:
NOT NULL: This constraint could be used to ensure that certain columns in the employee table, such as the employee's first and last name, cannot contain NULL values.
UNIQUE: This constraint could be used to ensure that the employee ID is unique. This would prevent duplicate entries in the employee table.
PRIMARY KEY: This constraint could be used to combine the and constraints to create a primary key for the employee table. The employee ID could serve as the primary key.
FOREIGN KEY: This constraint could be used to establish relationships between the employee table and other tables in the database. For example, you could use a foreign key to link the employee ID to the department ID in a department table to track which department each employee belongs to.
CHECK: This constraint could be used to ensure that certain data meets specific conditions. For example, you could use a constraint to ensure that salary values are always positive numbers.
DEFAULT: This constraint could be used to specify default values for certain columns. For example, you could use a constraint to set the employee hire date to the current date if no value is provided when a new employee is added to the database.
SQL Question 4: Sales Tracking in Arrow Electronics
Arrow Electronics, being a global provider of products, services, and solutions to users, has a vast database that records the transactions of its business. For effective business decision making, management would like to be able to analyze their sales data. Can you help design a database system that allows them to track their clients' orders by location and category?
The table has columns for , , .
Example Input:
| client_id | name | location |
|---|---|---|
| 1001 | Company A | New York |
| 1002 | Company B | Los Angeles |
| 1003 | Company C | Chicago |
The table has columns for , , .
Example Input:
| product_id | name | category |
|---|---|---|
| 2001 | Server | Hardware |
| 2002 | Workstation | Hardware |
| 2003 | Antivirus software | Software |
The table has columns for , , , , and .
Example Input:
| sale_id | client_id | product_id | sale_date | sale_amount |
|---|---|---|---|---|
| 3001 | 1001 | 2001 | 06/01/2022 | $2000 |
| 3002 | 1002 | 2002 | 06/10/2022 | $1500 |
| 3003 | 1002 | 2003 | 06/10/2022 | $300 |
Based on the design, answer the following question:
Find the total amount of sales per location and category for the month of June 2022.
Answer:
The query uses inner joins to link the table with the and tables based on their keys. We use the function to calculate the total sales amount and the statement to group the result by location and category. The clause is used to filter the results for the month of June 2022.
SQL Question 5: What does the clause do vs. the clause?
Before we address vs. question, let's address the clause which is used in a statement to group rows into a set of summary rows. It's typically used in conjunction with aggregate functions such as:
- `MIN
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:
This query retrieves the total salary for each department and groups the rows by department. The clause then filters the groups to include only Arrow Electronics departments where the total salary is greater than $1 million
Note that the clause must be used after the clause and can only reference columns listed in the clause or aggregated columns selected by the statement.
SQL Question 6: Filter Customer Orders
Given a customers and orders database in Arrow Electronics, write a query to filter customers who have placed at least one order in the year 2022 and are from the United States. Also, if they have placed orders for products with a unit price greater than $500.
Table:
| customer_id | first_name | last_name | country |
|---|---|---|---|
| 1 | John | Doe | United States |
| 2 | Jane | Doe | Canada |
| 3 | Bill | Smith | United States |
| 4 | Mary | Johnson | United Kingdom |
Table:
| order_id | customer_id | product_id | quantity | unit_price | order_date |
|---|---|---|---|---|---|
| 1 | 1 | 1001 | 2 | 450.00 | 2021-01-20 |
| 2 | 2 | 1002 | 1 | 600.00 | 2022-02-15 |
| 3 | 1 | 1003 | 1 | 750.00 | 2022-03-10 |
| 4 | 3 | 1004 | 1 | 2000.00 | 2022-04-05 |
| 5 | 4 | 1005 | 1 | 100.00 | 2021-05-01 |
Answer:
The above SQL query uses a operator to combine and tables and selects customers who made a purchase in 2022 from the United States. The clause filters out customers based on the country, the year of the order, and the unit price being greater than $500.
SQL Question 7: What are the similarities and difference between relational and NoSQL databases?
While both types of databases are used to store data (obviously), there's some key differences in how they store and organize data.
Relational databases try to represent the world into neat little tables, with rows and columns. Non-relational (NoSQL) databases use a variety of data models to represent data, including document, key-value, columnar, and graph storage formats.
While the exact types of NoSQL databases is beyond the scope of a Data Analyst and Data Scientist SQL interview at Arrow Electronics, it's good to know that companies generally choose to use NoSQL databases:
- when dealing with unstructured or semi-structured data
- when the database needs to be scaled horizontally easily
- when the data is non-relational (like storing social network data which makes more sense in a graph format)
SQL Question 8: Analyzing Click-Through Rates for Arrow Electronics
Arrow Electronics is a large company involved in the marketing and selling of various electronic components. One of their key metrics is analyzing the click-through rates (CTR) of their digital ads to better understand user interactions and conversion rates.
For this task, assume they want to calculate the CTR for their electronics products per month based on clicks and views recorded in their system. CTR is calculated by dividing the total number of clicks by the total number of views and then multiplying by 100 to get a percentage.
To solve this query, we will use two tables namely and . The table includes , , and fields while the table includes , , and .
Example Input:
| view_id | user_id | view_date | product_id |
|---|---|---|---|
| 101 | 456 | 2022-06-08 | 70101 |
| 102 | 789 | 2022-06-10 | 70102 |
| 103 | 321 | 2022-07-20 | 70101 |
| 104 | 654 | 2022-07-26 | 70102 |
| 105 | 987 | 2022-06-05 | 70101 |
Example Input:
| click_id | user_id | click_date | product_id |
|---|---|---|---|
| 201 | 456 | 2022-06-08 | 70101 |
| 202 | 789 | 2022-06-10 | 70102 |
| 203 | 654 | 2022-07-26 | 70102 |
| 204 | 321 | 2022-08-01 | 70101 |
| 205 | 456 | 2022-06-10 | 70101 |
Answer:
This query first joins the and tables based on and . It then groups the results by month (extracted from ) and . The click-through rate is then calculated by counting the unique s, dividing by the count of unique s, and multiplying it by 100 to turn it into a percentage.
To solve a similar problem on DataLemur's free online SQL coding environment, solve this Meta SQL interview question:
SQL Question 9: Average Component Price
Arrow Electronics has a vast inventory of different electronic components. The product team wants to know the average price of all the components grouped by category. Can you help them write this SQL query?
Here are some example data:
Example Input:
| component_id | category | price |
|---|---|---|
| 1 | Memory | 35.50 |
| 2 | CPU | 125.75 |
| 3 | CPU | 115.25 |
| 4 | Memory | 45.00 |
| 5 | Motherboard | 95.50 |
Note: The table has as the primary key, as the type of the component like Memory, CPU, Motherboard, etc., and the representing the price of the component.
The output would be the average price of every category.
Example Output:
| category | avg_price |
|---|---|
| Memory | 40.25 |
| CPU | 120.5 |
| Motherboard | 95.5 |
Answer:
In PostgreSQL, you can use the function to calculate the average price for each category. The clause will segregate the data accordingly.
With the above query, we first group all the components by their category and then calculate the average price for each group. The result set will include each distinct category along with its average price. This will provide the product team with the data they requested, and they can use it to analyze the pricing structure of their inventory.
SQL Question 10: What do stored procedures do, and when would you use one?
Stored procedures are like functions in Python – they can accept input params and return values, and are used to encapsulate complex logic.
For example, if you worked as a Data Analyst in support of the Marketing Analytics team at Arrow Electronics, a common task might be to find the conversion rate for your ads given a specific time-frame. Instead of having to write this query over-and-over again, you could write a stored procedure like the following:
To call this stored procedure, you'd execute the following query:
How To Prepare for the Arrow Electronics SQL Interview
The best way to prepare for a Arrow Electronics SQL interview is to practice, practice, practice. Beyond just solving the earlier Arrow Electronics SQL interview questions, you should also solve the 200+ DataLemur interview questions which come from companies like Google, Facebook, Microsoft and Amazon.
Each DataLemur SQL question has multiple hints, detailed solutions and best of all, there is an interactive coding environment so you can right online code up your query and have it graded.
To prep for the Arrow Electronics SQL interview you can also be a great idea to solve 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 foundations are weak, forget about going right into solving questions – refresh your SQL knowledge with this free SQL for Data Analytics course.
This tutorial covers things like RANK() window functions and Self-Joins – both of which show up often in Arrow Electronics SQL assessments.
Arrow Electronics Data Science Interview Tips
What Do Arrow Electronics Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories covered in the Arrow Electronics Data Science Interview include:
- AB Testing Questions
- Coding Questions in Python or R
- Business Sense and Product-Sense Questions
- Machine Learning Questions
- Resume-Based Behavioral Questions
How To Prepare for Arrow Electronics Data Science Interviews?
To prepare for the Arrow Electronics Data Science interview make sure you have a strong understanding of the company's values and mission – this will be key to acing the behavioral interview. For technical interviews prepare by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from Facebook, Google & startups
- A Refresher covering Stats, ML, & Data Case Studies
- Great Reviews (1000+ 5-star reviews on Amazon)