10 PerkinElmer SQL Interview Questions (Updated 2024)
At PerkinElmer, SQL is used to analyze complex biological data sets, helping scientists and researchers uncover insights about health and disease patterns. They also rely on SQL to efficiently manage and query their large product and customer databases, ensuring they can quickly access the information needed to support their innovative solutions, this is why PerkinElmer ask SQL questions during interviews for Data Science, Data Engineering, and Data Analytics jobs.
To help you prepare for the PerkinElmer SQL interview, we'll cover 10 PerkinElmer SQL interview questions in this blog.
10 PerkinElmer SQL Interview Questions
SQL Question 1: Analyzing Product Performance
PerkinElmer, Inc. specializes in the business sector of human and environmental health. One of the areas they focus on is the production and distribution of medical and scientific equipment. For a given dataset named , write a SQL query that ranks each product based on its total sales for each year. Specifically, the query should return each product_id, the total sales per year, and the rank of the product for that year based on the sales.
Sample tables:
Example Input:
| sales_id | product_id | sales_year | sales_units |
|---|---|---|---|
| 1 | 1001 | 2020 | 250 |
| 2 | 1002 | 2020 | 300 |
| 3 | 1003 | 2020 | 350 |
| 4 | 1001 | 2021 | 400 |
| 5 | 1002 | 2021 | 450 |
| 6 | 1003 | 2021 | 500 |
Example Output:
| sales_year | product_id | total_sales | rank |
|---|---|---|---|
| 2020 | 1003 | 350 | 1 |
| 2020 | 1002 | 300 | 2 |
| 2020 | 1001 | 250 | 3 |
| 2021 | 1003 | 500 | 1 |
| 2021 | 1002 | 450 | 2 |
| 2021 | 1001 | 400 | 3 |
Answer:
According to this query, we first split the data by the using the clause. Afterwards, we order the result of each partition by the total sales in descending order and assign a rank using the window function. This helps us determine which products performed best in terms of units sold for each year. This query can be valuable in understanding which products are consistently successful or up-and-coming within the company's product lineup.
For more window function practice, try this Uber SQL Interview Question on DataLemur's online SQL coding environment:
Explore PerkinElmer's newsroom to discover their latest innovations and contributions to the life sciences sector! Gaining insights into PerkinElmer's initiatives will help you appreciate their role in advancing scientific research and healthcare solutions.
SQL Question 2: Top Department Salaries
Given a table of PerkinElmer employee salary data, write a SQL query to find the top 3 highest earning employees within each department.
PerkinElmer Example Input:
| employee_id | name | salary | department_id |
|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 |
| 2 | Daniel Rodriguez | 2230 | 1 |
| 3 | Olivia Smith | 2000 | 1 |
| 4 | Noah Johnson | 6800 | 2 |
| 5 | Sophia Martinez | 1750 | 1 |
| 8 | William Davis | 6800 | 2 |
| 10 | James Anderson | 4000 | 1 |
Example Input:
| department_id | department_name |
|---|---|
| 1 | Data Analytics |
| 2 | Data Science |
Example Output:
| department_name | name | salary |
|---|---|---|
| Data Analytics | James Anderson | 4000 |
| Data Analytics | Emma Thompson | 3800 |
| Data Analytics | Daniel Rodriguez | 2230 |
| Data Science | Noah Johnson | 6800 |
| Data Science | William Davis | 6800 |
Solve this question and run your code right in DataLemur's online SQL environment:
Answer:
We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.
If the code above is hard to understand, you can find a detailed solution here: Top 3 Department Salaries.
SQL Question 3: What's a cross-join, and why are they used?
A cross-join, also known as a cartesian join, is a JOIN that produces the cross-product of two tables. In a cross-join, each row from the first table is matched with every row from the second table, resulting in a new table with a row for each possible combination of rows from the two input tables.
Suppose you were building a Neural Network ML model, that tried to score the probability of a customer buying a PerkinElmer product. Before you started working in Python and Tensorflow, you might want to do some Exploratory Data Analysis (EDA) in SQL, and generate all pairs of customers and PerkinElmer products.
Here's a cross-join query you could use to find all the combos:
Cross-joins are great for generating all possible combinations, but they can also create really big tables if you're not careful. For example, if you had 10,000 potential customers, and PerkinElmer had 500 different product SKUs, you'd get 5 million rows as a result!!
SQL Question 4: Sales Data Analysis for PerkinElmer
PerkinElmer is a corporation focused on improving human and environmental health, particularly through diagnostics, life science research, industrial, environmental, and laboratory services.
Assume you work as a Data Analyst in the Sales department at PerkinElmer. You have access to two tables:
- : stores information related to each sale carried out.
Example Input:
| sale_id | product_id | customer_id | sale_amount | sale_date |
|---|---|---|---|---|
| 8789 | 149 | 693 | 40000 | 2022-06-06 |
| 9720 | 465 | 985 | 50000 | 2022-06-15 |
| 6531 | 149 | 762 | 45000 | 2022-06-25 |
| 3876 | 465 | 193 | 60000 | 2022-07-01 |
| 5032 | 232 | 985 | 38000 | 2022-07-06 |
- : stores information related to each product sold by the company.
Example Input:
| product_id | product_name | price |
|---|---|---|
| 149 | Genome Sequencer | 40000 |
| 465 | Spectrum Analyzer | 50000 |
| 232 | Microplate Reader | 38000 |
The management wants to know the total revenue generated by each product per month. Write a SQL query to retrieve the total revenue generated by each product for the month of June.
Answer:
This query will return the product name, month number (in this case it would be 6 for June), and the total sales amount for that product for the month of June. The results are grouped by product name and month to provide individual total sales amounts per product. As we specify June in our clause, we will only get the totals for June sales.
SQL Question 5: What are the similarities and differences between the and functions?
Both window functions are used to find rows at a given offset from the current row. However, will give you the rows AFTER the current row you. On the other hand, will give you the rows BEFORE the current row.
SQL Question 6: Filter customer records based on purchasing and location criteria
PerkinElmer, a corporation focused on improving the health and safety standards of people and the environment by providing analytical instruments, has a database of customer transactions. The table contains columns such as , , , , , and .
Their marketing team is planning a promotional offer specifically for customers from 'California' who purchased 'Product Z' and whose total transactions amount to more than $1000. Write an SQL query to fetch records of these customers.
Example Input:
| transaction_id | customer_id | purchase_date | product_id | purchase_amount | location |
|---|---|---|---|---|---|
| 101 | 4501 | 2022-04-26 | Z | 200 | California |
| 102 | 4502 | 2022-04-26 | Y | 500 | Ohio |
| 103 | 4501 | 2022-05-02 | Z | 300 | California |
| 104 | 4502 | 2022-05-03 | Z | 600 | California |
| 105 | 4501 | 2022-05-08 | Z | 1000 | California |
| 106 | 4503 | 2022-05-09 | Z | 400 | New York |
Example Output:
| customer_id | total_amount |
|---|---|
| 4501 | 1500 |
Answer:
This SQL query filters the table for records where the is 'California' and the is 'Z'. The search result is then grouped by , and the total for each customer is calculated. The clause is used to filter the customers whose total is more than $1000. This gives us the desired customer records who qualify for the promotional offer.
SQL Question 7: Can you explain the purpose of the constraint and give an example of when you might use it?
The constraint is used to enforce rules on the data in a specific column. If a row is inserted or updated with data that does not follow the constraint's rule, the operation will fail.
For example, say you had a database that stores ad campaign data from PerkinElmer's Google Analytics account.
Here's what some constraints could look like:
In this example, the constraint is used to ensure that the and fields have positive values. This helps to ensure that the data in the database is valid and makes sense in the context of ad campaigns.
You can also use the constraint to ensure that data meets other specific conditions. For example, you could use a constraint to ensure that the is before the for each ad campaign.
SQL Question 8: Calculate the Click-Through Rate for PerkinElmer's Ads
Given two tables, and , calculate the click-through rate of each ad. Click-through rate is defined as the number of clicks on an ad divided by the number of times the ad is shown, usually expressed as a percentage.
The table contains information about each ad, including its and the . The table contains information about each click, including the , the , and the .
Example Input:
| ad_id | time_shown |
|---|---|
| 1 | 06/08/2022 00:00:00 |
| 2 | 06/10/2022 00:00:00 |
| 3 | 06/18/2022 00:00:00 |
| 1 | 07/26/2022 00:00:00 |
| 2 | 07/05/2022 00:00:00 |
Example Input:
| click_id | ad_id | time_clicked |
|---|---|---|
| 101 | 1 | 06/08/2022 00:03:00 |
| 102 | 2 | 06/10/2022 00:30:00 |
| 103 | 1 | 07/26/2022 00:20:00 |
| 104 | 2 | 07/05/2022 05:40:00 |
| 105 | 3 | 06/18/2022 01:10:00 |
Answer:
This query will join the two tables based on the and then count the number of clicks and shows for each . Computing the click-through rate by dividing the number of clicks by the number of shows and multiplying by 100 to express as a percentage. The click-through rate is then returned for each . This allows us to understand which ads have the highest engagement in terms of click-through rates.
To solve a related SQL interview question on DataLemur's free interactive SQL code editor, try this Meta SQL interview question:
SQL Question 9: Filter Customer Database by Location
As a part of PerkinElmer's customer management team, you're given a task to filter out the customers who are residing in California, USA. This filtering is particularly important as the new regulations implemented by the California government require us to provide a special type of servicing for devices used by customers located in that region. The company maintains a table which consists of (an unique identifier for each customer), (the name of the customer), (the location of the customer), and (the identifier of the PerkinElmer device the customer is using).
Example Input:
| customer_id | name | location | device_id |
|---|---|---|---|
| 101 | John Doe | California, USA | 301 |
| 102 | Emily Smith | Texas, USA | 303 |
| 103 | Robert Johnson | New York, USA | 301 |
| 104 | Linda Anderson | California, USA | 305 |
| 105 | Michael Brown | Florida, USA | 304 |
Expected Output:
| customer_id | name | location | device_id |
|---|---|---|---|
| 101 | John Doe | California, USA | 301 |
| 104 | Linda Anderson | California, USA | 305 |
Note: The output includes customers who are residing in 'California, USA'.
Write a SQL query that filters out customers based on the location 'California, USA'.
Answer:
The above SQL query uses the keyword to filter out all the records from table where the field matches the string 'California, USA'.
SQL Question 10: Can you describe the concept of a database index and the various types of indexes?
A database index is a data structure that provides a quick lookup of data in a column or columns of a table.
There are several types of indexes that can be used in a database:
- Primary index: a unique identifier is used to access the row directly.
- Unique index: used to enforce the uniqueness of the indexed columns in a table.
- Composite index: created on multiple columns of a table, is used to speed up the search process for multiple columns
- Clustered index: determines the physical order of the data in a table
PerkinElmer SQL Interview Tips
The best way to prepare for a PerkinElmer SQL interview is to practice, practice, practice. Beyond just solving the above PerkinElmer SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Netflix, Google, and Amazon.
Each DataLemur SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and crucially, there's an interactive coding environment so you can right in the browser run your SQL query answer and have it graded.
To prep for the PerkinElmer SQL interview you can also be a great idea to solve SQL questions from other healthcare and pharmaceutical companies like:
- Encompass Health SQL questions
- Syneos Health SQL questions
- Edwards Lifesciences SQL questions
- Hologic SQL questions
However, if your SQL coding skills are weak, don't worry about going right into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.
This tutorial covers topics including creating summary stats with GROUP BY and how window functions work – both of which show up routinely in PerkinElmer interviews.
PerkinElmer Data Science Interview Tips
What Do PerkinElmer Data Science Interviews Cover?
Besides SQL interview questions, the other types of problems tested in the PerkinElmer Data Science Interview are:
- Probability & Statistics Questions
- Python Pandas or R Coding Questions
- Open-Ended Data Case Studies
- ML Modelling Questions
- Behavioral Based Interview Questions
How To Prepare for PerkinElmer Data Science Interviews?
I think the best way to study for PerkinElmer Data Science interviews is to read the book Ace the Data Science Interview.
It has 201 data interview questions taken from companies like Google, Tesla, & Goldman Sachs. The book's also got a crash course on Python, SQL & ML. And finally it's vouched for by the data community, which is how it's gotten to be an Amazon best-seller with over 1000+ 5-star reviews.
While the book is more technical, it's also important to prepare for the PerkinElmer behavioral interview. Start by understanding the company's unique cultural values.