9 Delta Electronics SQL Interview Questions (Updated 2024)
At Delta Electronics, SQL is used day-to-day for analyzing production efficiency and predicting component failure based on historical data. That's why Delta Electronics almost always asks SQL questions during interviews for Data Science, Data Engineering and Data Analytics jobs.
So, to help you prepare for the Delta Electronics SQL interview, this blog covers 9 Delta Electronics SQL interview questions – can you solve them?
9 Delta Electronics SQL Interview Questions
SQL Question 1: Identify Top Customers for Delta Electronics.
For Delta Electronics, their most important users might be defined as those who frequently purchase high-value products. For this exercise, let's look for customers who have made purchases totaling $10,000 or more in a given month. In addition, let's understand what are their most frequently purchased products in that month.
We can construct two sample tables, and :
Example Input:
Example Input:
| purchase_id | customer_id | product_id | purchase_date | purchase_amount |
|---|---|---|---|---|
| 1 | 1 | 101 | 01/07/2022 00:00:00 | 5000.00 |
| 2 | 1 | 102 | 01/07/2022 00:00:00 | 3000.00 |
| 3 | 2 | 101 | 01/07/2022 00:00:00 | 4000.00 |
| 4 | 2 | 103 | 01/07/2022 00:00:00 | 2000.00 |
| 5 | 1 | 102 | 02/07/2022 00:00:00 | 5000.00 |
| 6 | 3 | 104 | 02/07/2022 00:00:00 | 1000.00 |
| 7 | 4 | 105 | 02/07/2022 00:00:00 | 2000.00 |
| 8 | 1 | 101 | 08/07/2022 00:00:00 | 5000.00 |
Answer:
We will achieve this by first aggregating purchases for each customer for each month and then filter out customers who made purchases totalling $10,000 or more. Then join these results back to the purchases to find their most frequently purchased product.
With this result, we can now easily identify our VIP customers, see how much they are spending, as well as the product ID they most frequently buy.
To solve a super-customer analysis question on DataLemur's free online SQL coding environment, try this Microsoft Azure Cloud SQL Interview Question:
SQL Question 2: Compute the monthly sales and rank the product based on sales
Delta Electronics would like to know their monthly sales for each product. They also want to rank their products based on these sales within each month. Assume we have a table named "sales", which consists of the order_id, user_id, product_id, sales_date and sold_units columns.
Example Input:
| order_id | user_id | sales_date | product_id | sold_units |
|---|---|---|---|---|
| 5012 | 738 | 06/02/2022 | 50001 | 3 |
| 1035 | 243 | 06/12/2022 | 69852 | 1 |
| 7254 | 122 | 06/18/2022 | 50001 | 4 |
| 9753 | 789 | 07/20/2022 | 69852 | 2 |
| 8963 | 901 | 07/24/2022 | 50001 | 2 |
Write a SQL query that computes the total sold units for each product per month and assigns a rank to each product within each month based on the sold units.
The sample output table "monthly_sales_rank":
Example Output:
| month | product_id | total_sold | rank |
|---|---|---|---|
| 6 | 50001 | 7 | 1 |
| 6 | 69852 | 1 | 2 |
| 7 | 50001 | 2 | 2 |
| 7 | 69852 | 2 | 1 |
Answer:
Here is a postgreSQL query to solve this SQL problem.
The query starts by truncating the date to the month using the function. Then, for each truncated date (month), the query gets the number of sold units for each product using the function and . Finally, the window function is used to rank the products based on the total sold units for each month. The in the function is set to the truncated month to ensure that the ranking is done within each month.
Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur
SQL Question 3: What are the differences between an inner and a full outer join?
A full outer join returns all rows from both tables, including any unmatched rows, whereas an inner join only returns rows that match the join condition between the two tables.
For a tangible example, suppose you had a table of Delta Electronics orders and Delta Electronics customers.
Here's a SQL inner join using the orders and customers tables:
This query will return rows from the orders and customers tables that have matching values. Only rows with matching values will be included in the results.
Here is an example of a using the orders and customers tables:
This query will return all rows from both the orders and customers tables, including any rows that do not have matching values. Any rows with null values for either table will be included in the results.
SQL Question 4: Average sales per product
For Delta Electronics, a manufacturer of various electronic devices, an important performance metric they consider is the average sales of each of their products. They want to see which products are sold more on average per month, which may give insights about their popularity, effectiveness, and quality.
Suppose they have a 'sales' table recording every sale that happens. Writing a SQL query, can you find the average number of sales per month for each product?
Example Input:
| sale_id | product_id | sale_date | units_sold |
|---|---|---|---|
| 101 | P1001 | 2022/01/04 | 20 |
| 102 | P1002 | 2022/01/08 | 10 |
| 103 | P1001 | 2022/02/14 | 15 |
| 104 | P1002 | 2022/02/18 | 5 |
| 105 | P1001 | 2022/03/12 | 25 |
Example Output:
| month | product_id | avg_sales |
|---|---|---|
| 1 | P1001 | 20.00 |
| 1 | P1002 | 10.00 |
| 2 | P1001 | 15.00 |
| 2 | P1002 | 5.00 |
| 3 | P1001 | 25.00 |
Answer:
This solution works by grouping the sales data by month and product_id and then calculating the average in each group. The function is used to get the month from the column. The results are sorted by and to make the output well-organized and easy to interpret.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating sales for specific products or this Wayfair Y-on-Y Growth Rate Question which is similar for computing the average sales over a time period.
SQL Question 5: What does adding 'DISTINCT' to a SQL query 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 Delta Electronics 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 Delta Electronics:
| job_title |
|---|
| Data Analyst |
| Data Scientist |
| Data Engineer |
SQL Question 6: Calculate the Total Sales For Each Product Category
As an analyst at Delta Electronics, your job is to assist in tracking the company's sales performance. Given a table of sales data, write a SQL query to find out the total sales for each product category on a yearly basis.
Please use the following sample data to solve the problem:
Example Input:
| sales_id | product_id | product_category | transaction_date | sales_amount |
|---|---|---|---|---|
| 1023 | 4001 | Computers | 01-Jan-2020 | 200.00 |
| 1024 | 4002 | Computers | 02-Feb-2020 | 250.00 |
| 1025 | 5001 | Electronics | 15-Mar-2020 | 150.00 |
| 1026 | 5002 | Electronics | 25-Apr-2020 | 300.00 |
| 1027 | 6001 | Appliances | 20-May-2020 | 450.00 |
We need to calculate the total sales for each category over the year 2020.
Answer:
This SQL statement groups the sales data by product category and sales year, and then calculates the total sales for each group. The result is ordered in descending order by total sales. It uses the built-in PostgreSQL function EXTRACT to get the year part of the transaction_date, and it sums the column to get the total sales.
Example Output:
| product_category | sales_year | total_sales |
|---|---|---|
| Computers | 2020 | 450.00 |
| Electronics | 2020 | 450.00 |
| Appliances | 2020 | 450.00 |
This table shows the total sales for each product category in 2020.
SQL Question 7: What do primary keys do?
The primary key of a table is a column or combination of columns that serves to uniquely identify each row in the table. To define a primary key in a SQL database, you can use the constraint.
For instance, consider a table of :
In this example, the column is the primary key of the Delta Electronics employees table.
Primary keys are important in databases for several reasons:
- Uniqueness: A primary key is used to uniquely identify each row in a table. This means that no two rows in the table can have the same primary key value. This is important because it helps to ensure the accuracy and integrity of the data in the table.
- Non-nullability: A primary key is typically defined as a non-null column, which means that it cannot contain a null value. This helps to ensure that every row in the table has a unique identifier.
- Relationship-building: Primary keys are often used to establish relationships between tables in a database. For example, you might use a primary key to link the table to the table.
SQL Question 8: Calculate Weighted Ratings
Delta Electronics, a leading global provider of power and thermal management solutions, wants to calculate a weighted rating for its products based on reviews. The aim is to give more weightage to recent reviews than older ones.
For this, they have decided to use the following formula to calculate the weighted rating:
The is the difference in days from the 'submit_date' of each review and the current date. The is the average 'review_age_in_days' of all reviews.
Create a query to calculate the for each product.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-06-08 | 50001 | 4 |
| 7802 | 265 | 2022-06-10 | 69852 | 4 |
| 5293 | 362 | 2022-06-18 | 50001 | 3 |
| 6352 | 192 | 2022-07-26 | 69852 | 3 |
| 4517 | 981 | 2022-07-05 | 69852 | 2 |
Expected Output:
| product_id | weighted_rating |
|---|---|
| 50001 | 7.00 |
| 69852 | 16.64 |
Answer:
<WRITEUP_OF_ANSWER>: This query works by first calculating the for each review and then using this information to find the for all reviews. This average is then used in the calculation of . The function is used to ensure that the weightage of the review is positive. The function is used to round off the number of stars given. The function is used to sum up the calculated weighted ratings for each of the products. Finally, the results are grouped by product_id.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for working with review data or this Twitter Tweets' Rolling Averages Question which is similar for using a window function and time-series data.
SQL Question 9: Analyze Monthly Sales of Delta Electronics Products
Delta Electronics, as a leading provider of power and thermal management solutions, sells a wide variety of electronic products. It wants to understand the monthly sales for each product in the last year to better plan for inventory and production.
Write a SQL query to find the total amount of sales for each product for each month in the last year. Assume that today's date is '2022-12-01'.
Use the schema provided below for your query.
Example Input:
| sale_id | product_id | quantity | price_per_unit | sale_date |
|---|---|---|---|---|
| 5001 | 1001 | 20 | 50 | 2022-06-15 |
| 5002 | 1002 | 10 | 100 | 2022-06-20 |
| 5003 | 1001 | 15 | 50 | 2022-07-18 |
| 5004 | 1002 | 30 | 100 | 2022-07-25 |
| 5005 | 1002 | 5 | 100 | 2022-08-01 |
Example Output:
| month | product_id | total_sales |
|---|---|---|
| 6 | 1001 | 1000 |
| 6 | 1002 | 1000 |
| 7 | 1001 | 750 |
| 7 | 1002 | 3000 |
| 8 | 1002 | 500 |
Answer:
This query works by first selecting the 's month and from the table, where is between '2021-12-01' and '2022-12-01'. It then calculates the total sales for each product in each month by multiplying the with and sums them up. The result is grouped by the month and , then ordered by the same.
How To Prepare for the Delta Electronics SQL Interview
The best way to prepare for a Delta Electronics SQL interview is to practice, practice, practice.
In addition to solving the above Delta Electronics SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like FAANG tech companies and tech startups.
Each problem on DataLemur has multiple hints, full answers and best of all, there's an online SQL code editor so you can right in the browser run your SQL query answer and have it graded.
To prep for the Delta Electronics SQL interview you can also be helpful to solve SQL questions from other industrial-tech companies like:
In case your SQL skills are weak, don't worry about going right into solving questions – refresh your SQL knowledge with this free SQL tutorial.
This tutorial covers SQL topics like CTEs and handling timestamps – both of which show up often during SQL interviews at Delta Electronics.
Delta Electronics Data Science Interview Tips
What Do Delta Electronics Data Science Interviews Cover?
Beyond writing SQL queries, the other topics to prepare for the Delta Electronics Data Science Interview are:
- Probability & Statistics Questions
- Python Pandas or R Coding Questions
- Analytics and Product-Metrics Questions
- ML Interview Questions
- Behavioral Interview Questions
How To Prepare for Delta Electronics Data Science Interviews?
The best way to prepare for Delta Electronics Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from Facebook, Google & startups
- A Crash Course on SQL, Product-Sense & ML
- Amazing Reviews (900+ 5-star reviews on Amazon)