8 National Instruments SQL Interview Questions (Updated 2024)
At National Instruments, SQL crucial for analyzing and manipulating large datasets for hardware testing, and managing customer data to enhance sales operations. That's why National Instruments LOVES to ask SQL query questions in interviews for Data Science, Data Engineering and Data Analytics jobs.
So, to help you prepare for the National Instruments SQL interview, here’s 8 National Instruments SQL interview questions – able to answer them all?
8 National Instruments SQL Interview Questions
SQL Question 1: Analyzing High-Value ("Power") Customers
National Instruments wants to identify its high-value customers ("power customers"). A power customer is defined as one who has purchased at least $50,000 worth of products in total based on the total transaction value. Write a SQL query to identify these users.
Example Input:
| user_id | user_name |
|---|---|
| 101 | John Doe |
| 102 | Jane Smith |
| 103 | Charlie Brown |
Example Input:
| order_id | user_id | product_id | qty | unit_price |
|---|---|---|---|---|
| 201 | 101 | 501 | 10 | 4000 |
| 202 | 101 | 502 | 15 | 100 |
| 203 | 102 | 501 | 5 | 4000 |
| 204 | 102 | 502 | 25 | 100 |
| 205 | 103 | 501 | 20 | 4000 |
Example Output:
| user_id | user_name | total_spent |
|---|---|---|
| 101 | John Doe | 50000 |
| 103 | Charlie Brown | 80000 |
Answer:
This query first joins the 'customer' and 'orders' tables on the 'user_id' field. It then groups the resulting rows by 'user_id' and 'user_name', effectively grouping by unique user. It calculates the total dollar amount that each user has spent by multiplying the quantity of each product purchased ('qty') by the unit price of the product ('unit_price'), and then summing these values over each group. It only includes rows where this sum is at least $50,000, identifying our 'power' customers.
To practice a related customer analytics question on DataLemur's free online SQL code editor, try this Microsoft SQL Interview problem:
SQL Question 2: Calculate Average Monthly Sales per Product
National Instruments wants to keep a track on how well its products are performing on a monthly basis. As part of this task, you have been provided with a dataset that contains information about the sales of different products every month.
Your task is to write a SQL query to calculate the average units sold per product each month.
For your convenience, here's some sample data:
Example Input:
| sale_id | product_id | product_name | sale_date | units_sold |
|---|---|---|---|---|
| 1001 | 2001 | "Product A" | 01/02/2022 | 125 |
| 1002 | 2002 | "Product B" | 01/15/2022 | 100 |
| 1003 | 2002 | "Product B" | 02/11/2022 | 95 |
| 1004 | 2001 | "Product A" | 02/25/2022 | 130 |
| 1005 | 2001 | "Product A" | 02/28/2022 | 150 |
| 1006 | 2002 | "Product B" | 03/07/2022 | 80 |
Example Output:
| month | product_id | product_name | average_units_sold |
|---|---|---|---|
| 1 | 2001 | "Product A" | 125.00 |
| 1 | 2002 | "Product B" | 100.00 |
| 2 | 2001 | "Product A" | 140.00 |
| 2 | 2002 | "Product B" | 95.00 |
| 3 | 2002 | "Product B" | 80.00 |
Answer:
The PostgreSQL query that solves this issue would be something like this:
This SQL query first extracts the month from the column using the function. Then it groups the data by , , and . Finally, it calculates the average for each group. The clause is used to sort the results by and .
For more window function practice, try this Uber SQL Interview Question within DataLemur's interactive coding environment:
SQL Question 3: What's a self-join, and when would you use one?
A self-join is a type of join in which a table is joined to itself. To perform a self-join, you need to specify the table name twice in the FROM clause, and give each instance of the table a different alias. You can then join the two instances of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.
Self-joins are the go-to technique for any data analysis that involves pairs of the same thing, like identifying pairs of products that are frequently purchased together like in this Walmart SQL interview question.
For another example, say you were doing an HR analytics project and needed to analyze how much all National Instruments employees in the same department interact with each other. Here's a self-join query you could use to retrieve all pairs of National Instruments employees who work in the same department:
This query returns all pairs of National Instruments employees who work in the same department, and excludes pairs where the employee's id is the same (since this would represent the same National Instruments employee being paired with themselves).
SQL Question 4: Average Use Time of Instruments
National Instruments designs, manufactures, and sells engineers and scientists a wide variety of products such as data acquisition devices, RF and communications devices, and industrial IoT systems. One of the many metrics National Instruments might be interested in is the average usage time of their devices.
Given a table that records every time a device is used, can you write a query to find the average usage time (in hours) of each device?
Example Input:
| usage_id | device_id | start_time | end_time |
|---|---|---|---|
| 1 | A1 | 2022-06-08 09:00:00 | 2022-06-08 11:30:00 |
| 2 | B2 | 2022-06-09 10:00:00 | 2022-06-09 12:45:00 |
| 3 | A1 | 2022-06-10 08:00:00 | 2022-06-10 11:45:00 |
| 4 | C3 | 2022-06-11 11:00:00 | 2022-06-11 14:30:00 |
| 5 | B2 | 2022-06-12 10:00:00 | 2022-06-12 13:25:00 |
Example Output:
| device_id | avg_usage_hours |
|---|---|
| A1 | 3.12 |
| B2 | 3.35 |
| C3 | 3.50 |
Answer:
The command subtracts the start time from the end time for each usage, and then convert the interval to seconds. By dividing it by 3600 we get the duration in hours. The function is then used to calculate the average usage time for each device.
SQL Question 5: Why is normalizing a database helpful?
Normalization can reduce redundancy and improve performance and flexibility in a database.
By dividing larger tables into smaller, more specific ones linked by foreign keys, it is often possible to improve query speed. Note: it is not always the case that query speed will be improved due to costly nature of joins. Still, we think normalization is a good idea because it can also increase flexibility by making it easier to alter individual tables without affecting others, which can be useful for adapting National Instruments's database to ever-changing business needs.
SQL Question 6: Calculate Click-through Conversion Rates for Ads and Products
National Instruments wants to analyze the click-through conversions of their digital ads and products. Given the tables 'ad_clicks' and 'product_views', could you write a query that provides the click-through rates for each digital ad, and also the conversion rates from viewing a product to adding it to the cart?
Example Input:
| ad_id | user_id | click_date |
|---|---|---|
| 1101 | 222 | 07/25/2022 17:30:00 |
| 1202 | 345 | 07/25/2022 21:20:00 |
| 1333 | 174 | 07/26/2022 17:00:00 |
| 1101 | 222 | 07/28/2022 13:00:00 |
| 1202 | 563 | 07/28/2022 20:15:00 |
Example Input:
| view_id | user_id | view_date | product_id | added_to_cart |
|---|---|---|---|---|
| 2591 | 222 | 07/25/2022 17:45:00 | 60245 | True |
| 4932 | 566 | 07/26/2022 10:10:00 | 80543 | False |
| 7283 | 345 | 07/27/2022 11:00:00 | 60245 | True |
| 8324 | 972 | 07/28/2022 09:30:00 | 80543 | False |
| 3985 | 563 | 07/28/2022 20:30:00 | 60245 | True |
Answer:
The above query first aggregates ad clicks by ad_id and views by product_id while counting the number of cases where the product is added to the cart. Then it joins these two tables on ad_id and product_id and calculates the click-through conversion rate for each ad as the ratio of products added to the cart to total views, presented as a decimal rounded to 2 places.
To solve a related SQL problem on DataLemur's free online SQL code editor, try this SQL interview question asked by Facebook:
SQL Question 7: How do you identify duplicated data in a table?
One way to find duplicatesis to use a clause and then use to find groups
You could also use the operator:
SQL Question 8: Find Customer Data with Specific Email Domain
As a data analyst at National Instruments, you are asked to find and list all customers whose email addresses end with "@gmail.com". They might be eligible for a special marketing campaign that is strategically designed for Google mail users.
Consider the "customers" table maintained by the company as follows:
Example Input:
| customer_id | first_name | last_name | signup_date | |
|---|---|---|---|---|
| 001 | Jim | Hopkins | jim_hopkins@gmail.com | 2019/01/13 |
| 002 | Brad | Johnson | bradjohnson@yahoo.com | 2018/02/23 |
| 003 | Cindy | Kim | cindykim@gmail.com | 2020/06/12 |
| 004 | Oscar | Wilde | oscar_wilde@hotmail.com | 2018/07/26 |
| 005 | May | Liu | mayliu@gmail.com | 2019/08/01 |
Your task is to write a SQL query that identifies the required customers.
Answer:
This SQL query will select all columns for the rows in the "customers" table where the "email" field Ends with "@gmail.com". The percent symbol (%) in the LIKE clause is a wildcard character that matches any sequence of characters. In this case, it matches any email address that ends with "@gmail.com", regardless of what characters (if any) come before it.
Preparing For The National Instruments SQL Interview
The key to acing a National Instruments SQL interview is to practice, practice, and then practice some more!
Beyond just solving the earlier National Instruments SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Google, Microsoft and Silicon Valley startups.
Each interview question has hints to guide you, detailed solutions and crucially, there is an online SQL coding environment so you can instantly run your SQL query and have it graded.
To prep for the National Instruments SQL interview it is also helpful to solve SQL problems from other tech companies like:
However, if your SQL foundations are weak, forget about jumping right into solving questions – refresh your SQL knowledge with this free SQL tutorial.
This tutorial covers SQL topics like INTERCEPT/EXCEPT and creating pairs via SELF-JOINs – both of which come up often during National Instruments SQL assessments.
National Instruments Data Science Interview Tips
What Do National Instruments Data Science Interviews Cover?
Besides SQL interview questions, the other question categories tested in the National Instruments Data Science Interview are:
- Statistics & Probability Questions
- Python or R Programming Questions
- Product Data Science Interview Questions
- ML Modelling Questions
- Resume-Based Behavioral Questions
How To Prepare for National Instruments Data Science Interviews?
To prepare for National Instruments Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from tech companies like Netflix, Google, & Airbnb
- a crash course covering Stats, SQL & ML
- over 900+ reviews on Amazon & 4.5-star rating