Hologic employees use SQL to analyze customer data from medical devices, gaining valuable insights that help improve product offerings and enhance patient care. It is also used to manage the database of digital medical imaging systems, ensuring everything runs smoothly and efficiently, this is the reason why Hologic evaluates jobseekers with SQL problems during interviews for Data Science, Data Engineering, and Data Analytics jobs.
To help you study for the Hologic SQL interview, here's 10 Hologic SQL interview questions – scroll down to start solving them!
Hologic is a medical technology company that focuses on women’s health. Imagine we have a table called which contains customer ratings for two of Hologic's products, given on different dates. Each review is identified by a , and we know the of the user who posted the review, the of the product being reviewed, the when the review was posted, and finally, the value representing the rating out of 5 given by the user for the product. Your task is to write a SQL query that calculates the average rating (stars) of each product on a monthly basis.
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 |
month | product | avg_stars |
---|---|---|
6 | 50001 | 3.5 |
6 | 69852 | 4.0 |
7 | 69852 | 2.5 |
This SQL command groups the data on the basis of and the month of review submission. Then it calculates the average rating for each one of these groups. The function is used to obtain the month from the column. The function then calculates the average rating for each month for each product.
To solve another window function question on DataLemur's free online SQL code editor, solve this Amazon SQL question asked in a BI Engineer interview:
Uncover the collaboration between Hologic and Google Cloud aimed at advancing next-generation healthcare solutions! This partnership highlights the importance of technology in improving health outcomes, making it relevant for anyone interested in the future of healthcare.
Imagine you had a table of Hologic employee salary data. Write a SQL query to find the top 3 highest earning employees within each department.
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 |
department_id | department_name |
---|---|
1 | Data Analytics |
2 | Data Science |
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 |
Try this interview question interactively on DataLemur:
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 tough, you can find a detailed solution here: Top 3 Department Salaries.
The clause in SQL allows you to select records that are unique, eliminating duplicates.
For example, if you had a table of Hologic employees, and wanted to see what are all the unique job titles that currently worked at the company, you could write the following query:
Hologic Inc. is an innovative medical technology company and they are primarily focused on improving women's health and well-being. One of their products includes breast examination devices. These devices often require regular maintenance and checks. To do this, Hologic maintains records for each hospital/clinic which owns a device, its maintenance records and the details of the employees who are handling the device.
Design a database that can hold this information. The database will have three tables: , , and .
Below are sample records for these tables:
clinic_id | clinic_name | location |
---|---|---|
1001 | Clinic A | New York |
1002 | Clinic B | Chicago |
1003 | Clinic C | Los Angeles |
device_id | clinic_id | purchase_date | model |
---|---|---|---|
2001 | 1001 | 15/07/2017 | Model X |
2002 | 1001 | 18/06/2018 | Model Y |
2003 | 1002 | 12/05/2019 | Model Z |
2004 | 1003 | 05/04/2020 | Model Z |
tech_id | device_id | tech_name | last_maintenance_date |
---|---|---|---|
3001 | 2001 | John Smith | 01/04/2022 |
3002 | 2002 | Jane Doe | 15/03/2022 |
3003 | 2003 | David Johnson | 12/03/2022 |
3004 | 2004 | Mariam Davis | 25/02/2022 |
Given this setup, write a SQL query that retrieves the list of all devices that belong to a specific clinic (e.g., Clinic A), together with their model, purchase date, the technician who last maintained the device, and the last maintenance date.
This query works by performing a JOIN operation on the and tables using as the key. Then it performs another JOIN on and tables using . The WHERE clause then filters out the result by clinic name.
The operator is used to return all rows from the first statement that are not returned by the second statement. Note that is available in PostgreSQL and SQL Server, and it's equivalent operator is called and is available in MySQL and Oracle.
For a tangible example, suppose you were doing an HR Analytics project for Hologic, and had access to Hologic'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 never were a contractor using this query:
As a quality assurance engineer at Hologic, a leading developer, manufacturer, and supplier of premium diagnostic products, you've been tasked to ensure that every machine operates within acceptable time limits. From the database containing records of each test run, your aim is to find the average testing time for each machine.
test_id | machine_id | start_time | end_time |
---|---|---|---|
124 | 101 | 2022-07-06 13:00:00 | 2022-07-06 13:30:00 |
316 | 102 | 2022-07-06 14:15:00 | 2022-07-06 14:45:00 |
711 | 101 | 2022-07-07 10:00:00 | 2022-07-07 10:20:00 |
489 | 103 | 2022-07-07 16:00:00 | 2022-07-07 16:35:00 |
221 | 101 | 2022-07-08 09:00:00 | 2022-07-08 09:45:00 |
This query extracts the difference between the start time and end time for each test on a machine using PostgreSQL's function. The function EPOCH is used for the extraction because it provides the difference in seconds which is then divided by 60 to convert into minutes. function calculates the average of these time differences for each machine.
machine_id | avg_test_minutes |
---|---|
101 | 30.00 |
102 | 30.00 |
103 | 35.00 |
In this output, it shows that the average test times for machines 101 and 102 are 30 minutes, whereas for machine 103 it is 35 minutes.
To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating total duration from start and end times or this Tesla Unfinished Parts Question which is similar for analyzing time duration for task completion.
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.
Often, the offset for both functions is 1, which gives access to the immediately following/preceding row. Here's a SQL query example:
Suppose Hologic has a number of digital products with ads displayed across multiple channels. Typically, when a potential customer clicks an ad, he/she is directed to a product page. Some customers add the product to their cart, which is considered a conversion.
The company wants to perform an analysis of its click-through and conversion rates to better understand the effectiveness of its ads and user engagement. Write a SQL query to calculate the total number of ads clicks, total number of products added to cart and the click-through conversion rate (total added to cart / total ad clicks) for each product in the month of June.
Assume tables and have the following schema:
click_id | ad_date | product_id |
---|---|---|
1 | 06/01/2022 | 1001 |
2 | 06/02/2022 | 1002 |
3 | 06/03/2022 | 1001 |
4 | 06/04/2022 | 1003 |
5 | 06/05/2022 | 1002 |
add_id | add_date | product_id |
---|---|---|
10 | 06/02/2022 | 1001 |
20 | 06/03/2022 | 1001 |
30 | 06/05/2022 | 1003 |
40 | 06/06/2022 | 1001 |
50 | 06/07/2022 | 1003 |
We will use SQL JOIN to link the two tables based on product_id and count the relevant records.
This will give you the total number of ad clicks, total products added to the cart, and the conversion rate for each product for the month of June.
To practice a similar SQL interview question on DataLemur's free online SQL code editor, attempt this Facebook SQL Interview question:
Hologic has been trying to increase its customer engagement. As a first step, they want to send an email to all customers who are located in the "Eastern Region" to inform them about the latest diagnostic products and technologies that Hologic offers. As a Database Administrator, fetch the full name, email and phone for all customers located in the Eastern Region from the table. The records are considered to match if the customer's field is exactly "Eastern Region".
Use the SQL keyword to filter the data.
customer_id | first_name | last_name | region | phone | |
---|---|---|---|---|---|
0001 | John | Doe | Eastern Region | johndoe@example.com | 123-456-7890 |
0002 | Jane | Smith | Western Region | janesmith@example.com | 098-765-4321 |
0003 | Martin | Hope | Eastern Region | martinhope@example.com | 123-789-0654 |
0004 | Edward | Johnson | Northern Region | edwardjohnson@example.com | 589-234-9012 |
full_name | phone | |
---|---|---|
John Doe | johndoe@example.com | 123-456-7890 |
Martin Hope | martinhope@example.com | 123-789-0654 |
This SQL query concatenates the and columns to provide the full name of each customer. It then filters results where the is exactly 'Eastern Region' by using the keyword. The remaining data displays the full name, email, and phone of each customer from the Eastern Region.
To ensure the reliability and integrity of data, a database management system (DBMS) strives to maintain the ACID properties: Atomicity, Consistency, Isolation, and Durability. To illustrate these concepts, consider the following examples of how ACID properties apply to banking transactions:
The key to acing a Hologic SQL interview is to practice, practice, and then practice some more! Besides solving the earlier Hologic SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like FAANG (FB, Apple, Amazon, Netflix, Google).
Each problem on DataLemur has multiple hints, step-by-step solutions and crucially, there is an online SQL code editor so you can right in the browser run your query and have it graded.
To prep for the Hologic SQL interview it is also wise to practice SQL problems from other healthcare and pharmaceutical companies like:
However, if your SQL foundations are weak, don't worry about diving straight into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.
This tutorial covers SQL topics like CTEs and creating summary stats with GROUP BY – both of which pop up often during SQL job interviews at Hologic.
In addition to SQL interview questions, the other types of questions covered in the Hologic Data Science Interview include:
To prepare for the Hologic Data Science interview make sure you have a strong understanding of the company's values and company principles – this will be key to acing the behavioral interview. For technical interviews get ready by reading Ace the Data Science Interview. The book's got: