11 Western Digital SQL Interview Questions (Updated 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:

Example Input:

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.

Answer:

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:

Example Output:

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:

Answer:

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:

:

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:

Example Output:

Answer:

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:

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:

Example Input:

Example Input:

Answer:

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:

Example Input:

Answer:

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:

Table:

Answer:

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:

Example Output:

Answer:

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:

• Intel SQL questions
• Micron SQL questions
• Applied Materials SQL questions
• NetApp SQL questions

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.