8 Keysight SQL Interview Questions (Updated 2024)
At Keysight Technologies, SQL does the heavy lifting for analyzing sales & marketing data for it's electronics products. Keysight also supports exporting data from it's scope's into databases. Unsurprisingly this is why Keysight frequently asks SQL query questions in interviews for Data Science, Analytics, and & Data Engineering jobs.
So, to help you study for the Keysight SQL interview, here’s 8 Keysight Technologies SQL interview questions – can you solve them?
8 Keysight Technologies SQL Interview Questions
SQL Question 1: Compute the Daily Average Rating for Each Product
Keysight Technologies is an electronic measurement company that requires regular feedback from their customers in the form of product reviews. The reviews are stored in a database where each review has a product ID, a user ID, a submitted date, and a star rating.
You have been given access to this data and are required to write a SQL query that computes the daily average rating for each product in Keysight's product catalog. The daily average rating is computed by taking the average of all the star ratings given to a product on each day.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-06-08 | 50001 | 4 |
| 7802 | 265 | 2022-06-10 | 69852 | 4 |
| 5293 | 362 | 2022-06-08 | 50001 | 3 |
| 6352 | 192 | 2022-07-26 | 69852 | 3 |
| 4517 | 981 | 2022-07-05 | 69852 | 2 |
Example Output:
| date | product | avg_stars |
|---|---|---|
| 2022-06-08 | 50001 | 3.5 |
| 2022-06-10 | 69852 | 4.0 |
| 2022-07-26 | 69852 | 3.0 |
| 2022-07-05 | 69852 | 2.0 |
Answer:
This SQL query calculates the daily average star rating for each product by grouping the reviews by the submit date and the product id using the clause. It then computes the average star rating for each group using the function. The results are sorted by the submit date and the product id in ascending order.
To practice another window function question on DataLemur's free interactive coding environment, solve this Google SQL Interview Question:
SQL Question 2: Average Duration of Equipment Usage
As a technician at Keysight, a leading electronic measurement company, you are responsible for regularly maintaining various pieces of complicated machinery. To better understand the equipment's wear and tear, find the average usage duration of each piece of equipment.
Example Input:
| log_id | equipment_id | start_time | end_time |
|---|---|---|---|
| 1105 | E101 | 2022-09-01 08:00:00 | 2022-09-01 12:00:00 |
| 2143 | E102 | 2022-09-01 09:30:00 | 2022-09-01 17:30:00 |
| 3264 | E101 | 2022-09-02 08:00:00 | 2022-09-02 18:00:00 |
| 4375 | E103 | 2022-09-02 10:00:00 | 2022-09-02 16:00:00 |
| 5101 | E102 | 2022-09-03 09:00:00 | 2022-09-03 17:00:00 |
Answer:
In the query above, we first calculate the usage duration of each log entry in hours by subtracting the from and using to convert the interval to seconds, and then divide by 3600 to convert seconds to hours. We then use the function to find the average usage duration for each .
The two most similar questions to your use case of finding the average usage duration of each piece of equipment are "Server Utilization Time" from Amazon and "Unfinished Parts" from Tesla. The similarity lies in the calculation and comparison of time-based data.
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for using similar concepts in the calculation of time-based data or this Tesla Unfinished Parts Question which is similar for providing insights into parts or equipments usage based on timestamps.
SQL Question 3: Can you provide an example of two entities that have a one-to-one relationship, and another example of a one-to-many relationship?
In database schema design, a one-to-one relationship is when each entity is associated with only one instance of the other. For instance, a US citizen's relationship with their social-security number (SSN) is one-to-one because each citizen can only have one SSN, and each SSN belongs to one person.
A one-to-many relationship, on the other hand, is when one entity can be associated with multiple instances of the other entity. An example of this is the relationship between a person and their email addresses - one person can have multiple email addresses, but each email address only belongs to one person.
SQL Question 4: Calculate the Click-Through Rates for different products
Keysight is a company that delivers numerous digital products. They are interested in understanding their users' behavior in terms of the proportion of users viewing a product page and subsequently adding the product to their shopping cart. Your task is to determine the click-through conversion rates from viewing a page to adding a product to the cart for various products.
We have two tables: and . The table saves each instance when a user views a product's specifications. The table, on the other hand, records every instance where a user adds a product to their shopping cart.
Example Input:
| view_id | user_id | view_date | product_id |
|---|---|---|---|
| 1063 | 401 | 2022-06-08 | 19 |
| 2084 | 425 | 2022-06-10 | 23 |
| 3155 | 331 | 2022-06-18 | 12 |
| 4065 | 215 | 2022-07-26 | 19 |
| 5293 | 736 | 2022-07-05 | 23 |
Example Input:
| add_id | user_id | add_date | product_id |
|---|---|---|---|
| 5512 | 391 | 2022-06-09 | 19 |
| 6721 | 431 | 2022-06-10 | 23 |
| 7642 | 361 | 2022-06-19 | 12 |
| 8517 | 222 | 2022-07-26 | 19 |
| 9122 | 741 | 2022-07-06 | 23 |
Example Output:
| product_id | ctr |
|---|---|
| 12 | 66.67 |
| 19 | 50.00 |
| 23 | 100.00 |
Answer:
This SQL query joins and tables on and to derive the number of users who viewed and also added a particular product to their cart. This is then divided by the total number of users who viewed that product to derive the click-through rate. Using a LEFT JOIN ensures we still consider products that were viewed and not added to the cart. For each product, we show the click-through rate (ctr in %) rounded to two decimal places.
To solve a similar SQL problem on DataLemur's free interactive coding environment, attempt this SQL interview question asked by Facebook:
SQL Question 5: What's the difference between and ?
The operator merges the output of two or more statements into a single result set. It ignores duplicated rows, and makes sure each row in the result set is unique.
For a concrete example, say you were a Data Analyst at Keysight working on a Marketing Analytics project. If you needed to get the combined result set of both Keysight's Google and Facebook ads you could execute this SQL query:
The operator works in a similar way to combine data from multiple statements, but it differs from the operator when it comes to handling duplicate rows. Whereas filters out duplicates (so if the same ad_name is run on both Facebook and Google, it only shows up once), outputs duplicate rows.
SQL Question 6: Joining and Analyzing Customer and Orders Data
You are given two tables: and . The table contains details about each customer including their , , and . The table contains details about each order including , , , and .
The question is: Write a SQL query to find the total amount spent by each customer along with their details. Exclude the customers who have not made any orders.
Customers Example Input
| customer_id | first_name | last_name | |
|---|---|---|---|
| 23 | John | Doe | johndoe@gmail.com |
| 56 | Jane | Doe | janedoe@gmail.com |
| 78 | Sara | Smith | sarasmith@gmail.com |
| 35 | Peter | Parker | peterparker@gmail.com |
Orders Example Input
| order_id | customer_id | product_name | order_date | price |
|---|---|---|---|---|
| 1 | 23 | Product A | 08/25/2022 | 20 |
| 2 | 56 | Product B | 08/26/2022 | 50 |
| 3 | 23 | Product C | 08/27/2022 | 30 |
| 4 | 56 | Product A | 08/28/2022 | 20 |
Example Output
| customer_id | first_name | last_name | total_spent | |
|---|---|---|---|---|
| 23 | John | Doe | johndoe@gmail.com | 50 |
| 56 | Jane | Doe | janedoe@gmail.com | 70 |
Answer
This query works by joining the two tables on the . It then groups the result by . The aggregate function is used to compute the total amount spent by each customer. The clause ensures that only customers who have made at least one order (and therefore have a total spend greater than 0) are included in the result.
Since joins come up so often during SQL interviews, try an interactive SQL join question from Spotify:
SQL Question 7: In SQL, Are NULL values the same as a zero or blank space?
{#Question-7}
In SQL, zero's are numerical values which can be used in calculations and comparisons just like any other number. A blank space, also known as an empty string, is a character value and can be used in character manipulation functions and comparisons.
NULLs aren't the same as zero's or blank spaces. NULLs represent unkonwn, missing, or not applicable values. They are not included in calculations and comparisons involving NULL values always result in NULL.
SQL Question 8: Calculate power consumption
Given a table for Keysight company's machines with columns , , and which is the amount of power consumed per hour in watts. Each machine can operate for multiple hours. A second table has columns , , , and . We want to analyze the machine power consumption.
Calculate the total power consumption per machine, round off to the nearest whole number and order the result set by total power consumption in descending order.
Example Input:
| machine_id | operation_hours | power_consumption_per_hour |
|---|---|---|
| 101 | 8 | 2.5 |
| 102 | 4 | 3.2 |
| 103 | 10 | 1.8 |
Example Input:
| id | machine_id | operation_start | operation_end |
|---|---|---|---|
| 1 | 101 | 06/08/2022 00:00:00 | 06/08/2022 08:00:00 |
| 2 | 102 | 06/10/2022 10:00:00 | 06/10/2022 14:00:00 |
| 3 | 103 | 06/18/2022 00:00:00 | 06/17/2022 10:00:00 |
| 4 | 101 | 07/26/2022 00:00:00 | 07/26/2022 08:00:00 |
Expected Output:
| machine_id | total_power_consumption |
|---|---|
| 101 | 40 |
| 103 | 36 |
| 102 | 13 |
Answer:
The query can be written as follows (assuming and are of data type):
In the query, we're joining the and tables using the column. Then we calculate the time difference between operation start and end time using to resulting hours.
This time difference in hours is then multiplied by the power consumption per hour to get the total power consumed, which is then rounded off using the function.
We group the results by to calculate total power consumption for each machine. The result is ordered by total power consumption in descending order.
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating total operation times> or this Twitter Tweets' Rolling Averages Question which is similar for aggregating over time-bound data.
Preparing For The Keysight SQL Interview
The key to acing a Keysight SQL interview is to practice, practice, and then practice some more!
Beyond just solving the above Keysight SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like FAANG tech companies and tech startups.
Each exercise has hints to guide you, full answers and crucially, there is an online SQL code editor so you can right online code up your SQL query and have it graded.
To prep for the Keysight SQL interview it is also useful to practice SQL problems from other tech companies like:
However, if your SQL coding skills are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this SQL interview tutorial.
This tutorial covers things like handling date/timestamp data and creating pairs via SELF-JOINs – both of these come up frequently in Keysight SQL assessments.
Keysight Technologies Data Science Interview Tips
What Do Keysight Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories covered in the Keysight Data Science Interview are:
- Statistics Interview Questions
- Python or R Programming Questions
- Product Data Science Interview Questions
- ML Modelling Questions
- Behavioral Based Interview Questions
How To Prepare for Keysight Data Science Interviews?
To prepare for Keysight Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from Google, Microsoft & tech startups
- a refresher covering SQL, Product-Sense & ML
- over 900+ reviews on Amazon & 4.5-star rating