8 NXP Semiconductors SQL Interview Questions (Updated 2024)
At NXP Semiconductors, SQL is used all the damn time for At NXP Semiconductors, SQL is used for managing semiconductor production data and conducting performance analytics on chipset designs. Unsurprisingly this is why NXP Semiconductors often tests SQL query questions in interviews for Data Analyst, Data Science, and BI jobs.
So, to help you ace the NXP Semiconductors SQL interview, this blog covers 8 NXP Semiconductors SQL interview questions – how many can you solve?
8 NXP Semiconductors SQL Interview Questions
SQL Question 1: Find the monthly average sales per product
At NXP Semiconductors, suppose we have a sales records table detailing the sales data of various products over time. For a particular product, a record is created whenever it's sold, along with the date of the sale and the product's unit price at the time of the sale.
Now, write a SQL query that calculates the monthly average unit price for each product using a window function.
Imagine you have the following table for input:
Example Input:
| sale_id | sale_date | product_id | unit_price |
|---|---|---|---|
| 101 | 2017-01-10 | NXP01 | 50 |
| 102 | 2017-01-20 | NXP02 | 150 |
| 103 | 2017-02-05 | NXP01 | 52 |
| 104 | 2017-02-17 | NXP02 | 148 |
| 105 | 2017-03-10 | NXP01 | 51 |
| 106 | 2017-03-12 | NXP01 | 53 |
Your expected output table should look like this:
Example Output:
| month | product_id | avg_unit_price |
|---|---|---|
| 01 | NXP01 | 50 |
| 01 | NXP02 | 150 |
| 02 | NXP01 | 52 |
| 02 | NXP02 | 148 |
| 03 | NXP01 | 52 |
Answer:
Here's the SQL code:
This query uses a window function to calculate the average unit price for each product per month. The clause in the function distributes rows into ordered partitions such that rows with the same and month fall into the same partition. The function then computes the average unit price over these partitions. The resulting avg_unit_price for each row is the average unit price for that product in that month.
To solve a similar window function interview problem which uses RANK() on DataLemur's free online SQL coding environment, try this Amazon SQL Interview Question:
SQL Question 2: Find the average lifespan of each type of semiconductor chip produced by NXP Semiconductors.
NXP Semiconductors, a leading tech company focused on crafting solutions for automotive, industrial & IoT, mobile, and communication infrastructure, needs to analyze the average lifespan of each type of semiconductor chip they produce. Their database contains two tables: , which holds information about each chip produced, and , which logs when a chip fails.
The table contains the , , and . The table includes and .
Help NXP Semiconductors analyze their product longevity by writing a SQL query that calculates the average lifespan (in days) of each chip type.
Example Input:
| chip_id | chip_type | manufacture_date |
|---|---|---|
| 2839 | MCU | 2020-02-01 |
| 4216 | RF | 2021-02-15 |
| 3945 | MCU | 2019-11-07 |
| 1892 | SOC | 2020-09-30 |
| 5371 | RF | 2021-01-03 |
Example Input:
| chip_id | failure_date |
|---|---|
| 2839 | 2022-08-01 |
| 4216 | 2022-08-01 |
| 3945 | 2022-08-01 |
| 1892 | 2022-08-01 |
| 5371 | 2022-08-01 |
Answer:
This query first joins the and table on . Then for each type of chip (), it calculates the average lifespan by subtracting the from the and extracts the days. The result will be the average lifespan in days for each chip type produced by NXP Semiconductors.
To practice a very similar question try this interactive Google Odd and Even Measurements Question which is similar for dealing with IoT sensor data analysis or this Amazon Server Utilization Time Question which is similar for calculating time-related values.
SQL Question 3: How can you select unique records from a table?
The keyword removes duplicates from a query.
Suppose you had a table of NXP Semiconductors customers, and wanted to figure out which cities the customers lived in, but didn't want duplicate results.
table:
| name | city |
|---|---|
| Akash | SF |
| Brittany | NYC |
| Carlos | NYC |
| Diego | Seattle |
| Eva | SF |
| Faye | Seattle |
You could write a query like this to filter out the repeated cities:
Your result would be:
| city |
|---|
| SF |
| NYC |
| Seattle |
SQL Question 4: Calculating Click-Through Rates for NXP Semiconductors' Digital Products
Given the following databases and , calculate the click-through rate (CTR) for each product. The CTR is defined as the number of unique product clicks divided by the number of unique site visits.
Example Input:
| visit_id | user_id | visit_date |
|---|---|---|
| 3421 | 124 | 06/08/2022 00:00:00 |
| 5402 | 287 | 06/10/2022 00:00:00 |
| 8256 | 485 | 06/18/2022 00:00:00 |
| 2025 | 192 | 07/26/2022 00:00:00 |
| 4173 | 980 | 07/05/2022 00:00:00 |
Example Input:
| click_id | user_id | click_date | product_id |
|---|---|---|---|
| 2914 | 124 | 06/08/2022 00:00:00 | 30002 |
| 4367 | 287 | 06/10/2022 00:00:00 | 20013 |
| 6756 | 485 | 06/18/2022 00:00:00 | 30002 |
| 2317 | 192 | 07/26/2022 00:00:00 | 20013 |
| 6331 | 124 | 07/05/2022 00:00:00 | 30002 |
Answer:
To solve this, we first need to create subqueries for unique website visits and unique product clicks, and then join them on the . Then to calculate the click through rate, we divide the count of unique product clicks by count of unique site visits. Here is the PostgreSQL query:
This query will return results showing the calculated click-through rates for each product on NXP Semiconductors' website. The COALESCE function is used to handle potential null values in the number of clicks, replacing them with zero.
To practice a related problem on DataLemur's free interactive SQL code editor, attempt this Facebook SQL Interview question:
SQL Question 5: What do the SQL commands / do?
For a tangible example of in PostgreSQL, suppose you were doing an HR Analytics project for NXP Semiconductors, and had access to NXP Semiconductors's contractors and employees 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 never were a employee using this query:
Note that is available in PostgreSQL and SQL Server, while is the equivalent operator which is available in MySQL and Oracle (but don't worry about knowing which RDBMS supports which exact commands since NXP Semiconductors interviewers aren't trying to trip you up on memorizing SQL syntax).
SQL Question 6: Average Sale Price Per Product
As an analyst at NXP Semiconductors, you have been tasked to identify which products have the highest average sales price. You will need to create a report summarizing the average sales price for each product sold in the previous year, grouped by product id.
Assume that you have a table that contains sales data. The relevant fields in the table are , , , and .
Example Input:
| sale_id | product_id | sale_date | sale_price |
|---|---|---|---|
| 1511 | 2002 | 05/20/2021 | 250.0 |
| 3210 | 2004 | 06/05/2021 | 197.5 |
| 5683 | 2009 | 07/01/2021 | 400.0 |
| 7645 | 2002 | 07/26/2021 | 275.0 |
| 9120 | 2004 | 08/15/2021 | 210.0 |
| 1011 | 2009 | 08/30/2021 | 410.0 |
Example Output:
| product_id | average_sale_price |
|---|---|
| 2002 | 262.5 |
| 2004 | 203.75 |
| 2009 | 405.0 |
Answer:
In this query, we are calculating the average sale price for each product for the previous year. We do this by grouping the sales by and then calculating the average for each group. The WHERE clause is used to filter out sales that were not made in the previous year. This is important to make sure that our analysis is relevant to the current market situation.
SQL Question 7: What is a foreign key?
A foreign key is a column or group of columns in a table that refers to the primary key in another table. The foreign key constraint helps maintain referential integrity between the two tables.
Let's examine employee data from NXP Semiconductors's HR database:
:
+------------+------------+------------+------------+ | employee_id| first_name | last_name | manager_id | +------------+------------+------------+------------+ | 1 | Aubrey | Graham | 3 | | 2 | Marshal | Mathers | 3 | | 3 | Dwayne | Carter | 4 | | 4 | Shawn | Carter | | +------------+------------+------------+------------+
In this table, serves as the primary key and functions as a foreign key because it links to the of the employee's manager. This establishes a relationship between NXP Semiconductors employees and their managers, allowing for easy querying to find an employee's manager or see which employees report to a specific manager.
The table may also have multiple foreign keys that reference primary keys in other tables. For example, and foreign keys could be used to connect each employee to their respective department and location.
SQL Question 8: Joining Customer and Orders Database
Write a SQL query to get a list of customers who have purchased 'Semiconductor' products. The output should include their customer ID, name, product ID and order date. The customers’ data is stored in a 'Customers' table and the order data is stored in an 'Orders' table. Please display the most recent order if a customer has multiple orders.
Sample Input
| customer_id | name |
|---|---|
| 171 | John Doe |
| 472 | Jane Smith |
| 563 | Tom Johnson |
| 947 | Emily Davis |
| 118 | Jessica White |
Sample Input
| order_id | product_id | order_date | customer_id |
|---|---|---|---|
| 6171 | NX50001 | 2022-01-05 | 171 |
| 7802 | NX69852 | 2022-04-17 | 472 |
| 5293 | NX50001 | 2022-03-02 | 563 |
| 6352 | NX69852 | 2022-06-26 | 947 |
| 4517 | NX69852 | 2022-02-05 | 118 |
Answer:
This query joins the Customers and Orders table on the customer_id field. It selects the customer_id, name, and product_id fields. The MAX function is used to retrieve the most recent order_date. The WHERE clause filters for inventory items, 'product_id', beginning with 'NX' which represents 'Semiconductor' products. The query groups the output by customer_id, name, and product_id and orders the output in descending order of the most_recent_order_date.
Because joins come up frequently during SQL interviews, try an interactive Spotify JOIN SQL question:
How To Prepare for the NXP Semiconductors SQL Interview
The key to acing a NXP Semiconductors SQL interview is to practice, practice, and then practice some more!
Beyond just solving the above NXP Semiconductors SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Facebook, Google and unicorn tech startups.
Each DataLemur SQL question has hints to guide you, step-by-step solutions and most importantly, there is an interactive SQL code editor so you can easily right in the browser your SQL query answer and have it executed.
To prep for the NXP Semiconductors SQL interview you can also be a great idea to practice interview questions from other tech companies like:
In case your SQL coding skills are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.
This tutorial covers SQL concepts such as cleaning text data and CASE/WHEN statements – both of these come up routinely during NXP Semiconductors SQL interviews.
NXP Semiconductors Data Science Interview Tips
What Do NXP Semiconductors Data Science Interviews Cover?
Beyond writing SQL queries, the other types of questions tested in the NXP Semiconductors Data Science Interview are:
- Statistics Interview Questions
- Python or R Coding Questions
- Product-Sense Questions
- Machine Learning Questions
- Resume-Based Behavioral Questions
How To Prepare for NXP Semiconductors Data Science Interviews?
The best way to prepare for NXP Semiconductors Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from companies like Google, Tesla, & Goldman Sachs
- A Crash Course covering Stats, SQL & ML
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