# 8 ASML Holding SQL Interview Questions

Updated on

February 7, 2024

At ASML (Advanced Semiconductor Materials Lithography), SQL is used across the company for analyzing semiconductor production and to manage the databases associated with their lithography machine software. Because of this, ASML frequently asks SQL coding questions during interviews for Data Science and Data Engineering positions. To help, here's 8 ASML Holding SQL interview questions to practice – how many can you solve?

## 8 ASML Holding SQL Interview Questions

Sure, here is a SQL window function question for ASML using the context of wafer production.

### SQL Question 1: Calculating Running Average of Wafer Production

Consider the ASML's wafer production cycle. Wafers are produced in batches and each batch is assigned a . Each batch goes through several production stages before it is completed, with a recorded for each batch. Also recorded is the produced in each batch.

We want you to calculate a running average of produced for each month, considering each month as a separate period for this running average. Note that we would want to consider batches completed only till date.

##### Example Input
batch_idcompletion_datenumber_of_wafers
100101/15/2021250
102302/01/2021300
105002/27/2021275
108003/01/2021310
110203/15/2021290
##### Example Output
monthrunning_avg_wafers
1250.00
2275.00
3301.66

This query first extracts the month from the for each batch. Then, the window function combined with is used to compute a running average of for each month. The inside the window function chronologically sorts the data before applying the window function. The clause means that all preceding rows (sorted chronologically) and the current row will be considered while calculating the running average. The final sorts the result by month.

Remember to execute this query in a PostgreSQL environment as not all SQL dialects fully support window functions.

To practice a related window function SQL problem on DataLemur's free online SQL coding environment, try this Amazon SQL question asked in a BI Engineer interview:

### SQL Question 2: ASML Machinery Maintenance Tracking

ASML is a company specializing in manufacturing machines for chip production. As machines require periodic maintenance, ASML needs to keep track of different types of machines, their maintenance schedules, and which engineers are assigned to them.

The model entails 3 tables capturing the , , and assigned to each maintenance task. They would like to know which machines are due for maintenance this month and which engineers are assigned for those tasks.

Here are sample tables to illustrate the problem:

machine_idmachine_typeinstallation_date
1001TypeA2018-03-18
1002TypeB2019-07-30
1003TypeC2020-06-15
300110012022-11-01
300210022022-11-15
300310032022-12-01
50013001John Smith
50023002Sally Johnson
50033003Robert Williams

This SQL query joins the three tables on the relevant columns and then selects the machines due for maintenance this month, including the engineer assigned for each task. It uses the DATE_TRUNC function to truncate the and the current date to the month level, to compare them properly. The result table gives ASML a quick overview of which machines require maintenance this month and the assigned engineers. undefined

### SQL Question 3: In the context of a database transaction, what does ACID mean?

A DBMS (database management system), in order to ensure transactions are relaible and correct, tries to mantain the following ACID properties: Atomicity, Consistency, Isolation, and Durability

Here is what each of the ACID properties stands for:

Atomicity: ensures that a transaction is either completed in its entirety, or not completed at all. If a transaction fails halfway, the database does a rollback on the commit.

Consistency: ensures that a transaction will only be completed if adheres to the constraints defined in the database of the DB.

Isolation: ensures that concurrent transactions are isolated from each one another, so that the changes made by one transaction cannot be seen by a 2nd transaction until the 1st transaction is done.

**Durability: ** ensures that once a transaction has been committed, the database permanently stores the results in the DB.

As you can see, it's pretty important for ASML's data systems to be ACID compliant, else they'll be a big problem for their customers!

### SQL Question 4: Calculate the Average Chip Production Quantity

ASML is a company that manufactures chips for semiconductors. As a data scientist, you are tasked to analyze the overall production of their various chip products.

You have been given a database that contains two tables: and .

The table has the following fields:

• : Unique identifier for each product made by ASML.
• : Name of the product.
##### Example Input:
product_idproduct_name
50001Product A
69852Product B
36218Product C

The table has the following fields:

• : Unique identifier for each production record.
• : Identifier for the product.
• : Date the production was carried out.
• : The quantity of chips produced.
##### Example Input:
production_idproduct_idproduction_datequantity
15000106/08/2022200
26985206/10/2022400
35000106/18/2022300
46985207/26/2022250
56985207/05/2022150

Write an SQL query that returns each product and the average chip production quantity per month.

##### Example Output:
monthproductavg_quantity
6Product A250.00
6Product B400.00
7Product B200.00

This query first extracts the month from the production date and performs a join operation between the table and the table using as the join key. Then, it groups the results by month and product and finally calculates the average production quantity for each group, producing the desired output. undefined

### SQL Question 5: What is database denormalization, and when is it a good idea to consider it?

Denormalization is the practice of altering a database schema in a way that breaks the normalization rules (1st, 2nd, 3rd normal forms).

A few reasons to denormalize a database:

• Improved performance: Denormalization often reduces the the number of costly join operations that are needed to retrieve data. This is helpful when the database is being used for OLAP (Online Analytical Processing) use cases at ASML, as joins can be expensive and slow.

• Scalability: Denormalization can be like a turbo boost for your database's scalability! By requiring less data to be read and processed when executing a query, denormalization can help your database handle a ton of queries without breaking a sweat.

• Simplification: One way to simplify the design of a database is by using denormalization to reduce the number of tables and relationships that need to be managed. This can make the database easier to understand and maintain.

Of course, don't over-do the database denormalization magic – too much redundancy can increase data storage costs, and get complicated to manage if there's frequent commands that need to be run.

### SQL Question 6: Average Purchase Amount per Customer from Different Countries

ASML has a customer database in which each customer is from a different country. They also maintain a separate table recording all purchase transactions made by these customers. The task is to write a PostgreSQL query that determines the average amount of purchase for customers from each country.

##### Sample Input:
customer_idfirst_namelast_namecountry
1JohnDoeUSA
2JaneDoeGermany
3JimBrownNetherlands
4BobJohnsonUSA
##### Sample Input:
purchase_idcustomer_idpurchase_dateamount
1001101/03/2022250.00
1002201/10/2022300.00
1003301/20/2022200.00
1004102/03/2022350.00
1005302/20/2022450.00
1006403/01/2022150.00

This query first joins the and tables on the field, then it groups the results by the field and calculates the average purchase amount for each group.

Because joins come up frequently during SQL interviews, try an interactive SQL join question from Spotify:

### SQL Question 7: What does do, and when would you use this function?

The function is used to remove NULLs, and replace them with another value.

For example, say you were a Data Analyst at ASML and were doing a customer analytics project to see who the most marketing-engaged customers were, and had access to the below table.

asml_customers:

customer_idemail_engagementsms_engagement
101very_activenot_opted_in
201un-subscribedNULL
301NULLnot_opted_in
401not_activevery_active
501very_activemildly_active
303NULLNULL

Before you could procede, you had to remove the NULLs, and replace them with the default value (not_active for email, and not_opted_in for SMS). To do this, you'd run the following query:

This would get you the following output:

customer_idemail_engagementsms_engagement
101very_activenot_opted_in
201un-subscribednot_opted_in
301not_activenot_opted_in
401not_activevery_active
501very_activemildly_active
303not_activenot_opted_in

### SQL Question 8: Calculate the Monthly Average Equipment Down Time

ASML is a leading supplier of semiconductor manufacturing equipment. In their manufacturing sites, the equipment often needs to be maintained and occasionally breaks down, resulting in productive hours being lost. For this exercise, you are provided with a dataset containing timestamps of when production equipment goes down and when it gets back to operation.

Your task is to write a SQL query to calculate the average equipment downtime per month in hours.

##### Example Input:
down_time_idequipment_idstart_timeend_time
1E1012022-06-01 09:30:002022-06-01 11:30:00
2E1022022-06-10 14:15:002022-06-10 16:20:00
3E1012022-07-05 10:00:002022-07-05 13:00:00
4E1022022-07-15 12:00:002022-07-15 13:30:00
5E1012022-07-20 09:05:002022-07-20 12:15:00
##### Example Output:
monthavg_downtime_hours
62.17
72.75

In PostgreSQL, the function can be used to get the month and function to get the difference between the end and start times.

This query groups all the downtime instances by month. It then calculates the time difference between the end_time and start_time to get the duration of each downtime instance, averages them for each month, and orders the result by the month. The is used to get the difference in hours since EPOCH returns the result in seconds. undefined

### How To Prepare for the ASML SQL Interview

The key to acing a ASML SQL interview is to practice, practice, and then practice some more! Beyond just solving the above ASML SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Google, Microsoft and Silicon Valley startups.

Each exercise has hints to guide you, detailed solutions and crucially, there's an interactive SQL code editor so you can right in the browser run your SQL query and have it graded.

To prep for the ASML SQL interview you can also be wise to practice interview questions from other tech companies like:

However, if your SQL skills are weak, don't worry about jumping right into solving questions – refresh your SQL knowledge with this interactive SQL tutorial.

This tutorial covers things like LEAD/LAG window functions and aggregate window functions – both of these show up frequently in SQL interviews at ASML.

### ASML Holding Data Science Interview Tips

#### What Do ASML Data Science Interviews Cover?

For the ASML Data Science Interview, besides SQL questions, the other types of questions to prepare for are:

#### How To Prepare for ASML Data Science Interviews?

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

• 201 Interview Questions from Google, Microsoft & tech startups
• A Refresher on Stats, ML, & Data Case Studies
• Amazing Reviews (900+ 5-star reviews on Amazon)