10 Intel SQL Interview Questions (Updated 2024)

At Intel, SQL is used often for analyzing large datasets of manufacturing and supply-chain data related to making chips. They also support data compression & security via Intel QAT for Microsoft SQL Server. Because of this, there's currently 47 Intel jobs which require SQL skills:

This is also why Intel typically asks SQL questions in interviews for Data Analytics, Data Science, and Data Engineering jobs. So, in case you're preparing for an Intel SQL Interview, here’s 10 Intel SQL interview questions to practice – how many can you solve?

10 Intel SQL Interview Questions

SQL Question 1: Compute Average Product Review Ratings Per Month

Intel is interested in evaluating the performance of its products based on user reviews. Given the table that contains a product's ID, the date the review was submitted, and a user's given star rating (1 through 5), write a SQL query to compute the average star rating for each product per month.

Example Input:

Example Output:

Answer:

This PostgreSQL query takes the month from the of each review, together with the , and calculates the average for each group. The function is used to retrieve the month part of the date. The result is ordered by month and product ID for easier reading.

SQL Question 2: Intel Products Manufacturing Data

Intel, as a pioneering company in the semiconductor industry, has a large scale of manufacturing operations. There is a continuous need to monitor and analyze the manufacturing data to drive optimizations and maintain high-quality standards. Let's assume Intel has a table that keeps track of each product and its manufacturing details, and an table that stores the quality inspection results for each product.

Our task is to design related database tables, and write a PostgreSQL query to find and list all products that have failed quality inspection more than once last month.

Example Input:

Example Input:

Answer:

We will use a subquery to first find all the failed inspections from the last month, group them by and filter out the ones with more than one failure. Then, we'll join with the table to get the product names.

The above query fetches all the products that had more than one failed inspection in the last month. The sub-query groups the inspection results by , counts the inspection fails, and filters out only those with more than one fail. It then joins with the table to get the product names. This would provide intel with the necessary information to scrutinize its manufacturing process for these particular products that are failing the quality inspection multiple times.

SQL Question 3: Can you describe the role of the constraint and provide an example of a situation where it might be applied?

The CHECK constraint is used to enforce rules on the data in a specific column. If a row is inserted or updated with data that does not follow the CHECK constraint's rule, the operation will fail.

For example, say you had a database that stores ad campaign data from Intel's Google Analytics account.

Here's what some constraints could look like:

In this example, the constraint is used to ensure that the "budget" and "cost_per_click" fields have positive values. This helps to ensure that the data in the database is valid and makes sense in the context of ad campaigns.

You can also use the constraint to ensure that data meets other specific conditions. For example, you could use a constraint to ensure that the "start_date" is before the "end_date" for each ad campaign.

SQL Question 4: Calculating Click-through-rate for Intel Ads

Given a table of user click events on Intel's digital advertisement and another table for user purchases, calculate the click-through conversion rate, defined as the number of users who made a purchase after clicking the ad divided by the total number of users who clicked the ad.

Example Input:

Example Input:

Answer:

This query first creates two CTEs, one with the unique users who clicked on the ads and another with the users who made purchases after clicking. Then, it counts the total number of clicks and purchases. Finally, it calculates the click-through conversion rate by dividing the total purchases by the total clicks. The rate is multiplied by 100 to convert it into percentage.

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

SQL Question 5: What's the purpose of the function in SQL?

The function accepts an unlimited number of input arguments, and returns the first argument from that list which isn't null.If all input arguments are null, will return null too.

For example, suppose you had data on Intel salespeople, and the amount of deals they closed. This data was exported from a 3rd-party system CRM, which exports a value if the salesperson didn't close any deals.

To get rid of these NULLs, and replace them with zero's (so you can do some further analytics like find the average number of closed deals), you would use the function as follows:

You'd get the following output:

SQL Question 6: Average Rating per CPU Product

In Intel, we are interested in the performance and quality of our CPU (Central Processing Unit) products over time. One way of gauging product performance is by analyzing the ratings given by our customers. As a data analyst, we need you to write a query that will provide us with the average rating (stars) per CPU product for each year.

For this question, we are assuming that we have 2 tables. The first table is and the other is .

Answer:

For PostgreSQL:

Here, we are first extracting the year from review date using the function. Then, we join the and tables on the product_id column. The average rating is calculated using the function and rounded to 2 decimal places using Finally, the result is grouped by year and product, and ordered by year and product for easy reading. Any NULL values in the reviews or products tables could impact this calculation and should be addressed in the data-cleaning stage.

To practice another question about calculating rates, solve this TikTok SQL question on DataLemur's interactive coding environment:

SQL Question 7: What are the different kinds of joins in SQL?

In SQL, a join retrieves rows from multiple tables and combines them into a single result set.

Four JOIN types can be found in SQL. For an example of each one, suppose you had a table of Intel orders and Intel customers.

1. INNER JOIN: Rows from both tables are retrieved when there is a match in the shared key or keys. An between the Orders and Customers tables would return only rows where the in the Orders table matches the in the Customers table.

2. LEFT JOIN: A retrieves all rows from the left table (in this case, the Orders table) and any matching rows from the right table (the Customers table). If there is no match in the right table, NULL values will be returned for the right table's columns.

3. RIGHT JOIN: A combines all rows from the right table (in this case, the Customers table) and any matching rows from the left table (the Orders table). If there is no match in the left table, NULL values will be displayed for the left table's columns.

4. FULL OUTER JOIN: A combines all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, NULL values will be displayed for the columns of the non-matching table.

SQL Question 8: Find Intel Employees

Intel Corp. wants to filter through its employee database to find employees who have 'Systems Engineer' in their job titles and who got hired in the year 2020. The 'employees' table consists of the fields 'employee_id', 'name', 'job_title', 'hire_date', 'salary' and 'dept_name'.

Example Input:

Expected Output:

Answer:

This query looks for employees who have 'Systems Engineer' within their job titles, making use of the LIKE keyword in conjunction with the '%' placeholder. It further filters these results to only include employees who were hired in the year 2020 by using the EXTRACT function. The query finally outputs the details of these filtered employees, such as their 'employee_id', 'name', 'job_title', 'hire_date', 'salary' and 'dept_name'.

To practice a related problem on DataLemur's free interactive SQL code editor, attempt this Meta SQL interview question:

SQL Question 9: Purchase Analysis Combined From Customers and Products

Analyze the purchasing behavior of Intel's customers and identify the most bought product. The analysis will be based on two tables: and .

The table has five columns: , , , and (the date when the customer was added).

Example Input for :

The table has four columns: , (linked to the table), and .

Example Input for :

The question is to write a SQL query that returns the most purchased product by customers in Intel. If more than one product has the most purchases, return all of them.

Answer:

This query first counts the number of purchases per product, then identifies the maximum purchase count, and finally, returns the ID(s) of the product(s) with the maximum purchase count. This allows Intel to identify the product that is most popular among its customers.

SQL Question 10: What sets the 'BETWEEN' and 'IN' operators apart?

The and operators are both used to filter data based on certain criteria, but they work in different ways. is used to select values within a range, while is used to select values that match a list.

For instance, if you have a table called that contains the salary of each employee, along with which country they reside in, you could use the operator to find all employees who make between $130k and$160k:

To find all employees that reside in France and Germany, you could use the operator:

How To Prepare for the Intel SQL Interview

The best way to prepare for a Intel SQL interview is to practice, practice, practice. Besides solving the earlier Intel SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like FAANG and tech startups.

Each interview question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and most importantly, there's an online SQL code editor so you can easily right in the browser your SQL query and have it graded.

To prep for the Intel SQL interview it is also wise to solve interview questions from other tech companies like:

• NVIDIA SQL questions
• Apple SQL questions
• Microsoft SQL questions
• Google SQL questions

In case your SQL skills are weak, don't worry about jumping right into solving questions – refresh your SQL knowledge with this free SQL for Data Analytics course.

This tutorial covers things like 4 types of JOINS and how window functions work – both of these show up routinely during SQL job interviews at Intel.

Intel Data Science Interview Tips

What Do Intel Data Science Interviews Cover?

For the Intel Data Science Interview, in addition to SQL query questions, the other types of questions which are covered:

• Probability & Statistics Questions
• Python or R Coding Questions
• Business Sense and Product-Sense Questions
• ML Modelling Questions
• Behavioral & Resume-Based Questions

How To Prepare for Intel Data Science Interviews?

The best way to prepare for Intel Data Science interviews is by reading Ace the Data Science Interview. The book's got:

• 201 Interview Questions from tech companies like Google & Microsoft
• A Crash Course on SQL, Product-Sense & ML
• Great Reviews (900+ 5-star reviews on Amazon)

Also it's important to have a strong understanding on how Data Science is used and its impact on the Supply Chain process, read an example use case in from Intel in this blog article!