8 Patterson SQL Interview Questions (Updated 2024)

Patterson employees write SQL queries to analyze sales data, enabling them to make smarter inventory decisions and ensure they have the right products on hand. They also use SQL to clean and organize dental supply chain information, making it easier to create predictive models that forecast demand, that is why Patterson asks SQL problems during interviews for Data Science, Data Engineering, and Data Analytics jobs.

So, to help you prep for the Patterson SQL interview, we'll cover 8 Patterson SQL interview questions – scroll down to start solving them!

8 Patterson SQL Interview Questions

SQL Question 1: Identify Top Customers by Purchase Volume and Frequency

Patterson is a company that sells a wide range of products. They are interested in identifying their top customers, often referred to as 'Whale Users'. These users are customers who have made the most purchases in terms of both volume and frequency.

To facilitate this, they store transaction data in a table where each row represents a unique transaction. The structure of the table is as follows:

Example Input:

Now, write a PostgreSQL query to find out the top 3 customers who have made the most purchases in terms of both volume and frequency over the past month (July 2022).

Answer:

This query first filters out only those transactions that were made in the month of July 2022. It performs a grouping operation by the and calculates two fields: which is the count of transactions per customer and which is the total quantity of products purchased by each customer. The result is then sorted by both volume and frequency in descending order such that customers who have made the most purchases in terms of volume and frequency appear at the top. Finally, is used to take only the top 3 customers.

To practice a similar VIP customer analysis question on DataLemur's free online SQL coding environment, try this Microsoft SQL Interview problem:

Visit Patterson's newsroom to discover their latest innovations and contributions to the dental and animal health industries! Learning about Patterson's initiatives can provide valuable insights into how they are shaping the future of healthcare services.

SQL Question 2: Department Salaries

You're given a table of Patterson employee and department salary information. Write a SQL query to find departments where the departments average salary is higher than the company's average salary.

Solve this question and run your code right in DataLemur's online SQL environment:

The answer is LONG – 30+ lines of SQL. You can find a detailed solution with hints here: Department vs. Company Salary.

SQL Question 3: How does the LEAD() function differ from the LAG() function?

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Both the and window functions are used to access a row at a specific offset from the current row.

However, the function retrieves a value from a row that follows the current row, whereas the function retrieves a value from a row that precedes the current row.

Say you had a table of salary data for Patterson employees:

You could use the function to output the salary of each employee, along with the next highest-paid employee:

This would yield the following output:

Swapping for would get you the salary of the person who made just more than you:

SQL Question 4: Compute rolling average of product reviews

Patterson is an E-commerce company that has a massive catalog of products across different categories. They keep track of each product review in a table, with an associated , (the date the review was submitted), , and the given by the user.

Your task is to write a SQL query that computes a rolling average of the review for each , over a window of the 3 most recent reviews. This would help Patterson get a better understanding of the recent performance of their products based on customer feedback.

Example Input:

Example Output:

Answer:

This query computes a rolling average of the field over a window of the 3 most recent reviews (), partitioned by the . It does so for each row in the table. The output is sorted by and to see the progression of each product's reviews clearly.

p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur

SQL Question 5: What's the purpose of the function in SQL?

The function allows you to select the first non-NULL value from a list of values. It is often used to replace a NULL value with a default value in order to run aggregate functions like or on a column without being affected by values.

For example, if you conducted a customer satisfaction survey for a company and asked customers to rate their level of agreement with a statement on a scale of 1 to 10, some customers may not have answered all the questions, resulting in NULL values in the survey data:

To replace the NULLs in the column with the default value of 5 which corresponds to neutral on the survey, you could run the following SQL query:

You'd get the following output:

SQL Question 6: Calculate click-through-conversion rate for a specific period

The marketing department of Patterson has decided to study the efficiency of their e-commerce platform. They want to examine the click-through-conversion rate for the month of July 2022. Click-through-conversion is defined as the number of users who added a product to the cart after viewing it over the total number of users who viewed the product. Specifically, they are interested in product number 815.

For this question, we need two tables:

Example Input:

Example Input:

Answer:

In this query, we first create two CTEs ( and ) to find the total number of views and adds for product 815 during the month of July, 2022 separately. We then divide the number of adds by the number of views to get the click-through-conversion rate. These calculations are kept separate for clarity and to reduce errors. It's important to note that this method might skew results if multiple views and cart additions from the same user are considered.

To solve a similar SQL problem on DataLemur's free online SQL coding environment, attempt this Facebook SQL Interview question:

SQL Question 7: In database normalization, what's the distinction between 1NF, 2NF, and 3NF?

Normalization is the process of dividing a larger table into smaller tables, to eliminate redundancy and dependency. Although there are 5 levels of normalization (normal forms), the 3 most important ones that you should know for the Patterson SQL interview are:

1. First Normal Form (1NF): Remove a table's duplicate columns, and make sure each value in the column is a singular value (no containers or lists of data). Each row of table should have a unique identifier as well.
2. Second Normal Form (2NF): A table is in 2NF if it meets all requirements of the 1NF the non-key columns are dependent only on the primary key. You do this by separating subsets of columns subsets, and associating the tables by using primary/foreign keys.
3. Third Normal Form (3NF): The table should be in 2NF and there shouldn't be any dependency on any non-key attributes (meaning a primary key should be the only thing needed to identify a row).

SQL Question 8: Finding Customers in a Specific City

Patterson Company wants you to retrieve all customer records where the address is like '%' + 'Texas' (meaning, all customers that are located in Texas). Use the "customers" table for this task. The table has several columns but you will primarily be working with:

• (integer): a unique identifier for the customer.
• (string): the first name of the customer.
• (string): the last name of the customer.
• (string): The customers' address.

Example Input:

Answer:

Here is the PostgreSQL query to solve the task:

Output:

The above SQL statement will select all records (rows) from the 'customers' table where the 'address' field contains the word 'Texas' — effectively returning all the customers located in Texas.

Patterson 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 Patterson SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Microsoft, Google, and Meta.

Each exercise has multiple hints, full answers and most importantly, there is an online SQL coding environment so you can right online code up your query and have it graded.

To prep for the Patterson SQL interview you can also be useful to practice interview questions from other healthcare and pharmaceutical companies like:

• Select Medical Holdings SQL questions
• Vertex Pharmaceuticals SQL questions
• Zoetis SQL questions
• Zimmer Biomet Holdings SQL questions

But if your SQL foundations are weak, forget about diving straight into solving questions – refresh your SQL knowledge with this SQL interview tutorial.

This tutorial covers topics including using ORDER BY and Subqueries – both of these pop up often during Patterson interviews.

Patterson Data Science Interview Tips

What Do Patterson Data Science Interviews Cover?

Besides SQL interview questions, the other types of questions to practice for the Patterson Data Science Interview are:

• Statistics & Probability Questions
• Python or R Coding Questions
• Product Data Science Interview Questions
• ML Interview Questions
• Behavioral Questions focussed on Patterson culture and values

How To Prepare for Patterson Data Science Interviews?

To prepare for Patterson 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 Stats, ML, & Data Case Studies
• over 1000+ reviews on Amazon & 4.5-star rating

Don't ignore the behavioral interview – prepare for it using this guide on behavioral interview questions.