10 CompuGroup Medical SQL Interview Questions (Updated 2024)
At CompuGroup Medical, SQL is used all the damn time for analyzing healthcare data to inform patient care decisions, and managing databases within the company's medical software solutions. Unsurprisingly this is why CompuGroup Medical almost always evaluates jobseekers on SQL query questions during interviews for Data Science and Data Engineering positions.
So, to help you prepare for the CompuGroup Medical SQL interview, here’s 10 CompuGroup Medical SQL interview questions – able to solve them?
10 CompuGroup Medical SQL Interview Questions
SQL Question 1: Identify Power Users in CompuGroup Medical Services
CompuGroup Medical is a healthcare software company and in this context, a power user would be a health service provider (HSP) that uses a specific healthcare software frequently. Assume we have a "usage_log" table that records every time a HSP logs into and uses a product (software). Each record in the usage_log table has an id for the record (log_id), the id of the HSP that used the product (hsp_id), the id of the product that was used (product_id), and the timestamp of when the product was used (usage_timestamp).
Your task is to write a SQL query to identify the top 3 HSPs that have used any individual product the most number of times in the past six months. Display the hsp_id, product_id and usage_count (number of times the product was used).
Example Input:
| log_id | hsp_id | product_id | usage_timestamp |
|---|---|---|---|
| 101 | 123 | 500 | 01/02/2022 09:00:00 |
| 102 | 265 | 500 | 01/04/2022 10:00:00 |
| 103 | 123 | 200 | 01/06/2022 11:00:00 |
| 104 | 531 | 900 | 01/08/2022 12:00:00 |
| 105 | 772 | 900 | 01/10/2022 13:00:00 |
| 106 | 123 | 500 | 01/12/2022 14:00:00 |
| 107 | 265 | 700 | 01/14/2022 15:00:00 |
| 108 | 123 | 500 | 01/16/2022 16:00:00 |
| 109 | 531 | 500 | 01/18/2022 17:00:00 |
| 110 | 772 | 200 | 01/20/2022 18:00:00 |
Answer:
The subquery (WITH clause) named product_usage selects and groups the data by hsp_id and product_id where the usage is within the past six months and counts the number of logs (usage_count) for each pair of hsp_id and product_id.
After getting the usage_count, the main query orders the data by usage_count in descending order and selects the top 3 to identify the top 3 power users.
To work on another SQL customer analytics question where you can solve it right in the browser and have your SQL code instantly graded, try this Walmart SQL Interview Question:
SQL Question 2: Compute Monthly Average Review Scores
CompuGroup Medical, a leading eHealth corporation, needs your help to analyze customer feedback for its medical software products. Each product gets reviewed by customers and scores are assigned. Your task is to write a SQL query that computes the average review scores per product per month. The dataset you need to analyze is in a table named .
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 |
Example Output:
| mth | product_id | avg_stars |
|---|---|---|
| 6 | 50001 | 3.5 |
| 6 | 69852 | 4 |
| 7 | 69852 | 2.5 |
Answer:
Here is the SQL query that solves the problem.
This PostgreSQL query first extracts the month from the using the function. For each combination of month and product (, ), the query then calculates the average review score (). The outcome is eventually ordered by month and product.
p.s. Window functions show up pretty frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
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: Healthcare Services Utilization by Patients
CompuGroup Medical is a global eHealth provider with a comprehensive portfolio of cutting-edge IT solutions for the healthcare industry. We are interested in understanding healthcare services utilization by our patients: how many different types of services each patient uses, the frequency of each service type, and the total cost involved.
Please consider the following database schema for this problem: a 'patients' table including patient_id and name, a 'services' table with service_id and service_type, and an 'appointments' table which includes appointment_id, patient_id, service_id, appointment_date, and service_cost.
Example Input:
| patient_id | name |
|---|---|
| 1 | John Doe |
| 2 | Jane Doe |
| 3 | David Smith |
Example Input:
| service_id | service_type |
|---|---|
| 1 | Physical Examination |
| 2 | Blood Tests |
| 3 | Cardiology Consultation |
Example Input:
| appointment_id | patient_id | service_id | appointment_date | service_cost |
|---|---|---|---|---|
| 1 | 1 | 3 | 06/10/2022 | 120 |
| 2 | 1 | 2 | 06/18/2022 | 50 |
| 3 | 2 | 1 | 07/05/2022 | 70 |
| 4 | 2 | 3 | 07/10/2022 | 120 |
| 5 | 3 | 1 | 07/26/2022 | 70 |
We want to see the total cost each patient has to pay for the services received in each month. Show the result in the format (, , ).
Answer:
This query extracts the month from the appointment_date, grouping by patient_id and month. It calculates the sum of service_cost for each patient for each month. The final result is sorted by month and patient_id for clarity.
SQL Question 5: What is normalization?
To normalize a database, tables are divided into smaller, more specialized ones and relationships between them are defined via primary and foreign keys. This minimizes redundancy, making the database more flexible, scalable, and easier to maintain. Normalization also helps to ensure the accuracy of the data by reducing the likelihood of inconsistencies and errors.
SQL Question 6: Filtering patients based on their medical conditions
As a medical data analyst at CompuGroup Medical, your job is to analyze the patients information and draw meaningful insights. You have been given the access to the patient's database and you are required to extract the information of those patients who have diabetes and are above the age of 60. In addition, the patients should also not have taken any hospitalization services in the last one year. Given the patients and hospitalization tables, write a SQL query to extract this information.
Example Input:
| patient_id | first_name | last_name | age | has_diabetes |
|---|---|---|---|---|
| 4765 | John | Doe | 65 | True |
| 6291 | Jane | Smith | 70 | True |
| 9842 | Michael | Roe | 50 | True |
| 4235 | Sarah | Johnson | 80 | False |
| 6719 | Patricia | Williams | 63 | True |
Example Input:
| hospitalization_id | patient_id | date_of_hospitalization |
|---|---|---|
| 1246 | 4765 | 09/25/2020 |
| 1523 | 6291 | 08/20/2021 |
| 6874 | 9842 | 07/30/2022 |
| 2645 | 4235 | 05/12/2021 |
| 6853 | 6719 | 03/21/2020 |
Answer:
This SQL query first joins the patients and hospitalizations tables on the patient_id field. It then uses the WHERE clause to filter out patients who have diabetes, are above the age of 60, and have not taken hospitalization services in the past year. The final grouping by patient_id ensures that you get a unique list of patients satisfying the given conditions.
SQL Question 7: What is the difference between the and window functions?
While both and are used to rank rows, the key difference is in how they deal with ties.
RANK(): When there's a tie, leaves a gap in the ranking. For example, if three rows are tied for 2nd place, the RANK() function will assign a rank of 2 to the first of these rows, a rank of 3 to the 2nd row in the tie, and a rank of 4 to the the 3rd tie.
DENSE_RANK(): For ties, does not leave a gap in the ranking. Instead, it assigns the same rank to all tied rows, and then makes the next row 1 bigger. Confusing, I know, but here's an example to make it more clear: if three rows are tied for 3rd place, the function will assign a rank of 3 to all three rows, and then assign a rank of 4 to the next row.
Suppose we had data on how many deals different salespeople at CompuGroup Medical closed, and wanted to rank the salespeople.
The result of this query would be:
| name | deals_closed | rank | dense_rank |
|---|---|---|---|
| Akash | 50 | 1 | 1 |
| Brittany | 50 | 2 | 1 |
| Carlos | 40 | 3 | 2 |
| Dave | 40 | 4 | 3 |
| Eve | 30 | 5 | 3 |
| Frank | 20 | 6 | 4 |
As you can see, the function assigns a rank of 1 to the first row (Akash), a rank of 2 to the second row (Brittany), and so on. In contrast, the , gives both Akash and Brittany a rank of 1, since they are tied, then moves on to rank 2 for Carlos.
SQL Question 8: What is the Average Duration of Patient Appointments?
As a data analyst for CompuGroup Medical, one of your tasks is to assess the operational efficiency of healthcare providers using CompuGroup's software by quantifying patient wait times during appointments. Can you write a SQL query to calculate the average duration of patient appointments for each healthcare provider, in minutes?
Consider the following and tables.
Example Input:
| appointment_id | provider_id | appointment_date | start_time | end_time |
|---|---|---|---|---|
| 8171 | 001 | 06/08/2022 00:00:00 | 8:30:00 | 9:15:00 |
| 8022 | 002 | 06/10/2022 00:00:00 | 12:00:00 | 13:00:00 |
| 8293 | 001 | 06/18/2022 00:00:00 | 8:00:00 | 9:00:00 |
| 8152 | 003 | 07/26/2022 00:00:00 | 15:00:00 | 15:30:00 |
| 8517 | 003 | 07/05/2022 00:00:00 | 14:00:00 | 14:30:00 |
Example Input:
| provider_id | provider_name |
|---|---|
| 001 | Dr. Smith |
| 002 | Dr. Johnson |
| 003 | Dr. Gupta |
Answer:
Explanation:
The query first joins the table with the table on the . It then calculates the duration of each appointment by subtracting the from the , and divides it by 60 to convert the result to minutes. The function is then used to calculate the average appointment duration for each healthcare provider. Finally, the results are ordered by descending average appointment duration.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating average metrics from data or this Alibaba Compressed Mean Question which is similar for dealing with averages in SQL queries.
SQL Question 9: Analyzing Patient Visits per Department in a Healthcare setting.
CompuGroup Medical deals with software and consulting for the healthcare sector. Assume your database stores the appointment data of patients by department.
Based on the data, can you determine the average number of patient visits per department per month?
Example Input:
| visit_id | patient_id | visit_date | department_id |
|---|---|---|---|
| 1001 | 77 | 06/08/2022 00:00:00 | 20 |
| 1002 | 163 | 06/10/2022 00:00:00 | 30 |
| 1003 | 354 | 06/18/2022 00:00:00 | 20 |
| 1004 | 46 | 07/26/2022 00:00:00 | 10 |
| 1005 | 501 | 07/05/2022 00:00:00 | 10 |
Example Output:
| month | department_id | avg_visits |
|---|---|---|
| 6 | 20 | 2 |
| 6 | 30 | 1 |
| 7 | 10 | 2 |
Answer:
This query breaks down the visit data by month and department. It then uses the COUNT function to find the total number of visits and divides this by the distinct number of patients to find the average number of visits per patient for each department in each month.
SQL Question 10: Can you describe the difference between a correlated and a non-correlated sub-query?
hile a correlated subquery relies on columns in the main query's FROM clause and cannot function independently, a non-correlated subquery operates as a standalone query and its results are integrated into the main query.
An example correlated sub-query:
This correlated subquery retrieves the names and salaries of CompuGroup Medical employees who make more than the average salary for their department. The subquery references the department column in the main query's FROM clause (e1.department) and uses it to filter the rows of the subquery's FROM clause (e2.department).
An example non-correlated sub-query:
This non-correlated subquery retrieves the names and salaries of CompuGroup Medical employees who make more than the average salary for the Data Science department (which honestly should be very few people since Data Scientists are awesome and deserve to be paid well).The subquery is considered independent of the main query can stand alone. Its output (the average salary for the Data Science department) is then used in the main query to filter the rows of the CompuGroup Medical employees table.
CompuGroup Medical SQL Interview Tips
The best way to prepare for a CompuGroup Medical SQL interview is to practice, practice, practice.
Beyond just solving the earlier CompuGroup Medical SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Facebook, Google and unicorn tech startups.
Each SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and most importantly, there's an interactive coding environment so you can right in the browser run your SQL query and have it executed.
To prep for the CompuGroup Medical SQL interview you can also be helpful to practice interview questions from other tech companies like:
However, if your SQL query skills are weak, forget about going right into solving questions – strengthen your SQL foundations with this SQL interview tutorial.
This tutorial covers things like RANK() window functions and WHERE vs. HAVING – both of these come up often in SQL job interviews at CompuGroup Medical.
CompuGroup Medical Data Science Interview Tips
What Do CompuGroup Medical Data Science Interviews Cover?
In addition to SQL interview questions, the other question categories to practice for the CompuGroup Medical Data Science Interview are:
- Probability & Statistics Questions
- Python or R Programming Questions
- Product Analytics Questions
- Machine Learning Questions
- Behavioral Interview Questions
How To Prepare for CompuGroup Medical Data Science Interviews?
To prepare for CompuGroup Medical Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from tech companies like Google & Microsoft
- a refresher covering Python, SQL & ML
- over 900+ reviews on Amazon & 4.5-star rating