9 GlobalFoundries SQL Interview Questions (Updated 2024)
At GlobalFoundries, SQL is used across the company for analyzing process data for optimizing chip fabrication, and managing material tracking systems for supply chain optimization & resilience. Unsurprisingly this is why GlobalFoundries LOVES to ask SQL problems in interviews for Data Science, Analytics, and & Data Engineering jobs.
As such, to help you practice for the GlobalFoundries SQL interview, we've curated 9 GlobalFoundries SQL interview questions – how many can you solve?
9 GlobalFoundries SQL Interview Questions
SQL Question 1: Analyzing GlobalFoundries Chip Performance
As a data scientist for GlobalFoundries, a leading company specializing in delivering semiconductor technologies, your team is responsible for evaluating the performance of produced chips. You are tasked to analyze the average chip performance per production batch for the past year. Using window functions, write a SQL query to find the average chip performance for each production batch.
Assume that the company has two tables: 'chip' and 'production_batch'. The 'chip' table details each chip produced by GlobalFoundries, including its , , and which assesses the chip's performance. Each chip belongs to a specific in the 'production_batch' table, which contains details about the batch including the and .
Example Input:
| chip_id | batch_id | performance_score |
|---|---|---|
| 1 | 1 | 95 |
| 2 | 1 | 96 |
| 3 | 2 | 85 |
| 4 | 2 | 80 |
| 5 | 3 | 92 |
Example Input:
| batch_id | batch_date |
|---|---|
| 1 | 01/10/2022 |
| 2 | 02/10/2022 |
| 3 | 03/15/2022 |
Your output should indicate for each the average .
Example Output:
| batch_id | avg_chip_performance |
|---|---|
| 1 | 95.5 |
| 2 | 82.5 |
| 3 | 92.0 |
Answer:
This query joins the 'chip' table to the 'production_batch' table on . Then, it calculates the average chip performance per batch for the chips produced last year using the aggregate function, which is applied to the column, partitioned by . The statement causes the function to compute a separate average for each unique .
Pro Tip: Window functions are a frequent SQL interview topic, so practice all the window function problems on DataLemur
SQL Question 2: Filter customer data based on specific criteria
For GlobalFoundries, a company specializing in semiconductor foundry, you've been given access to their database of orders placed by various clients. In particular, they are interested in understanding orders placed within the current year for certain product lines, specifically DUV (Deep Ultraviolet) and EUV (Extreme Ultraviolet).
Your task is to write a query that returns customer data for orders placed in the current year (2022) for the specified product lines (DUV and EUV). Also, ignore the data where the quantity ordered is less than 10.
Example Input:
| order_id | customer_id | order_date | product_line | quantity |
|---|---|---|---|---|
| 2016 | 425 | 01/12/2022 00:00:00 | EUV | 50 |
| 3059 | 489 | 02/10/2022 00:00:00 | FinFET | 15 |
| 6043 | 592 | 03/05/2022 00:00:00 | DUV | 30 |
| 8005 | 125 | 04/04/2022 00:00:00 | EUV | 5 |
| 7112 | 392 | 05/20/2022 00:00:00 | DUV | 9 |
Example Output:
| order_id | customer_id | order_date | product_line | quantity |
|---|---|---|---|---|
| 2016 | 425 | 01/12/2022 00:00:00 | EUV | 50 |
| 6043 | 592 | 03/05/2022 00:00:00 | DUV | 30 |
Answer:
In the query, we begin by selecting all columns from the 'orders' table. The WHERE clause specifies the conditions for retrieving the data. The order_date BETWEEN '2022-01-01' AND '2022-12-31' restricts the data to records from the current year (2022). The conditions (product_line = 'DUV' OR product_line = 'EUV') matches any orders specifically from DUV and EUV product lines. Lastly, the condition quantity >= 10 ignores any records where the quantity ordered is less than 10.
SQL Question 3: Can you describe the concept of a database index and the various types of indexes?
A database index is a data structure that improves the speed of data retrieval operations on a database table.
There are few different types of indexes that can be used in a database:
- Primary index: a unique identifier is used to access the row directly.
- Unique index: used to enforce the uniqueness of the indexed columns in a table.
- Composite index: created on multiple columns of a table, is used to speed up the search process for multiple columns
- Clustered index: determines the physical order of the data in a table
For a concrete example, say you had a table of GlobalFoundries customer payments with the following columns:
Here's what a clustered index on the column would look like:
A clustered index on the column would determine the physical order of the records in the table based on the . This means that the records with the earliest values would be stored together physically in the table, followed by records with later payment_date values. This speeds up queries that filter or sort the data based on the , as the records are already physically sorted in the table. For example, if you want to retrieve all the payments made in the month of June, the database can use the clustered index to quickly locate and retrieve the desired records without having to search through the entire table.
SQL Question 4: Analyzing Click-Through Rates for GlobalFoundries Digital Ads
Imagine GlobalFoundries, a major semiconductor foundry company, is running a marketing campaign via its digital channels. The company is tracking two steps: the number of times an ad has been viewed, and whether viewers eventually clicked on the Add to Cart button in the product landing page.
The company needs to know the click-through rate (CTR) for this product viewing to 'Add to Cart' action, in order to gauge the effectiveness of various advertisements.
You have been given two tables:
Example Input:
| ad_id | user_id | view_date |
|---|---|---|
| 10 | 105 | 2022-06-08 |
| 15 | 240 | 2022-06-10 |
| 27 | 360 | 2022-06-11 |
| 32 | 192 | 2022-07-12 |
| 45 | 230 | 2022-07-14 |
Example Input:
| cart_id | user_id | ad_id | add_date |
|---|---|---|---|
| 101 | 105 | 10 | 2022-06-08 |
| 105 | 360 | 27 | 2022-06-12 |
| 109 | 105 | 15 | 2022-06-10 |
| 114 | 192 | 32 | 2022-07-13 |
| 116 | 230 | 45 | 2022-07-14 |
We need to calculate the click-through rate (CTR) for each ad, which is defined as the number of 'Add to Cart' actions divided by the number of views, per ad. Present the result in descending order of CTRs.
Answer:
This will provide a list of ads along with their click-through rates, total number of 'Add to Cart' actions and total number of views. The higher the click-through rate, the more effective the ad is considered. The use of LEFT JOIN allows inclusion of all ads, even those with no 'Add to Cart' actions.
To practice a similar problem about calculating rates, solve this SQL interview question from TikTok within DataLemur's interactive coding environment:
SQL Question 5: What is the purpose of the UNIQUE constraint?
A UNIQUE constraint ensures that all values in a column are different. This provides uniqueness for the column(s) and helps identify each row uniquely. Unlike primary key, there can be multiple unique constraints defined per table.
SQL Question 6: Average Cost of Projects By Month
In GlobalFoundries, they manage multiple projects for manufacturing semiconductors. A project can span multiple months. Given a table that records each project's id, the month when the project started, and its cost, write a query to find the average cost of projects for each month.
Example Input:
Example Output:
Answer:
In this query, we start by selecting the and columns from the table. We use the clause to group the result by . Then, we use the function to calculate the average project cost for each month. We order the result by to get the result in chronological order.
SQL Question 7: Can you describe the different types of joins in SQL?
Using a join in SQL, you can retrieve data from multiple tables and merge the results into a single table.
In SQL, there are four distinct types of JOINs. To demonstrate each kind, Imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.
-
: An INNER JOIN retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.
-
: A LEFT JOIN retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.
-
: A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.
-
: A FULL OUTER JOIN retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.
SQL Question 8: Customer and Order Analysis
You are tasked to analyze the customer base of GlobalFoundries. Write a SQL query to join the table with the table and find the total number of orders and total spending for each customer. The table has the following fields: , , , and . The table contains the fields: , , , , and .
Example Input:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 1 | John | Doe | johndoe@example.com |
| 2 | Jane | Smith | janesmith@example.com |
| 3 | Jim | Brown | jimbrown@example.com |
Example Input:
| order_id | customer_id | product_id | quantity | price_per_unit |
|---|---|---|---|---|
| 1001 | 1 | 2001 | 5 | 20.00 |
| 1002 | 1 | 2002 | 1 | 15.00 |
| 1003 | 2 | 2003 | 2 | 30.00 |
| 1004 | 3 | 2003 | 1 | 30.00 |
Answer:
Here is the SQL statement that performs the required task.
This SQL statement uses the inner join operation to combine the and tables based on matching . The output includes the customer details, total number of orders, and total spending by each customer. The results are grouped by in table, implying each row in the output represents a unique customer. Please note that the calculation of assumes that the total cost for each order is calculated by times .
Because joins come up frequently during SQL interviews, try an interactive SQL join question from Spotify:
SQL Question 9: Average Time to Manufacture Products
GlobalFoundries is involved in the manufacturing of semiconductor chips. Let's say they keep a detailed record of when each product batch manufacturing process starts and ends. Now, they want you to help them calculate the average time it took to manufacture each product in a specific month. You are given a table named with columns , , , and that logs the start and end timestamps of every batch production of a certain product.
Example Input:
| product_id | batch_id | start_time | end_time |
|---|---|---|---|
| A123 | B001 | 05/01/2022 08:00:00 | 05/01/2022 12:00:00 |
| A123 | B002 | 05/02/2022 10:00:00 | 05/02/2022 14:00:00 |
| B234 | B003 | 06/01/2022 09:00:00 | 06/01/2022 13:00:00 |
| B234 | B004 | 06/02/2022 11:00:00 | 06/02/2022 15:00:00 |
| A123 | B005 | 06/03/2022 08:00:00 | 06/03/2022 13:00:00 |
Your task is to write a query that shows the average time spent manufacturing each product per month.
Answer:
This PostgreSQL query uses the function to get the month of the . Then, it uses the and functions to calculate the difference between the and in seconds. This value is then converted to hours by dividing by 3600. It finally calculates the average of these differences for each product and month using the function. The output is ordered by and .
Preparing For The GlobalFoundries SQL Interview
The key to acing a GlobalFoundries SQL interview is to practice, practice, and then practice some more!
In addition to solving the above GlobalFoundries SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Netflix, Google, and Amazon.
Each exercise has hints to guide you, full answers and crucially, there is an interactive SQL code editor so you can right online code up your query and have it executed.
To prep for the GlobalFoundries SQL interview you can also be a great idea to solve SQL questions from other semiconductor companies like:
However, if your SQL coding skills are weak, don't worry about jumping right into solving questions – strengthen your SQL foundations with this SQL interview tutorial.
This tutorial covers SQL topics like handling dates and using LIKE – both of these come up often in SQL interviews at GlobalFoundries.
GlobalFoundries Data Science Interview Tips
What Do GlobalFoundries Data Science Interviews Cover?
Besides SQL interview questions, the other question categories tested in the GlobalFoundries Data Science Interview are:
- Probability & Stats Questions
- Python or R Programming Questions
- Product Analytics Questions
- Machine Learning and Predictive Modeling Questions
- Behavioral Based Interview Questions
How To Prepare for GlobalFoundries Data Science Interviews?
To prepare for GlobalFoundries Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from FAANG (FB, Apple, Amazon, Netflix, Google)
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