11 Technoprobe SQL Interview Questions (Updated 2024)
Technoprobe LOVES to ask SQL questions during interviews for Data Science, Analytics, and & Data Engineering jobs. To help you practice for the Technoprobe SQL interview, we'll cover 11 Technoprobe SQL interview questions – can you answer each one?
11 Technoprobe SQL Interview Questions
SQL Question 1: Calculate Monthly Average Probe Test Score for Each Probe Station
Technoprobe is an industry-leading company in advanced probe cards solutions utilized in the testing of semiconductors. Let's suppose the company tests different types of probes on various probe stations and monitors the test score (higher the score, better the probe performance).
Each probe station tests different types of probes (identified by ) and returns a score on a daily basis. Your task is to write a SQL query to calculate the average monthly test score for each probe station.
Example Input:
| test_id | probe_id | test_date | station_id | score |
|---|---|---|---|---|
| 101 | P456 | 07/01/2022 00:00:00 | S001 | 85 |
| 102 | P123 | 07/02/2022 00:00:00 | S002 | 90 |
| 103 | P789 | 07/05/2022 00:00:00 | S001 | 80 |
| 104 | P123 | 07/07/2022 00:00:00 | S002 | 85 |
| 105 | P789 | 08/01/2022 00:00:00 | S003 | 75 |
| 106 | P789 | 08/01/2022 00:00:00 | S001 | 70 |
| 107 | P456 | 08/02/2022 00:00:00 | S003 | 80 |
| 108 | P789 | 08/05/2022 00:00:00 | S002 | 90 |
| 109 | P123 | 08/07/2022 00:00:00 | S001 | 85 |
Example Output:
| month | station | avg_score |
|---|---|---|
| 7 | S001 | 82.5 |
| 7 | S002 | 87.5 |
| 8 | S001 | 77.5 |
| 8 | S002 | 90 |
| 8 | S003 | 77.5 |
Answer:
This query extracts the month from in table and groups by and . For each grouping, it calculates the average using the AVG SQL function.
For more window function practice, solve this Uber SQL Interview Question within DataLemur's online SQL code editor:
SQL Question 2: Asset Management in Technoprobe
Technoprobe, a firm specializing in advanced probe card solutions, has a trove of assets ranging from sensitive machinery, lab equipment, to consumable materials. To effectively manage these assets, a database system is put in place with details about each asset along with their acquisition dates and depreciation values. This database also keeps track of different departments that are using those assets.
The issue at hand is to write a SQL query that can summarize the total worth of assets each department is currently holding, based on their present value (original cost - depreciation).
The assets table has the following information:
Example Input:
| asset_id | asset_name | acquisition_date | original_cost | depreciation |
|---|---|---|---|---|
| 101 | Probe Card 1 | 2018-03-15 | 12000 | 2400 |
| 102 | Lab Equipment A | 2019-05-22 | 8500 | 1700 |
| 103 | Probe Card 2 | 2017-07-10 | 15000 | 3000 |
| 104 | Consumable Material X | 2020-01-07 | 3000 | 600 |
| 105 | Lab Equipment B | 2018-11-25 | 10000 | 2000 |
The departments table has the following information:
Example Input:
| department_id | department_name | asset_id |
|---|---|---|
| 1 | Engineering | 101 |
| 2 | Quality Control | 102 |
| 3 | Production | 103 |
| 3 | Production | 104 |
| 1 | Engineering | 105 |
Answer:
This SQL query joins the 'assets' table and the 'departments' table on 'asset_id', and groups the joined items by 'department_name'. The 'total_asset_value' is calculated as the sum of differences between the original cost and the depreciation value for each department. This gives us the total present value of assets held by each department.
SQL Question 3: How does differ from just ?
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 Technoprobe working on a Marketing Analytics project. If you needed to get the combined result set of both Technoprobe'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 4: Filtering Customer Records
As a database manager at Technoprobe, you are requested to pull up specific customer records based on certain conditions. The required data should meet the following conditions:
- Customers who are located in 'San Jose'.
- The customers' registration date is before '01-01-2021'.
- Customers either have a premium subscription or their total purchase amount is greater than 1000.
Here's the database table that you will be dealing with:
Sample Input:
| customer_id | name | city | RegistrationDate | is_premium | total_purchases |
|---|---|---|---|---|---|
| 1 | John Smith | San Jose | 12/12/2020 | False | 1200 |
| 2 | Jane Doe | New York | 05/05/2021 | True | 900 |
| 3 | Emily Rose | San Jose | 01/12/2020 | False | 800 |
| 4 | Michael Johnson | San Jose | 02/02/2022 | False | 1500 |
| 5 | Jennifer Williams | Los Angeles | 11/11/2019 | True | 3000 |
Write a SQL query to filter out the requested data.
Answer:
This query filters the customers table where the customers are from San Jose, registered before '01-01-2021', and they are either premium customers or their total purchases exceed 1000. The SQL commands , , are used to filter the required information based on the conditions given.
SQL Question 5: What does the keyword do?
The clause in SQL allows you to select records that are unique, eliminating duplicates.
For example, if you had a table of Technoprobe employees, and wanted to see what are all the unique job titles that currently worked at the company, you could write the following query:
SQL Question 6: Calculating Average Production Time
Technoprobe is a company that designs and manufactures high end microelectronic probes for various applications. An important performance indicator of their operations is the average production time of their probes. The management wants to know the average production time for each type of probe it produced in each month of the year.
You need to calculate this average production time from a table that tracks the production details, including the start and end dates of the production of each individual probe.
Example Input:
| prod_id | type | start_date | end_date |
|---|---|---|---|
| 1001 | A | 03/01/2022 | 03/05/2022 |
| 1002 | A | 03/02/2022 | 03/06/2022 |
| 1003 | B | 03/15/2022 | 03/19/2022 |
| 1004 | A | 04/02/2022 | 04/06/2022 |
| 1005 | B | 04/10/2022 | 04/15/2022 |
Answer:
In this query, we start by extracting the month from the and grouping by both this month and the probe . The average production time is then computed by calculating the difference between the and , and using the function on these differences. The resulting dataset should then give you the average production time for each type of probe for each month.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating averages per month or this McKinsey 3-Topping Pizzas Question which is similar for production-related calculations.
SQL Question 7: Can you describe the meaning of database normalization in layman's terms?
Normalizing a database involves dividing a large table into smaller and more specialized ones, and establishing relationships between them using foreign keys. This reduces repetition, resulting in a database that is more adaptable, scalable, and easy to maintain. Additionally, it helps to preserve the accuracy of the data by reducing the likelihood of inconsistencies and problems.
SQL Question 8: Filter Customer Records with Specific Pattern
At Technoprobe, we deal with many customers from not only local regions, but also from around the world. Our customer names usually have prefixes indicating their origin, such as 'US-', 'CAN-', 'UK-', etc., before the actual name. For this task, we want to filter all customer records where customers are from the UK. Could you write an SQL query to fetch all customer records with names starting with 'UK-'?
For this task, we will use the following Customers table:
Example Input:
| customer_id | name | join_date | order_count | total_spent |
|---|---|---|---|---|
| 123 | US-John | 12/05/2018 | 10 | $1,000 |
| 234 | CAN-Susan | 06/25/2019 | 15 | $2,300 |
| 345 | UK-George | 09/18/2016 | 20 | $3,450 |
| 456 | US-Mary | 05/31/2020 | 8 | $825 |
| 567 | UK-William | 01/07/2019 | 12 | $1,590 |
Please find all customers from the UK in the Customers table.
Answer:
This query uses the LIKE keyword to filter rows where the name column starts with 'UK-'. Thus, it returns all customer records from the UK.
SQL Question 9: Analyze Customer Purchases
As part of the Business Analysis team at Technoprobe, you are asked to inspect the customer transaction data. The company wants to determine the total amount spent by each customer. The database has a 'customers' table listing customer information and a 'purchases' table recording all transactions.
- Customers Table:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 1 | John | Doe | john.doe@mail.com |
| 2 | Jane | Smith | jane.smith@mail.com |
| 3 | Emma | Jones | emma.jones@mail.com |
- Purchases Table:
| purchase_id | customer_id | product_id | amount_spent |
|---|---|---|---|
| 101 | 1 | 401 | 150.00 |
| 102 | 2 | 323 | 175.00 |
| 103 | 1 | 401 | 150.00 |
| 104 | 3 | 277 | 200.00 |
| 105 | 2 | 401 | 150.00 |
Produce a query that provides the total amount each customer spent, listed by the customer's id, first name, and last name.
Answer:
In this query, we join the 'customers' and 'purchases' tables on since it's the common column linking customers with their purchases. After joining, we use the function to calculate the total amount spent per customer. We group by , and so that we have the amount spent shown for each specific customer.
Since joins come up so often during SQL interviews, practice an interactive Spotify JOIN SQL question:
SQL Question 10: Can you describe the concept of database denormalization in layman's terms?
Denormalization is the practice of altering a database schema in a way that breaks the normalization rules (1st, 2nd, 3rd normal forms).
Denormalization is done to improve the performance of the database when it is being used for online analytics processing (OLAP), rather than online transaction processing (OLTP) use cases.
For these OLAP use cases, you're bottleneck frequently is joining multiple tables, but de-normalizing your database cuts these outs.
Denormalization can improve query performance by reducing the number of expensive joins required to retrieve data, but it comes with its own drawbacks too. By adding redundant columns, you incur more data storage costs, and there's need for more complex update and delete operations in order to maintain data integrity across all the duplicated data. Thus, it's important to carefully consider the trade-offs involved before implementing denormalization.
SQL Question 11: Calculation of Sales Metrics
Technoprobe, being a technology company, has a product portfolio comprises of multiple items. Each product has a varying unit price and products are sold in varying quantities. A common task would be to calculate the total revenue generated from each product for a given month, and to determine the month-over-month growth rate in terms of revenue. The growth rate should be rounded to two decimal places for clarity.
Let's assume we have the following sales data for Technoprobe:
Example Input:
| sales_id | product_id | quantity | unit_price | sales_date |
|---|---|---|---|---|
| 1 | 101 | 4 | $300.00 | 08/01/2022 |
| 2 | 102 | 3 | $150.00 | 08/10/2022 |
| 3 | 101 | 5 | $300.00 | 08/25/2022 |
| 4 | 103 | 2 | $400.00 | 08/30/2022 |
| 5 | 101 | 3 | $300.00 | 09/05/2022 |
| 6 | 102 | 7 | $150.00 | 09/15/2022 |
| 7 | 103 | 1 | $400.00 | 09/20/2022 |
Answer:
This query works by first aggregating sales data by month and product to calculate the monthly revenue ( CTE). Then, it calculates the month-over-month growth rate by computing ((current_month_revenue - previous_month_revenue) / previous_month_revenue ) * 100 ( CTE).
Please note that we use PostgreSQL's to extract the month part from sales_date which is a timestamp in our example data. We also use the function to round off the growth rate to two decimal places. The inside the CTE does the total monthly product revenue calculation. The whole query results in a table with month, product_id, and the growth rate from the previous month for each product.
To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating growth rate of sales or this Amazon Highest-Grossing Items Question which is similar for identifying highest-grossing products.
Preparing For The Technoprobe SQL Interview
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews.
In addition to solving the earlier Technoprobe 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, fully explained answers along with a discussion board to see how others solved it and most importantly, there is an online SQL code editor so you can instantly run your SQL query answer and have it graded.
To prep for the Technoprobe SQL interview you can also be helpful to solve interview questions from other tech companies like:
However, if your SQL query skills are weak, forget about diving straight into solving questions – improve your SQL foundations with this SQL tutorial for Data Scientists & Analysts.
This tutorial covers things like sorting data with ORDER BY and CASE/WHEN/ELSE statements – both of these pop up frequently in SQL interviews at Technoprobe.
Technoprobe Data Science Interview Tips
What Do Technoprobe Data Science Interviews Cover?
In addition to SQL interview questions, the other types of questions tested in the Technoprobe Data Science Interview are:
- Statistics Interview Questions
- Coding Questions in Python or R
- Product-Sense Questions
- Machine Learning Questions
- Behavioral Based Interview Questions
How To Prepare for Technoprobe Data Science Interviews?
To prepare for Technoprobe Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions taken from companies like Microsoft, Google & Amazon
- a crash course covering Python, SQL & ML
- over 900+ 5-star reviews on Amazon