# 10 Medtronic SQL Interview Questions (Updated 2024)

Updated on

August 11, 2024

Medtronic employees use SQL daily to analyze patient data, including medical histories, treatment outcomes, and device performance metrics, to evaluate the effectiveness of medical devices. It is also used to manage large datasets, including clinical trial results and patient registries, to identify trends and insights that inform product development and improvement, the reason why Medtronic often asks SQL problems in interviews for Data Science and Data Engineering positions.

As such, to help you ace the Medtronic SQL interview, here's 10 Medtronic SQL interview questions in this blog.

## 10 Medtronic SQL Interview Questions

### SQL Question 1: Medtronic Product Sales Analysis

Keeping in mind the activities of Medtronic, which is a medical device company, let's say that they want to keep track of how their sales reps have been doing. Write a SQL query that will rank each sales representative by the total revenue they've generated from all the products they've sold, for each month, over a provided time period.

Here's some example data:

##### Example Input:
sale_idrep_idsale_dateproduct_idquantityprice
11012022-04-15200115010
21022022-04-2030011228
31032022-04-25200124110
41012022-04-3040013219
51022022-05-07200119410
61032022-05-1130014718
71012022-05-1640011199
81022022-06-2130013418
##### Example Output:
monthrep_idtotal_revenuerank
2022-0410146502
2022-041029763
2022-0410324101
2022-0510110712
2022-0510219401
2022-0610227281

Here's a PostgreSQL query that solves this:

In this solution, the window function is used along with to segment the data into sets based on the month of sale, and then order the data within each set based on the total revenue generated by each sales rep. The calculates the total revenue for each sales rep in each month, and then assigns a rank based on this total for each month. The result is a ranking of sales reps by revenue for each month.

To practice a related window function SQL problem on DataLemur's free online SQL coding environment, try this Google SQL Interview Question:

### SQL Question 2: Employees Earning More Than Managers

Given a table of Medtronic employee salaries, write a SQL query to find all employees who earn more than their own boss.

#### Medtronic Example Input:

employee_idnamesalarydepartment_idmanager_id
1Emma Thompson38001
2Daniel Rodriguez2230110
3Olivia Smith800018
4Noah Johnson680028
5Sophia Martinez1750110
8William Davis70002NULL
10James Anderson40001NULL

#### Example Output:

employee_idemployee_name
3Olivia Smith

This is the output because Olivia Smith earns \$8,000, surpassing her manager, William Davis who earns 7,800.

Test your SQL query for this interview question and run your code right in DataLemur's online SQL environment:

First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.

If the code above is tough, you can find a step-by-step solution here: Employee Salaries Higher Than Their Manager.

### SQL Question 3: What are the similarities and differences between a clustered index and non-clustered index?

A clustered index is an index where the order of the rows in the database corresponds to the order of the rows in the index. Because of this, a table can only have one clustered index, but it can have multiple non-clustered indexes.

The main difference between the two is that the database tries to keep the data in the same order as the corresponding keys in the clustered index. This can improve the performance of most query operations, as it provides a linear-access path to the data stored in the database.

### SQL Question 4: Identify Active Customers who purchased the Pacemaker

Medtronic Inc., a medical device company, wants to determine which customers have purchased their Pacemaker device and have been active within the last 6 months. "Active" is defined as having made at least one purchase within the last 6 months. Create an SQL command to filter out these customers from their customer records database.

##### Example Input:
customer_idlast_namefirst_namelast_purchase_date
121SmithJohn2022-06-08
265JohnsonJane2022-03-22
362BrownBob2022-07-12
192TaylorTed2022-02-15
981MillerMary2022-09-12
##### Example Input:
purchase_idcustomer_idproductquantity
4032121Pacemaker1
5293265Insulin Pump2
6953362Pacemaker1
7802192Neurostimulator1
8671981Pacemaker1

This PostgreSQL query joins the and tables on the field. It then filters for records where the product is 'Pacemaker' and the last purchase date is within the last 6 months using the clause with multiple conditions (). The construct calculates the date six months ago from the present time.

### SQL Question 5: When would you use the / commands in SQL?

The / operator is used to remove to return all rows from the first SELECT statement that are not returned by the second SELECT statement.

Note that is available in PostgreSQL and SQL Server, while MINUS is available in MySQL and Oracle (but don't stress about knowing which DBMS supports what exact commands since the interviewers at Medtronic should be lenient!).

For a tangible example in PostgreSQL, suppose you were doing an HR Analytics project for Medtronic, and had access to Medtronic'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 contractors who never were a employee using this query:

### SQL Question 6: Average Device Malfunctions per Month

In your role as a data analyst at Medtronic, a leading global provider of medical devices, you've been tasked with investigating the reliability of different devices. Devise a SQL query that calculates the average number of malfunctions reported per month for each device type over the past year.

Sample Input Table:

##### :
malfunction_idreport_datedevice_iddevice_type
10102/01/20213001Pacemaker
10202/15/20213001Pacemaker
10303/05/20213002Insulin Pump
10404/17/20213001Pacemaker
10505/23/20213002Insulin Pump

Sample Output Table:

##### Result:
monthdevice_typeavg_malfunctions
2Pacemaker2
3Insulin Pump1
4Pacemaker1
5Insulin Pump1

#### Explanation:

This query calculates the average number of malfunctions per month for each device type within the year 2021. The date range is specified in the WHERE clause as '2021-01-01' to '2021-12-31'. The EXTRACT function is utilized to get the month from the report_date. The AVG function along with count(malfunction_id) is used to find the average number of malfunctions for each month, partitioned by the device type and month. The final result is ordered by month and device type.

To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating averages over time or this Facebook Active User Retention Question which is similar for reporting monthly statistics.

### SQL Question 7: How does the RANK() window function differ from DENSE_RANK()?

In SQL, both and are used to rank rows within a result set. The key difference between the two functions is how deal with two or more rows having the same value in the ranked column (aka how the break 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 second row, and a rank of 4 to the third row.

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.

## SQL Question 8: Find the product with the highest average sales in every region

As a data analyst at Medtronic, a company that manufactures and sells medical devices, you need to analyze product sales. Write a SQL query that finds the product with the highest average sales in every region for the year 2020.

If there are multiple products with the same highest average sales in a region, return all of those products. For this question, “average sales” refers to the average quantity of sales transactions, not the dollar amount of sales.

Given the below tables, and :

##### Example Input:
sales_idproduct_idregionqtysales_date
1100West102020/01/15
2101East122020/07/02
3102North92020/08/24
4100West172020/02/10
5102East142020/03/05
6101West112020/04/12
##### Example Input:
product_idproduct_name
100Medtronic Device A
101Medtronic Device B
102Medtronic Device C

Write a PostgreSQL query to output the data in the following way:

##### Example Output:
regionaverage_salesproduct_name
West13.5Medtronic Device A
East13Medtronic Device B
North9Medtronic Device C

The query first joins the sales and products tables on the product_id field. Then, it filters for sales in the year 2020. It then groups by region and product_name to form subsets for each combination.

The AVG function is used to calculate the average quantity sold for each product in each region, then the ORDER BY statement arranges these averages in descending order. This means that the top row for each region (which can be obtained by doing a separate window function query) will be the product with the highest average sales for that region.

### SQL Question 9: Extracting Customers with Specific Email Domains

As a data analyst at Medtronic, your task is to filter the customer records to find customers with email addresses from a specific domain, let's say 'gmail.com'. This information is important to the marketing team for targeting email campaigns. Write an SQL query to retrieve customer data having their email addresses at 'gmail.com' from the customer database.

##### Example Input:
customer_idfirst_namelast_nameemailcreated_date
123JohnDoejohndoe@gmail.com08-12-2020 00:00:00
456MarySmithmarysmith@yahoo.com17-06-2021 00:00:00
789JamesBrownjamesbrown@gmail.com20-02-2020 00:00:00
012JenniferWilliamsjenniferw@outlook.com25-10-2019 00:00:00
345MichaelJonesmichaeljones@gmail.com15-03-2021 00:00:00

This query will list all the customers who have registered with an email address from the domain 'gmail.com'. The "%" on both sides of 'gmail.com' in the LIKE clause indicates that any characters can exist before and after the string 'gmail.com'. As email addresses follow a specific format, only the "%" before 'gmail.com' is relevant in this context, but it's a decent practice to use it on both sides for other scenarios.

### SQL Question 10: What distinguishes a left join from a right join?

In SQL, a join generally retrieves rows from multiple tables and combines them into a single result set. For an example of the difference between a left vs. right join, suppose you had a table of Medtronic orders and Medtronic customers.

A retrieves all rows from the left table (in this case, the Orders table) and any matching rows from the right table (the Customers table). If there is no match in the right table, NULL values will be returned for the right table's columns.

A combines all rows from the right table (in this case, the Customers table) and any matching rows from the left table (the Orders table). If there is no match in the left table, NULL values will be displayed for the left table's columns.

### Preparing For The Medtronic SQL Interview

The key to acing a Medtronic SQL interview is to practice, practice, and then practice some more! Besides solving the earlier Medtronic SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Microsoft, Google, Amazon, and tech startups.

Each SQL question has multiple hints, detailed solutions and most importantly, there's an online SQL coding environment so you can right in the browser run your SQL query and have it graded.

To prep for the Medtronic SQL interview you can also be wise to practice interview questions from other med-tech & pharma companies like:

Dive into the world of AI-powered healthcare and see how Medtronic is revolutionizing the industry!

In case your SQL coding skills are weak, forget about going right into solving questions – strengthen your SQL foundations with this DataLemur SQL Tutorial.

This tutorial covers SQL topics like filtering strings using LIKE and aggregate functions – both of these come up often during SQL interviews at Medtronic.

### Medtronic Data Science Interview Tips

#### What Do Medtronic Data Science Interviews Cover?

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

#### How To Prepare for Medtronic Data Science Interviews?

To prepare for Medtronic Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions sourced from tech companies like Netflix, Google, & Airbnb
• a crash course on Python, SQL & ML
• over 1000+ reviews on Amazon & 4.5-star rating

Also focus on the behavioral interview – prep for that with this behavioral interview question bank.