9 PDF Solutions SQL Interview Questions (Updated 2024)
Data Analysts & Data Scientists at PDF Solutions code up SQL queries almost every single workday. They use SQL for analyzing semiconductor manufacturing data and optimizing solutions for yield improvement. Because of this, PDF Solutions typically asks folks interviewing for data jobs SQL coding interview questions.
As such, to help you study for the PDF Solutions SQL interview, here’s 9 PDF Solutions SQL interview questions in this article.
9 PDF Solutions SQL Interview Questions
SQL Question 1: Identify Frequent PDF Converters
As a part of PDF Solutions, you are asked to analyze the users' conversion data. Your task is to identify power users, or VIP users - those who convert multiple documents to PDF very frequently.
The 'conversions' table logs all the conversions made by users. Each row records a single conversion event and keeps track of the 'user_id', the 'conversion_date', and the 'document_type' that was converted to PDF.
Your task is to write a SQL query that selects the user_id's of those who converted documents to PDF more than 50 times in the month of August 2021.
Example Input:
| conversion_id | user_id | conversion_date | document_type |
|---|---|---|---|
| 1 | 1001 | 08/05/2021 00:00:00 | docx |
| 2 | 1010 | 08/10/2021 00:00:00 | xlsx |
| 3 | 1030 | 08/15/2021 00:00:00 | docx |
| 4 | 1001 | 08/20/2021 00:00:00 | docx |
| 5 | 1001 | 08/25/2021 00:00:00 | pptx |
Answer:
The query starts by selecting the 'user_id' from the conversions table where the 'conversion_date' was in August 2021. This is achieved by truncating the 'conversion_date' to the month level and comparing it to '2021-08-01'.
Then, we group by 'user_id' because we want a count of conversions for each individual user.
The 'HAVING' clause then filters out only those users who have done more than 50 conversions, which essentially gives us the list of power users for the month of August 2021.
To practice a similar VIP customer analysis question on DataLemur's free interactive SQL code editor, try this Microsoft SQL Interview problem:
SQL Question 2: Department vs. Company Salary
You're given a table of PDF Solutions employee and department salaries. Write a SQL query to find departments where the departments average salary is higher than the company's average salary.
Try this problem interactively on DataLemur:
The answer is LONG – 30+ lines of SQL. You can find a step-by-step solution with hints here: Department Salaries.
SQL Question 3: What sets a cross join apart from a natural join?
A cross join is a type of JOIN operation in SQL that creates a new table by combining each row from the first table with every row from the second table. It is also known as a cartesian join.
For example, say you worked on the Marketing Analytics team at PDF Solutions, and needed to understand what advertising copy (text) goes best with what advertising creative (the photo that gets posted with the advertisement copy).
Here is an example of a cross-join between a table of ad_copy and a table of ad_creative:
A natural join, on the other hand, is a type of JOIN that combines rows from two or more tables based on their common columns. It is called a "natural" join because it is based on the natural relationship that exists between the common columns in the tables being joined.
For an example of each one, say you had sales data exported from PDF Solutions's Salesforce CRM stored in a datawarehouse which had two tables: and .
An (which is a type of natural join) combines the two tables on the common
This query will return rows from the sales and tables that have matching customer id values. Only rows with matching values will be included in the results.
One main difference between cross joins and natural joins is that cross joins do not require any common columns between the tables being joined, while natural joins do. Another difference is that cross joins can create very large tables if the input tables have a large number of rows, while natural joins will only return a table with the number of rows equal to the number of matching rows in the input tables.
SQL Question 4: Calculate the Monthly Average Rating of Each Product
You are a Data Analyst at PDF Solutions and your manager wants to understand how well our products are performing each month based on customer reviews. You have been given a table containing review data for the past few months. The reviews table, , has the following schema:
- (integer): unique identifier of the review
- (integer): unique identifier of the user who posted the review
- (date): date when the review was submitted
- (integer): unique identifier of the product
- (integer): rating of the product (1 to 5)
Write a SQL query that calculates the monthly average rating (stars) for each product. The result should include the month, product_id, and the average rating for that month. Round the average rating to two decimal places.
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 | 2022-06-18 | 50001 | 3 |
| 6352 | 192 | 2022-07-26 | 69852 | 3 |
| 4517 | 981 | 2022-07-05 | 69852 | 2 |
Answer:
This query first uses the function to truncate the to the closest month. The function calculates the average rating per product per month, and function is used to limit the precision to two decimal places. The results are grouped by month and product_id, and sorted in ascending order by month.
Example Output
| month | product_id | average_rating |
|---|---|---|
| 2022-06-01 00:00:00 | 50001 | 3.50 |
| 2022-06-01 00:00:00 | 69852 | 4.00 |
| 2022-07-01 00:00:00 | 69852 | 2.50 |
p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: What's the purpose of the the command?
combines the results from two or more SELECT statements, but only returns the rows that are exactly the same between the two sets.
For example, say you were doing an HR Analytics project for PDF Solutions, and had access to PDF Solutions'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 employees who also show up in the contractors table:
SQL Question 6: Calculate the most profitable product
For PDF Solutions, a company that specializes in integrated circuit engineering and related services, the management board wants to identify which products bring the most profit. They want to consider only those products that have been sold in the last three months and customers' total purchase amount for each product should be over $50000.
Here's an example of the customer purchase records.
Example Input:
| sale_id | customer_id | sale_date | product_id | unit_price | quantity |
|---|---|---|---|---|---|
| 1 | 105 | 01/01/2023 | 101 | 200 | 50 |
| 2 | 205 | 01/05/2023 | 102 | 300 | 100 |
| 3 | 305 | 02/15/2023 | 101 | 200 | 300 |
| 4 | 105 | 03/03/2023 | 103 | 500 | 30 |
| 5 | 405 | 03/10/2023 | 104 | 600 | 80 |
| 6 | 505 | 03/12/2023 | 101 | 200 | 100 |
We are looking for output that tells us the most profitable product and total sales of that product.
Example Output:
| most_profitable_product | total_sales |
|---|---|
| 101 | 140000 |
For solving the above problem, you can use the following SQL query:
Answer:
In the above query, we start with selecting the product id and total sales (calculated as unit price times quantity). We consider only sales that happened in the last three months. We use the GROUP BY clause to calculate total sales for each product. We filter out products with total sales less than $50000 using the HAVING clause. Finally, we order the result in descending order of total sales and only fetch the top row of the result using LIMIT 1. This gives us the most profitable product.
SQL Question 7: What is the purpose of the SQL constraint ?
{#Question-7}
A UNIQUE constraint ensures that all values in a column are different. This provides uniqueness for the column(s) and helps identify each row uniquely. Unlike primary key, there can be multiple unique constraints defined per table.
SQL Question 8: Calculate the Average Analysis Duration per Analyst in PDF Solutions
As a data analyst at PDF Solutions, you work along with a team of analysts who are responsible for monitoring various documents in a system. Your team is specifically tasked with analyzing different PDF files to ensure their quality and integrity. Every day, each analyst is assigned several PDF files for analysis.
Your manager is interested in finding out the average time each analyst spends analysing a PDF file. This information is vital for your manager as it helps in effectively allocating resources and identifying any opportunities for efficiency improvement.
Given a and tables with the following structure, write a PostgreSQL query that calculates the average analysis duration for each analyst.
Example Input:
| analyst_id | first_name | last_name |
|---|---|---|
| 1 | John | Doe |
| 2 | Jane | Smith |
| 3 | Sam | Brown |
Example Input:
| analysis_id | analyst_id | pdf_id | start_time | end_time |
|---|---|---|---|---|
| 101 | 1 | 5001 | 08/25/2022 09:00:00 | 08/25/2022 10:15:00 |
| 102 | 1 | 5002 | 08/25/2022 10:30:00 | 08/25/2022 11:45:00 |
| 103 | 2 | 5003 | 08/25/2022 09:15:00 | 08/25/2022 10:00:00 |
| 104 | 2 | 5004 | 08/25/2022 10:05:00 | 08/25/2022 11:00:00 |
| 105 | 3 | 5005 | 08/25/2022 09:00:00 | 08/25/2022 10:45:00 |
Answer:
This query will calculate the average duration that each analyst spends on analyzing a PDF. The duration of analysis is calculated as the difference between end_time and start_time for each analysis_id. This difference is extracted to minutes using EXTRACT and EPOCH functions. The AVG function is then used to compute the average duration spent by each analyst. The analysts are grouped by their first_name and last_name for this calculation.
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating total time aggregation or this Facebook Average Post Hiatus (Part 1) Question which is similar for determining time between activities.
SQL Question 9: Click-through Conversion Rates in PDF Solutions
PDF Solutions, a company specializing in developing software technologies that provide end-to-end design-to-silicon optimization for the manufacturing of integrated circuits, is analyzing the efficiency of their online product ads. They are interested in understanding the click-through conversion rate, i.e., the percent of users who viewed a product, clicked on the ad, and subsequently added the product to the shopping cart.
You're asked to calculate the click-through conversion rates for each product advertised in August 2022.
Here's a sample of the available data:
Example Input:
| click_id | user_id | click_date | product_id |
|---|---|---|---|
| 101 | 765 | 08/10/2022 10:00:00 | 5500 |
| 202 | 896 | 08/13/2022 12:05:00 | 6000 |
| 303 | 765 | 08/13/2022 14:00:00 | 5000 |
| 404 | 888 | 08/15/2022 18:10:00 | 7000 |
| 505 | 999 | 08/20/2022 22:00:00 | 8000 |
Example Input:
| cart_id | user_id | cart_date | product_id |
|---|---|---|---|
| 1001 | 765 | 08/10/2022 10:10:00 | 5500 |
| 2002 | 896 | 08/13/2022 12:15:00 | 6000 |
| 3003 | 765 | 08/20/2022 15:00:00 | 5000 |
| 4004 | 888 | 08/15/2022 18:20:00 | 6000 |
| 5005 | 999 | 08/20/2022 22:10:00 | 8000 |
Answer:
Based on the available data, your SQL query should look like this:
This SQL statement first creates a temporary table keeping the total clicked and converted (clicked and added to cart) for each product. It then calculates the conversion rate which is the percentage of click-through that resulted in a product being added to a cart. The statement is used to prevent division by zero.
To practice another question about calculating rates, try this TikTok SQL Interview Question on DataLemur's online SQL code editor:
PDF Solutions SQL Interview Tips
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 PDF Solutions SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like FAANG (FB, Apple, Amazon, Netflix, Google).
Each exercise has hints to guide you, fully explained answers along with a discussion board to see how others solved it and best of all, there's an online SQL coding environment so you can right in the browser run your SQL query and have it checked.
To prep for the PDF Solutions SQL interview it is also wise to solve SQL problems from other tech companies like:
However, if your SQL foundations are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this DataLemur SQL tutorial.
This tutorial covers topics including RANK vs. DENSE RANK and handling missing data (NULLs) – both of which show up routinely in PDF Solutions SQL interviews.
PDF Solutions Data Science Interview Tips
What Do PDF Solutions Data Science Interviews Cover?
Besides SQL interview questions, the other types of problems covered in the PDF Solutions Data Science Interview include:
- Statistics and Probability Questions
- Python or R Coding Questions
- Business Sense and Product-Sense Questions
- Machine Learning Questions
- Behavioral Based Interview Questions
How To Prepare for PDF Solutions Data Science Interviews?
I'm a bit biased, but I think the best way to study for PDF Solutions Data Science interviews is to read my book Ace the Data Science Interview.
The book solves 201 interview questions taken from tech companies like Netflix, Google, & Airbnb. It also has a crash course covering SQL, AB Testing & ML. And finally it's helped a TON of people, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.