9 Synopsys SQL Interview Questions (Updated 2024)
At Synopsys, SQL is used across the company for extracting and analyzing semiconductor design data, and building data models for software security solutions. That's why Synopsys LOVES to ask SQL problems in interviews for Data Analytics, Data Science, and Data Engineering jobs.
So, if you're stressed about an upcoming SQL Assessment, here’s 9 Synopsys SQL interview questions to practice, which are similar to recently asked questions at Synopsys – able to answer them all?
9 Synopsys SQL Interview Questions
SQL Question 1: Calculate the Monthly Average Rating of Synopsys Products
Synopsys is a company that designs and sells software, silicon structures, and services for the semiconductor industry. Let's assume that Synopsys has an online platform where users can leave product reviews. Your task is to write a SQL query that calculates the average rating for each product on a monthly basis.
The existing data inputted into the system is stored in the table, which contains the following columns:
: The unique identifier for each review.
: The unique identifier for each user.
: The date when the review was submitted.
: The unique identifier for each product.
: The star rating given by the user (between 1-5).
We want the output to include the following columns:
: The month when the review was submitted.
: The identifier for the product.
: The average star rating for the product in the given month.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 06/08/2022 00:00:00 | 50001 | 4 |
| 7802 | 265 | 06/10/2022 00:00:00 | 69852 | 4 |
| 5293 | 362 | 06/18/2022 00:00:00 | 50001 | 3 |
| 6352 | 192 | 07/26/2022 00:00:00 | 69852 | 3 |
| 4517 | 981 | 07/05/2022 00:00:00 | 69852 | 2 |
Example Output:
| mth | product_id | avg_stars |
|---|---|---|
| 6 | 50001 | 3.50 |
| 6 | 69852 | 4.00 |
| 7 | 69852 | 2.50 |
Answer:
The query uses the window function with a clause to calculate the average star rating for each product each month. The function is used to get the month from the column. The clause is used to order the result by the month and product id.
To solve a similar problem on DataLemur's free interactive SQL code editor, solve this Meta SQL interview question:
SQL Question 2: Design a Database for Software Versioning
As a software integrity company, Synopsys develops many software solutions. A considerable part of their business operation is ensuring they have an advanced version control system for tracking the changes in software applications, and they want to design a database to handle this.
This database will particularly have two tables: the table, which contains details about the software applications, and the table, which records all the versions related to a specific software in the table.
The table should have as its primary key, along with .
Example Input:
| software_id | software_name |
|---|---|
| 101 | Coverity |
| 102 | Black Duck |
The table should have the as its primary key, along with , and as a foreign key referencing in the table.
Example Input:
| version_id | version_number | release_date | software_id |
|---|---|---|---|
| 501 | 1.0 | 2022-01-01 | 101 |
| 502 | 2.0 | 2022-02-01 | 101 |
| 503 | 3.0 | 2022-03-01 | 101 |
| 504 | 1.0 | 2022-01-01 | 102 |
Using these two tables, we could tackle several questions that Synopsys might be interested in, such as extracting the latest version of each software.
Answer:
The example SQL would look as follows:
This SQL query first joins the and tables on the field. Then it selects the software_name, version_number, and release_date where the release_date is the maximum for each specific software_id, thus fetching the most recent version for each software.
NOTE: This is a simplified database design. More details would be needed (like author, change logs, etc.) in a real-world scenario.
To solve a related SQL problem on DataLemur's free online SQL coding environment, solve this SQL interview question asked by Facebook:
SQL Question 3: How can you identify duplicates in a table? Do have any other approaches?
"One creative way is to use the window function ROW_NUMBER() and partition by whichver columns you are loooking for duplicates in. If any row has a row_number() more than 1, then it's a duplicate!
You could also use COUNT(DISTINCT col1) vs. COUNT(*) and see if they return different numbers, indicating the prescence of duplicates!
SQL Question 4: Filter clients from the Synopsys database
Suppose you're a database manager at Synopsys, an electronic design automation (EDA) company that focuses on silicon design and verification, silicon intellectual property, and software security and quality.
It's your responsibility to provide journals on the company's database records based on several requirements. A single client could have purchased multiple Synopsys products and each product can have one or more subscription dates.
For a weekly report, you are asked to write a SQL query that returns all client records who purchased a specific product (let's say "HSPICE") after January 1, 2022 and are based either in Europe or Asia. Consider the clients table (), products table (), and the purchases table ().
Example Input:
| client_id | client_name | region |
|---|---|---|
| 1 | Acme Corp | Asia |
| 2 | Beta Inc | Europe |
| 3 | Gamma LLC | North America |
| 4 | Delta Ltd | Asia |
Example Input:
| product_id | product_name |
|---|---|
| 1 | HSPICE |
| 2 | Zebu Server |
| 3 | FPGA |
Example Input:
| purchase_id | client_id | product_id | purchase_date |
|---|---|---|---|
| 1 | 1 | 1 | 02/01/2022 |
| 2 | 2 | 2 | 01/15/2022 |
| 3 | 3 | 3 | 03/12/2022 |
| 4 | 1 | 3 | 02/28/2022 |
| 5 | 4 | 1 | 01/22/2022 |
Answer:
This SQL query will return all clients from either Europe or Asia who have purchased 'HSPICE' product after January 1, 2022. It joins the clients, products and purchases tables on their respective IDs, and then applies the filter conditions via the WHERE clause.
To practice another question about calculating rates, solve this TikTok SQL question on DataLemur's online SQL code editor:
SQL Question 5: What's the difference between a left and right join?
Both types of joins in SQL help you retrieve data from multiple tables and merge the results into a single table.
To demonstrate the difference between a left join versus a right join, imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.
A retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.
A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.
SQL Question 6: Click-Through-Rates For Different Software Products
As an analyst at Synopsys, a leading company in the Electronic Design Automation industry, you are tasked with analyzing the performance of different digital marketing campaigns for various software products. This analysis involves calculating the click-through rates and click-through conversion rates for each product.
The click-through rate (CTR) is the number of clicks on an ad divided by the number of times the ad is shown (impressions). The click-through conversion rate (CTCR) is the number of times a click on the ad leads to a conversion (adding a product to the cart) divided by total number of clicks.
Given the following tables:
Example Input:
| impression_id | product_id | impression_date |
|---|---|---|
| 1 | 101 | 2022-06-18 |
| 2 | 102 | 2022-06-19 |
| 3 | 101 | 2022-06-20 |
| 4 | 103 | 2022-06-21 |
| 5 | 102 | 2022-06-22 |
Example Input:
| click_id | impression_id | click_date |
|---|---|---|
| 1 | 1 | 2022-06-18 |
| 2 | 2 | 2022-06-19 |
| 3 | 3 | 2022-06-20 |
| 4 | 4 | 2022-06-21 |
| 5 | 3 | 2022-06-20 |
Example Input:
| conversion_id | click_id | conversion_date |
|---|---|---|
| 1 | 1 | 2022-06-18 |
| 2 | 2 | 2022-06-19 |
| 3 | 3 | 2022-06-20 |
| 4 | 5 | 2022-06-20 |
Write a SQL query to calculate the CTR and CTCR for each software product.
Answer:
This query first joins the impressions, clicks, and conversions tables. Then, it groups the result by product_id. For each product, it calculates the CTR as the number of distinct clicks divided by the number of impressions. It calculates the CTCR as the number of conversions divided by the number of clicks.
To practice a similar SQL interview question on DataLemur's free interactive SQL code editor, try this Meta SQL interview question:
SQL Question 7: How do you identify records in one table that are not present in a second table?
To discover records in one table that are not present in another, you can utilize a and filter out any values in the right-side table.
For example, say you had a table of Synopsys customers and a 2nd table of all purchases made with Synopsys. To find all customers who did not make a purchase, you'd use the following
This query fetches all rows from the customers table, along with any rows that match in the purchases table. If there is no matching row in the purchases table, values will be returned for all of the right table's columns. The clause then filters out any rows where the purchases.id column is NULL, leaving only customers who have not made a purchase.
SQL Question 8: Retrieve Customer Records Matching a Specific Email Pattern
As a data analyst for Synopsys, your task is to filter customers' records whose emails belong to the company's domain (i.e., email ends with '@synopsys.com').
For this task, the company has a table in their database that stores information about each customer.
Example Input:
| customer_id | first_name | last_name | creation_date | |
|---|---|---|---|---|
| 123 | John | Doe | johndoe@synopsys.com | 2020-01-01 00:00:00 |
| 124 | Jane | Doe | janedoe@gmail.com | 2020-02-01 00:00:00 |
| 125 | Jim | Beam | jimbeam@synopsys.com | 2020-03-01 00:00:00 |
| 126 | Jack | Daniels | jackdaniels@synopsys.com | 2020-04-01 00:00:00 |
| 127 | James | Bond | jamesbond@yahoo.com | 2020-05-01 00:00:00 |
Answer:
To accomplish this task, you would use the SQL LIKE keyword, which allows you to match a pattern in the WHERE part of your query.
This SQL command retrieves all fields () from customers whose email ends with '@synopsys.com'.
In SQL, the symbol is a wildcard character. By placing it before , it matches any string that ends with these characters, effectively filtering for customers with an email address that belongs to the Synopsys domain.
In the given example, the query would return the records for John Doe, Jim Beam, and Jack Daniels.
To solve a similar SQL problem on DataLemur's free interactive coding environment, solve this SQL interview question asked by Facebook:
SQL Question 9: Join Query Analysis on Customer and Product Database
Synopsys Inc has a customer database and a product database. Each customer in the customer database can purchase multiple products from the product database.
The database has columns: (unique id of the customer), (name of the customer), (email of the customer).
The database has columns: (unique id of the product), (name of the product), (price of the product).
A table tracks each purchase a customer makes, and it has columns: , , , and .
Write a PostgreSQL query to retrieve a list of customers along with their purchased product name and the date of purchase. Please, sort the result by .
Table Example:
| cust_id | name | |
|---|---|---|
| 001 | John | john@synopsys.com |
| 002 | Emma | emma@synopsys.com |
| 003 | Oliver | oliver@synopsys.com |
Table Example:
| product_id | product_name | product_price |
|---|---|---|
| 1001 | Product A | 100 |
| 1002 | Product B | 200 |
| 1003 | Product C | 300 |
Table Example:
| purchase_id | product_id | cust_id | purchase_date |
|---|---|---|---|
| 5001 | 1002 | 003 | 2022-06-15 |
| 5002 | 1001 | 002 | 2022-07-20 |
| 5003 | 1003 | 001 | 2022-07-25 |
Answer:
The SQL query will be:
In this query, we perform operations to combine the , , and tables based on the customer ID and product ID. The statement is used to retrieve the customer name, product name, and purchase date information. Finally, the clause is used to sort the results based on the purchase date.
To practice a related problem on DataLemur's free online SQL code editor, attempt this SQL interview question asked by Facebook:
How To Prepare for the Synopsys SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Synopsys SQL interview is to solve as many practice SQL interview questions as you can!
In addition to solving the above Synopsys SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Google, Uber, and Microsoft.
Each SQL question has multiple hints, full answers and crucially, there's an interactive SQL code editor so you can right online code up your SQL query and have it executed.
To prep for the Synopsys SQL interview it is also a great idea to practice SQL questions from other tech companies like:
However, if your SQL query skills are weak, don't worry about going right into solving questions – go learn SQL with this DataLemur SQL Tutorial.
This tutorial covers SQL topics like manipulating date/time data and finding NULLs – both of these pop up frequently in SQL interviews at Synopsys.
Synopsys Data Science Interview Tips
What Do Synopsys Data Science Interviews Cover?
For the Synopsys Data Science Interview, besides SQL questions, the other types of questions to practice:
- Statistics and Probability Questions
- Coding Questions in Python or R
- Product Analytics Questions
- ML Modelling Questions
- Behavioral Interview Questions
How To Prepare for Synopsys Data Science Interviews?
To prepare for Synopsys Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions taken from Facebook, Google, & Amazon
- a refresher on Stats, SQL & ML
- over 900+ reviews on Amazon & 4.5-star rating