10 Dell SQL Interview Questions (Updated 2024)
At Dell, SQL is used day-to-day for analyzing customer behaviors and troubleshooting database issues for efficient data management in the tech manufacturing and service industry. Unsurprisingly this is why Dell asks SQL query questions during interviews for Data Science, Data Engineering and Data Analytics jobs.
As such, to help you ace the Dell SQL interview, we've collected 10 Dell SQL interview questions – able to answer them all?
10 Dell SQL Interview Questions
SQL Question 1: Identifying Top Purchasing Customers
Dell needs to identify the top customers who have spent the most on their products over the past year. This analysis will help the company to identify its "power users," and potentially provide these customers with special offers, or focus on their needs and feedback to drive future product development.
Assume the company has two tables:
- table that contains transactional order data such as order ID, user ID, product ID, and the order' date
- table that contains product-related data such as product ID, product name, and product price.
Example Input:
| order_id | user_id | order_date | product_id |
|---|---|---|---|
| 2001 | 456 | 2021-04-09 | 106 |
| 2002 | 789 | 2021-05-10 | 105 |
| 2003 | 456 | 2021-06-15 | 107 |
| 2004 | 123 | 2021-07-20 | 105 |
| 2005 | 789 | 2021-08-25 | 106 |
Example Input:
| product_id | product_name | price_usd |
|---|---|---|
| 105 | Inspiron Laptop | 500 |
| 106 | Alienware Gaming Desktop | 2000 |
| 107 | Dell Monitor | 200 |
Your task is to write a SQL query to find the top 5 users who have spent the most money on Dell products over the past year.
Answer:
In this query, we're joining the table with the table on the column, which is common between the two tables. This enables us to fetch the price of the products ordered by each user. We're then grouping the results by the and summing the price to calculate the total amount spent by each user. Using the clause, we order the users in descending order based on the total amount they've spent, and select the top 5 using .
To practice a similar customer analytics SQL question where you can code right in the browser and have your SQL query automatically checked, try this Walmart SQL Interview Question:
SQL Question 2: Average Rating Per Month for Each Product
As a data analyst at Dell, you are tasked to analyze the customer reviews on each specific product. Using the table, write a SQL query to calculate the average rating ("stars") that each product received per month.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2020-06-08 | 50001 | 4 |
| 7802 | 265 | 2020-06-10 | 69852 | 4 |
| 5293 | 362 | 2020-06-18 | 50001 | 3 |
| 6352 | 192 | 2020-07-26 | 69852 | 3 |
| 4517 | 981 | 2020-07-05 | 69852 | 2 |
Example Output:
| month | product_id | avg_stars |
|---|---|---|
| 6 | 50001 | 3.50 |
| 6 | 69852 | 4.00 |
| 7 | 69852 | 2.50 |
Answer:
This query first extracts the month from the column using the function, and then groups the results by product_id and month using . The function is used to calculate the average rating for each group.
The clause ensures the output is sorted in ascending order first by product_id and then by month. Since product_id and month are both used in the clause, it's guaranteed every row in the output will represent a unique combination of product and month.
For more window function practice, try this Uber SQL problem within DataLemur's interactive SQL code editor:
SQL Question 3: What is database normalization?
To normalize a database, tables are divided into smaller, more specialized ones and relationships between them are defined via primary and foreign keys. This minimizes redundancy, making the database more flexible, scalable, and easier to maintain. Normalization also helps to ensure the accuracy of the data by reducing the likelihood of inconsistencies and errors.
SQL Question 4: Designing Database for Sales Management at Dell
Suppose you are asked to design a database for Dell to keep track of their sales of different products in different regions. Tables to be designed include:
- Products: Stores information about each product including product ID, name, price, and release date.
- Regions: Contains information about the different sales regions including region ID and name.
- Sales: Stores the sales record which includes information such as sales ID, product sold, region where the product was sold, sale date, and the number of units sold.
After designing the tables, now let's assume you are asked to find out the total sales (in terms of the number of units) for each product in each region.
Provide the data in the following format:
Sample Data
| product_id | name | price | release_date |
|---|---|---|---|
| 1 | Laptop A | 1200 | 2020-01-01 |
| 2 | Laptop B | 1500 | 2020-07-01 |
| 3 | Desktop A | 1700 | 2021-02-01 |
Sample Data
| region_id | name |
|---|---|
| 1 | North America |
| 2 | Europe |
| 3 | Asia-Pacific |
Sample Data
| sales_id | product_id | region_id | sale_date | units_sold |
|---|---|---|---|---|
| 1 | 1 | 1 | 2021-02-01 | 3 |
| 2 | 2 | 2 | 2021-03-01 | 5 |
| 3 | 3 | 3 | 2021-04-01 | 2 |
| 4 | 1 | 2 | 2021-05-01 | 4 |
| 5 | 2 | 3 | 2021-06-01 | 1 |
Answer
This query will provide the total number of units sold for each product in each region by joining the , , and tables. It groups the result by product and region names and orders the result by the same.
SQL Question 5: What does do?
The COALESCE() function returns the first non-NULL value from a list of values. This function is often used to replace a NULL with some default value, so that you can then take a or of some column without NULLs messing things up.
For example, suppose you ran a customer satisfaction survey for Dell and had statements like "I'd buy from Dell again". In the survey, customers would then answer how strongly they agreed with a statement on a scale of 1 to 5 (strongly disagree, disagree, neutral, agreee, strongly agree).
Because attention spans are short, many customers skipped many of the questions, and thus our survey data might be filled with NULLs:
| customer_id | question_id | agree_scale |
|---|---|---|
| 101 | 1 | 4 |
| 101 | 2 | 5 |
| 202 | 1 | 4 |
| 202 | 2 | NULL |
| 303 | 1 | 5 |
| 303 | 2 | NULL |
Before doing further analytics on this customer survey data, you could replace the NULLs in the column with the value of (because that corresponds to the default 'neutral' answer) using the function:
This would result in the following:
| customer_id | question_id | agree_scale |
|---|---|---|
| 101 | 1 | 4 |
| 101 | 2 | 5 |
| 202 | 1 | 4 |
| 202 | 2 | 3 |
| 303 | 1 | 5 |
| 303 | 2 | 3 |
SQL Question 6: Filter Dell Customers Based On Their Purchase and Support Experiences
As a data analyst at Dell, you are tasked with identifying customers whom Dell can target for their new product promotion. The target customers are those who have purchased laptops in the last year, rated their purchase experience 4 or higher (5 is the highest), and have not had any major tech support issues in the last six months.
You have been given two tables - and . The table records every laptop purchase with the purchase date and the customer's rating of the purchase experience. The table records every time a customer has contacted tech support, with the date and severity of the issue (on a scale of 1 to 5, with 1 being minor and 5 being a major issue).
The structure of the and tables is as follows:
Example Input:
| purchase_id | customer_id | purchase_date | product_id | rating |
|---|---|---|---|---|
| 1001 | 123 | 02/15/2022 | D50001 | 5 |
| 1002 | 456 | 05/20/2022 | D60052 | 3 |
| 1003 | 789 | 03/30/2022 | D70051 | 4 |
| 1004 | 123 | 06/18/2022 | D80050 | 4 |
| 1005 | 789 | 07/15/2022 | D90052 | 4 |
Example Input:
| support_id | customer_id | support_date | issue_level |
|---|---|---|---|
| 2001 | 123 | 05/18/2022 | 3 |
| 2002 | 456 | 06/21/2022 | 5 |
| 2003 | 789 | 02/20/2022 | 2 |
| 2004 | 123 | 03/25/2022 | 1 |
| 2005 | 789 | 07/16/2022 | 4 |
Answer:
For this question, you would approach it by first, selecting the customers in the table who made a purchase in the last year (from a provided snap-shot-date) and rated their experience 4 or higher. Next, filter out customers who had a tech support issue of 4 or higher in the last six months. Your query would look something like this:
In the resulting list, each represents a customer who can be targeted for the new product promotion.
SQL Question 7: What does the SQL command do?
If you have two tables and want to retrieve only the rows that are present in both tables, just use the operator!
For example, let's use to find all of Dell's Facebook video ads that are also being run on YouTube:
SQL Question 8: Calculate Average Sales of Dell Laptops per Month
You are working as a Data Analyst at Dell. Your manager wants to have a clear understanding of the sales performance of different laptop models on a monthly basis. Specifically, he wants to know the average number of units sold each month for each laptop model.
Could you calculate the average units sold per month for each laptop model using SQL?
Here is the structure of the sales table:
With the following sample data:
Example Input:
| id | sale_date | laptop_model | units_sold |
|---|---|---|---|
| 1 | 01/05/2022 | Dell Inspiron | 100 |
| 2 | 01/05/2022 | Dell XPS | 150 |
| 3 | 02/05/2022 | Dell Inspiron | 120 |
| 4 | 02/05/2022 | Dell XPS | 140 |
| 5 | 03/05/2022 | Dell Inspiron | 110 |
| 6 | 03/05/2022 | Dell XPS | 160 |
Answer:
Here is a PostgreSQL solution for the given problem:
In this SQL query, we group all records by the month of their and , then calculate the average number of in each group. The function truncates the timestamp to the beginning of the month, but keeps it in DATE format so we can use it for grouping. We order the output by and to make it easier to comprehend. This query gives us the average number of units sold for each laptop model per month.
The two most similar questions are "Y-on-Y Growth Rate" and "Average Review Ratings" as both require monthly sales/aggregated data calculation:
-
"Y-on-Y Growth Rate" from Wayfair focuses on sales data broken down by time periods, similar to your task.
-
"Average Review Ratings" from Amazon also involves grouping by month and calculating an average metric.
To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for analyzing sales over monthly periods or this Amazon Average Review Ratings Question which is similar for monthly average calculation.
SQL Question 9: Calculating Click-Through-Rate (CTR) for Dell digital Ad Campaigns
Dell Inc is conducting an Ad campaign across multiple platforms. The goal of the campaign is to increase the purchase of their new Dell XPS laptop. The data science team at Dell has collected some data about the number of times an Ad was seen (impressions) and how many times it was clicked (clicks). The higher the CTR the better the Ad Campaign performed.
Your task as a Data Analyst is to calculate the Click-Through-Rate (CTR) which is the number of ad clicks divided by the number of ad impressions. Write a SQL query to calculate the CTR for each ad campaign. Assume we have a table with the following structure:
Example input:
| campaign_id | impressions | clicks |
|---|---|---|
| 101 | 1200 | 15 |
| 102 | 1500 | 30 |
| 103 | 1100 | 20 |
| 104 | 1300 | 40 |
| 105 | 1000 | 50 |
Answer:
Here is a PostgreSQL query to solve the problem:
This query calculates the CTR for each ad campaign by dividing the number of clicks by the number of impressions for each campaign. The is used to caste the integer values to decimal, ensuring an accurate division result. The result is then rounded to 2 decimal places for easier reading. The clause is used to order the results by the campaign_id.
To solve another question about calculating rates, solve this TikTok SQL question on DataLemur's online SQL coding environment:
SQL Question 10: DBMS transactions are expected to follow the ACID properties. What are they, and what does each property mean?
A transaction is a one or more SQL commands which are executed as a singular unit if the transaction -commits- (or no execution hapens if the transaction -aborts-).
For transactions, a DBMS is supposed to enforce the follwing ACID properties: Atomicity, Consistency, Isolation, & Durability.
Here's what each one means:
- Atomicity: the transaction is completed in an all-or-nothing way (no partial commits)
- Consistency: the transaction is valid and follows all constraints and restrictions
- Isolation: the transaction doesn't affect another transaction
- Durability: the committed transactions is stored permanently in the DB (it doesn't dissapear!)
As you can see, it's pretty important for the multiple databases where Dell store's it's data to be ACID-compliant!
Preparing For The Dell SQL Interview
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews.
In addition to solving the earlier Dell SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like FAANG and tech startups.
Each SQL question has hints to guide you, step-by-step solutions and crucially, there is an interactive SQL code editor so you can easily right in the browser your SQL query answer and have it executed.
To prep for the Dell SQL interview you can also be wise to practice SQL questions from other tech companies like:
However, if your SQL foundations are weak, forget about diving straight into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Scientists & Analysts.
This tutorial covers SQL concepts such as advantages of CTEs vs. subqueries and joining a table to itself – both of these pop up routinely during SQL interviews at Dell.
Dell Data Science Interview Tips
What Do Dell Data Science Interviews Cover?
In addition to SQL interview questions, the other question categories covered in the Dell Data Science Interview are:
- Probability & Stats Questions
- Python Pandas or R Coding Questions
- Product Metrics Interview Questions
- ML Modelling Questions
- Resume-Based Behavioral Questions
How To Prepare for Dell Data Science Interviews?
The best way to prepare for Dell Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG (FB, Apple, Amazon, Netflix, Google)
- A Refresher on Stats, ML, & Data Case Studies
- Great Reviews (900+ reviews, 4.5-star rating)