# 11 Western Digital SQL Interview Questions (Updated 2024)

Updated on

August 11, 2024

Western Digital employees use SQL for analyzing large datasets to improve storage solutions, such as optimizing data compression algorithms. It is also used for managing databases for device quality control analytics, including tracking failure rates and performance metrics, the reason why Western Digital asks SQL problems in interviews for Data Science and Data Engineering positions.

Thus, to help you prep, we've collected 11 Western Digital SQL interview questions – can you answer each one?

## 11 Western Digital SQL Interview Questions

### SQL Question 1: Identify the Top Spending Customers

In Western Digital, a leading storage solutions company, you are given access to a customer's database. They are interested in identifying their VIP customers i.e. customers who have spent the most on their products. For simplicity, assume that we're only considering customers' total amount spent on hard drives.

Assume you have the following tables:

##### Example Input:
customer_idfirst_namelast_nameemail
1001JohnDoejohndoe@example.com
1002JaneDoejanedoe@example.com
1003AliceSmithalicesmith@example.com
1004BobJohnsonbobjohnson@example.com
1005CharlieBrowncharliebrown@example.com
##### Example Input:
order_idcustomer_idorder_datetotal_amount
5001100106/22/2022 00:00:00250.00
5002100106/23/2022 00:00:00300.00
5003100206/24/2022 00:00:00200.00
5004100306/25/2022 00:00:00275.00
5005100406/26/2022 00:00:00325.00

Given the tables above, write a SQL query that returns the top 3 customers with the highest total amount spent on hard drives. The output should include the customer's name and total amount spent.

This statement joins the and tables on the field, calculates the total amount spent by each customer by aggregating from the table, and then orders the results in descending order of to get the top spenders. The LIMIT clause then restricts the output to the top 3 customers.

To practice a similar customer analytics SQL question where you can solve it right in the browser and have your SQL code automatically checked, try this Walmart SQL Interview Question:

### SQL Question 2: Employees Earning More Than Their Boss

Suppose there was a table of Western Digital employee salary data. Write a SQL query to find the employees who earn more than their own manager.

#### Western Digital Example Input:

employee_idnamesalarydepartment_idmanager_id
1Emma Thompson38001
2Daniel Rodriguez2230110
3Olivia Smith800018
4Noah Johnson680028
5Sophia Martinez1750110
8William Davis70002NULL
10James Anderson40001NULL

#### Example Output:

employee_idemployee_name
3Olivia Smith

This is the output because Olivia Smith earns \$8,000, surpassing her manager, William Davis who earns 7,800.

Test your SQL query for this question and run your code right in DataLemur's online SQL environment:

First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.

If the solution above is confusing, you can find a detailed solution with hints here: Employees Earning More Than Managers.

### SQL Question 3: What is the difference between a primary key and a foreign key?

To explain the difference between a primary key and foreign key, let's inspect employee data from Western Digital's HR database:

:

employee_idfirst_namelast_namemanager_id
1AubreyGraham3
2MarshalMathers3
3DwayneCarter4
4ShawnCarter

In this table, could be a primary key. It is unique for each row in the table and cannot contain null values.

could be a foreign key. It references the of the manager of each employee in the table, establishing a relationship between the employees and their managers. This foreign key allows you to easily query the table to find out who a specific employee's manager is, or to find out which employees report to a specific manager.

It is also possible for a table to have multiple foreign keys that reference different primary keys in other tables. For example, the table could have additional foreign keys for the of the department where each employee works, and the of the location where each employee is based.

### SQL Question 4: Compute Peak Monthly Sales of Each Product.

Western Digital, a leading data infrastructure company, manufactures a variety of products ranging from hard drives to data center systems. It is beneficial to understand which products peak in sales during which months to better plan marketing strategies and maintain the stock levels.

Write a SQL query to determine the peak monthly sales for each product. Use the table with the following schema:

• : An unique ID for each sale (integer).
• : The product ID associated with the sale (integer).
• : The quantity of the product sold (integer).
• : The date when the item was sold ( data type)

For this task, consider only the year and month of the (called ), and compute the total sales for a product in each month. For simplicity, consider the year 2022 only. Identify the months when each product reached its maximum sales.

##### Example Input:
sales_idproduct_idsales_datequantity
2301212022-02-11 10:24:3020
2301322022-02-15 14:11:3515
2301412022-02-30 18:54:4835
2301522022-03-15 12:00:0030
2301612022-03-22 12:50:5025
##### Example Output:
PRODUCTPEAK_MONTHYEARMAX_SALES_QUANTITY
12022-0255
22022-0330

In PostgreSQL:

This SQL block first calculates the monthly sales quantity () for each product. It then ranks these monthly quantities within each product group and extracts the information related to the maximum (peak) monthly sales (i.e., the month where rank is 1). The statement separates the rows into different groups based on the product_id and monthyear, and ranks the rows within each partition.

p.s. Window functions show up super often during SQL interviews, so practice the 27+ window function questions on DataLemur

### SQL Question 5: How do the and window functions differ from each other?

While both and are used to rank rows, the key difference is in how they deal with ties.

RANK(): When there's a tie, leaves a gap in the ranking. For example, if three rows are tied for 2nd place, the RANK() function will assign a rank of 2 to the first of these rows, a rank of 3 to the 2nd row in the tie, and a rank of 4 to the the 3rd tie.

DENSE_RANK(): For ties, does not leave a gap in the ranking. Instead, it assigns the same rank to all tied rows, and then makes the next row 1 bigger. Confusing, I know, but here's an example to make it more clear: if three rows are tied for 3rd place, the function will assign a rank of 3 to all three rows, and then assign a rank of 4 to the next row.

Suppose we had data on how many deals different salespeople at Western Digital closed, and wanted to rank the salespeople.

The result of this query would be:

namedeals_closedrankdense_rank
Akash5011
Brittany5021
Carlos4032
Dave4043
Eve3053
Frank2064

As you can see, the function assigns a rank of 1 to the first row (Akash), a rank of 2 to the second row (Brittany), and so on. In contrast, the , gives both Akash and Brittany a rank of 1, since they are tied, then moves on to rank 2 for Carlos.

### SQL Question 6: Filter Customer Records Based on Purchase History and Location

As a data analyst at Western Digital, you've been assigned the task of examining the company's customer database.

Your challenge is to write a SQL query that retrieves the record of customers from USA who have purchased any product within the 'External Drives' category at least thrice in the last year.

##### Example Input:
customer_idfirst_namelast_namecountry
1JohnDoeUSA
2JaneSmithUSA
3WilliamWangChina
4OliviaJohnsonUSA
5SophiaAndersonGermany
##### Example Input:
purchase_idcustomer_idproduct_idpurchase_date
111012021-09-26
211012021-05-30
311012021-02-16
421022021-06-26
521012022-01-16
631032021-12-16
##### Example Input:
product_idproduct_namecategory
101My PassportExternal Drives
102My CloudCloud Storage
103My PassportExternal Drives
104My CloudCloud Storage

This query first filters the customer table to include only customers from the USA. It then performs a subquery on the purchase and product tables, counting the number of purchases for 'External Drives' category for each customer within a specific year. Customers with three or more qualifying purchases are included in the output.

### SQL Question 7: What does do?

The SQL command merges the results of multiple statements and keeps only those rows that are present in all sets.

For example, say you were doing an HR Analytics project for Western Digital, and had access to Western Digital's employees and contractors data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables. You could use operator to find all contractors who also show up in the employees table:

### SQL Question 8: Find the Average Hard Drive Failure Rate

As a data analyst at Western Digital, a company that produces computer hard drives, you're asked to calculate the average failure rate of different models of hard drives. The failure rate is defined as the number of failed drives divided by the total number of drives sold, expressed as a percentage. We have a table that records each sale of a hard drive, and a table that records each drive failure.

##### Example Input:
sales_iddate_solddrive_modelquantity_sold
120106/18/2022WD_Blue5
145206/21/2022WD_Red3
174307/02/2022WD_Blue4
109807/10/2022WD_Red2
189008/15/2022WD_Blue3
##### Example Input:
failure_iddate_faileddrive_modelquantity_failed
901206/28/2022WD_Blue2
107307/05/2022WD_Red1
346507/20/2022WD_Blue1
665208/18/2022WD_Red1
493008/26/2022WD_Blue1

This query joins the sales and failures tables on the drive model. It then sums up the number of failures and sales for each model, and divides the two to find the failure rate. The COALESCE function is used to replace NULL values with 0 in case there are no failures for a specific drive model. The final result is cast to a numeric type with 5 total digits and 2 decimal places for readability.

To practice a very similar question try this interactive Facebook App Click-through Rate (CTR) Question which is similar for calculating a rate in percentage or this Amazon Average Review Ratings Question which is similar for finding an average.

### SQL Question 9: Calculate the Click-through Rate for Western Digital

In the marketing team at Western Digital, we track user behavior in response to our digital ads. We record whenever a user views one of our ads (an ) and whenever that user then clicks on the ad (). We then determine the click-through rate (CTR) which is the ratio of users who click on our ads to the number of total users who view the ads.

Given tables and with the following structures, write a SQL query to calculate CTR for each ad in April 2022.

##### Table:
101104/01/2022 00:00:005001
102204/03/2022 00:00:007002
103304/30/2022 00:00:005001
##### Table:
501104/01/2022 00:01:005001
502204/03/2022 00:01:007002

This query first connects impressions to their corresponding clicks by user_id and ad_id on the same day. It then restricts to April 2022 impressions and for each ad, it calculates the number of clicks divided by the number of impressions to calculate the CTR. Note that if there are no clicks for a given impression, the join will still keep the impression but with a NULL click_id, which will not be counted by the COUNT() function.

To practice a similar problem about calculating rates, try this TikTok SQL question within DataLemur's online SQL coding environment:

### SQL Question 10: Why is database normalization a good idea?

Database normalization is a good idea to implement because it can reduce redundancy which can improve performance and database flexibility.

By dividing larger tables into smaller, more modular and specific tables which are linked via foreign keys, this can usually improve the speed of some queries because it minimizes the amount of random data the query has to sift through. However, it's not always 100% true that there is a query speed-up, because joins are an expensive operation.

Nonetheless, by reducing redundancy, besides improved performance you also get more database flexibility. By making tables more modular and reducing overlap, you're able to more easily, since one table can be changed more effortlessly without affecting others. This makes it easier to adapt the database schema to Western Digital's evolving business needs.

### SQL Question 11: Find the Average Sales per Product Type

As a data analyst at Western Digital, you are tasked with understanding sales trends. For each product type, you are required to calculate the average number of units sold every year. Assume that one purchase equals to one unit sold.

Here's some example tables for this problem:

##### Example Input:
sale_idproduct_typeproduct_idpurchase_datecustomer_id
101Solid State Drive101/12/202110001
102Solid State Drive103/20/202110002
103Hard Disk Drive207/09/202110003
104Hard Disk Drive206/29/202110001
105Solid State Drive112/05/202110004
##### Example Output:
yearproduct_typeavg_units_sold
2021Solid State Drive2
2021Hard Disk Drive1

To solve this, we can use the GROUP BY statement to separate the sales by year and product type. Then, we can use the COUNT function to calculate the total units sold and derive the average from it.

The PostgreSQL query may look like this:

This query extracts the year from the purchase_date, groups the sales by year and product type, and calculates the average units sold per product type using COUNT.

### How To Prepare for the Western Digital 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. Besides solving the above Western Digital SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like FAANG tech companies and tech startups.

Each DataLemur SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there is an online SQL coding environment so you can right in the browser run your query and have it graded.

To prep for the Western Digital SQL interview it is also wise to practice SQL questions from other technology semiconductor companies like:

Stay ahead of the curve with Western Digital's latest AI-powered storage solution!

But if your SQL skills are weak, forget about diving straight into solving questions – improve your SQL foundations with this interactive SQL tutorial.

This tutorial covers things like math functions and 4 types of JOINS – both of which pop up routinely during Western Digital SQL interviews.

### Western Digital Data Science Interview Tips

#### What Do Western Digital Data Science Interviews Cover?

Beyond writing SQL queries, the other types of problems to practice for the Western Digital Data Science Interview are:

• Statistics and Probability Questions
• Coding Questions in Python or R
• Analytics and Product-Metrics Questions
• ML Modelling Questions
• Behavioral Questions centered on Western Digital culture and values

#### How To Prepare for Western Digital Data Science Interviews?

To prepare for Western Digital Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions taken from Microsoft, Amazon & startups
• a refresher on SQL, Product-Sense & ML
• over 1000+ reviews on Amazon & 4.5-star rating

Don't forget about the behavioral interview – prep for that using this list of common Data Scientist behavioral interview questions.