9 DexCom SQL Interview Questions (Updated 2024)
Data Analysts and Data Scientists at DexCom write SQL queries to analyze glucose monitoring data, helping them find patterns that can lead to better health outcomes for patients. They also rely on SQL to keep track of patient databases, ensuring that each individual receives the attention they need based on their health information, that is the reason why DexCom often asks SQL interview problems to jobseekers .
Thus, to help you practice, here's 9 DexCom SQL interview questions – can you solve them?
9 DexCom SQL Interview Questions
SQL Question 1: Analyzing Glucose Monitoring Device Usage and Average Glucose Level
DexCom is a company that specializes in continuous glucose monitoring for diabetes management.
Let's imagine you are given a database that contains each patient's usage record and the reported glucose levels each time they use their DexCom device.
Design a SQL query that determines the average glucose levels for each patient on a weekly basis and also rank them based on this weekly average.
Sample Input:
| usage_id | patient_id | usage_date | device_id | glucose_level |
|---|---|---|---|---|
| 9393 | 406 | 01/06/2022 00:00:00 | 20005 | 150 |
| 2457 | 579 | 01/07/2022 00:00:00 | 35714 | 140 |
| 3195 | 406 | 01/08/2022 00:00:00 | 20005 | 122 |
| 2951 | 579 | 01/08/2022 00:00:00 | 35714 | 182 |
| 5834 | 406 | 01/13/2022 00:00:00 | 20005 | 130 |
Example Output:
| week | patient_id | avg_glucose_level | rank |
|---|---|---|---|
| 1 | 406 | 136 | 1 |
| 1 | 579 | 161 | 2 |
Answer:
The first block creates a temporary table, , to calculate the average glucose level for each patient on a weekly basis. In the main statement, we rank each patient's average glucose level within each week using the window function. The clause in both the and ensures that the operations are performed "per patient per week" and "per week," respectively. The result is a list of patients' IDs, their average glucose level for each week, and how they rank in terms of glucose level for that week.
p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
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SQL Question 2: Department Salaries
Assume there was a table of DexCom employee salaries, along with which department they were in. Write a query to compare the average salary of employees in each department to the company's average salary. Return the comparison result as 'higher', 'lower', or 'same' for each department. Display the department ID, payment month (in MM-YYYY format), and the comparison.
You can solve this question interactively on DataLemur:
The answer is LONG – 30+ lines of SQL. You can find a step-by-step solution here: Department vs. Company Salary.
SQL Question 3: How would you go about optimizing a slow SQL query?
First things first, figure out why the query is slow! You can use and commands in PostgreSQL to identify any performance bottlenecks. You might discover that your query is inefficient, or that there are many database writes at the same time you are doing a read, or maybe too many people are concurrently running queries on the same database server.
For Data Analyst and Data Science positions, knowing the ins-and-outs of SQL performance tuning is out-of-scope for the SQL interview round. However, knowing that joins are expensive, and indexes can speed up queries, is generally enough of an answer for DexCom SQL interviews.
SQL Question 4: Tracking Glucose Level Over Time in PostgreSQL
DexCom is a company that develops, manufactures, and distributes continuous glucose monitoring systems for diabetes management. It's important for such a company to track glucose levels of patients over time for any trends or patterns that may indicate overall effectiveness of their product and need for any improvements.
Design a SQL database with a table and a table. The table will contain attributes like , , , , and . The table will include , , , and .
The table should look like the following:
Example Input:
| patient_id | name | age | gender | blood_type |
|---|---|---|---|---|
| 1 | John Doe | 45 | Male | O |
| 2 | Jane Doe | 34 | Female | A |
| 3 | Jim Jones | 56 | Male | B |
| 4 | Betty Cooper | 42 | Female | AB |
| 5 | Tom Smith | 37 | Male | O |
The table could look as follows:
Example Input:
| reading_id | patient_id | timestamp | glucose_level |
|---|---|---|---|
| 101 | 1 | 07/15/2022 08:00:00 | 120 |
| 102 | 1 | 07/15/2022 12:00:00 | 110 |
| 103 | 2 | 07/15/2022 08:00:00 | 98 |
| 104 | 2 | 07/15/2022 12:00:00 | 105 |
| 105 | 3 | 07/15/2022 08:00:00 | 129 |
| 106 | 3 | 07/15/2022 12:00:00 | 125 |
| 107 | 4 | 07/15/2022 08:00:00 | 115 |
| 108 | 4 | 07/15/2022 12:00:00 | 120 |
| 109 | 5 | 07/15/2022 08:00:00 | 95 |
| 110 | 5 | 07/15/2022 12:00:00 | 105 |
The business question could be to obtain the average glucose level per patient for a particular date.
Answer:
To obtain the average glucose level per patient for a particular date, you can join the two tables on and then group by . You may write a PostgreSQL query as follows:
SQL Question 5: Can you explain the distinction between a clustered and a non-clustered index?
Here is an example of a clustered index on the column of a table of DexCom customer transactions:
This creates a clustered index on the column, which will determine the physical order of the data rows in the table.
Here is an example of a non-clustered index on the column of the same table:
This will create a non-clustered index on the column, which will not affect the physical order of the data rows in the table.
In terms of query performance, a clustered index is usually faster for searches that return a large number of records, while a non-clustered index is faster for searches that return a small number of records. However, updates to a clustered index are slower, as they require the data rows to be physically rearranged, while updates to a non-clustered index are faster, as they only require the index data structure to be updated.
SQL Question 6: Analyzing Click-Through Rates for DexCom Products
Dexcom is a company that designs, develops, and commercializes continuous glucose monitoring systems for people with diabetes. Let's say that they're interested to learn about the click-through rates of their marketing emails, and how many of those clicks result in a completed purchase. We have two tables, and , as follows:
Example Input:
| click_id | user_id | email_date | product_id |
|---|---|---|---|
| 1 | 111 | 2022-07-01 | 10001 |
| 2 | 111 | 2022-07-01 | 10002 |
| 3 | 222 | 2022-07-02 | 10001 |
| 4 | 333 | 2022-07-03 | 10003 |
| 5 | 444 | 2022-07-03 | 10002 |
Example Input:
| purchase_id | user_id | purchase_date | product_id |
|---|---|---|---|
| 1 | 111 | 2022-07-02 | 10001 |
| 2 | 555 | 2022-07-04 | 10001 |
| 3 | 444 | 2022-07-04 | 10002 |
| 4 | 333 | 2022-07-05 | 10003 |
| 5 | 666 | 2022-07-06 | 10001 |
Write a SQL query to find the click-through conversion rate for each product, where click-through conversion rate is defined as the number of purchases made through the email clicks, divided by the number of email clicks, for each product.
Answer:
Here is the SQL query that can be used:
In this query, we use a subquery to calculate the total number of clicks for each . We then JOIN this with another subquery , where we calculate the number of clicks that result in purchases, again grouped by . The function is used to ensure that if there are no purchases for a given (resulting in a NULL value), it will be replaced with 0 to avoid any errors. Finally, we calculate the by dividing the number of purchased clicks by total clicks and then multiplying by 100 to get it in percentage terms.
To solve another question about calculating rates, solve this TikTok SQL question on DataLemur's online SQL coding environment:
SQL Question 7: What is database denormalization, and when is it a good idea to consider it?
Denormalization is the practice of altering a database schema in a way that breaks the normalization rules (1st, 2nd, 3rd normal forms).
For example, in a database that stores DexCom sales analytics data, you might have separate tables for "customers," "orders," and "products," with foreign key constraints linking the tables together. This helps to ensure the integrity of the data and reduces redundancy, but it can also make queries that involve multiple tables more complex and slower to execute.
By de-normalizing the database, you can combine some of the data from separate tables into a single table, which can reduce the number of joins that are required to retrieve the data you need. This can speed up queries and improve the performance of your database.
However, it's important to carefully consider the trade-offs of de-normalization before making any changes to your database. De-normalization can make it more difficult to maintain the integrity and reliability of your data, and can also increase the risk of data redundancy. It's generally best to use de-normalization as a performance optimization technique only when necessary, and to carefully evaluate the benefits and drawbacks in the context of your specific database and workload.
SQL Question 8: Filter Customer Records based on Product Code
DexCom is a globally renowned company that specializes in manufacturing devices to diagnose and manage diabetes. Suppose you are working in the data team at DexCom. There is a table named , where you have records of all customers who have ever bought a product from DexCom. One of the columns in the table is , which contains unique codes of the products that customers have purchased. Your task is to write a SQL query to find the customers who purchased a product with a that starts with 'DexC'.
Below is a sample representation of Table:
Example Input:
| Customer_id | First_name | Last_name | Product_Code | Purchase_Date |
|---|---|---|---|---|
| 5432 | John | Doe | DexC12345 | 2022-08-01 |
| 7890 | Jane | Smith | Prod23456 | 2022-08-05 |
| 6524 | Sue | Johnson | DexC234567 | 2022-08-08 |
| 9802 | Mike | Williams | Prod78901 | 2022-08-11 |
| 6251 | Emily | Brown | DexC345678 | 2022-08-15 |
Answer:
The following SQL query can be used to solve this task:
This SQL query uses the keyword to filter the data. 'DexC%' is the pattern being matched here, where '%' is a wildcard that matches zero or more characters. Using 'DexC%' will return all records where the starts with 'DexC'.
So, this query will return the records of all customers who purchased a product having a Product Code starting with 'DexC'.
SQL Question 9: Calculate Device Efficiency
As DexCom is a medical device company that creates glucose monitoring systems, one important metric could be to measure the efficiency of the devices. Device efficiency could be defined as the absolute difference between the expected measurement value and the actual measurement value, divided by the expected value, and then rounded to two decimal places.
Find the average and variability (standard deviation) of the efficiency for each device model in DexCom's portfolio. Assume higher numbers for efficiency mean better performance.
Let's assume we have two tables:
Example Input:
| measurement_id | device_id | measurement_date | actual_value | expected_value |
|---|---|---|---|---|
| 1 | 100 | 06/08/2022 00:00:00 | 95 | 100 |
| 2 | 100 | 06/09/2022 00:00:00 | 105 | 100 |
| 3 | 101 | 06/10/2022 00:00:00 | 110 | 100 |
| 4 | 101 | 06/11/2022 00:00:00 | 90 | 100 |
| 5 | 102 | 06/12/2022 00:00:00 | 100 | 100 |
Example Input:
| device_id | model |
|---|---|
| 100 | DexCom G6 |
| 101 | DexCom G5 |
| 102 | DexCom G4 |
Answer:
This SQL query calculates the efficiency of each device in each measurement, averages them, and then calculates the standard deviation (variability) of these efficiencies for each device model. It makes use of mathematical functions such as (absolute value), (average), and (standard deviation), as well as the arithmetic operators , , and . All values are rounded to two decimal places. The clause is used to connect the measurements with their corresponding device model.
To practice a very similar question try this interactive Snapchat Sending vs. Opening Snaps Question which is similar for calculating percentages to two decimal places or this Google Median Google Search Frequency Question which is similar for rounding median to a decimal point.
How To Prepare for the DexCom SQL Interview
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. Besides solving the above DexCom SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Meta, Google and healthcare and pharmaceutical companies like DexCom.
Each interview question has multiple hints, fully explained answers along with a discussion board to see how others solved it and crucially, there is an interactive SQL code editor so you can right in the browser run your query and have it graded.
To prep for the DexCom SQL interview you can also be useful to solve SQL questions from other healthcare and pharmaceutical companies like:
- Teleflex SQL questions
- West Pharma SQL questions
- Hill-Rom Holdings SQL questions
- Change Healthcare SQL questions
But if your SQL skills are weak, don't worry about going right into solving questions – go learn SQL with this SQL tutorial for Data Scientists & Analysts.
This tutorial covers SQL concepts such as filtering data with boolean operators and math functions like CEIL()/FLOOR() – both of these show up routinely in DexCom SQL assessments.
DexCom Data Science Interview Tips
What Do DexCom Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories covered in the DexCom Data Science Interview include:
- Probability & Stats Questions
- Coding Questions in Python or R
- Product-Sense Questions
- Machine Learning Questions
- Behavioral Based Interview Questions
How To Prepare for DexCom Data Science Interviews?
To prepare for the DexCom Data Science interview make sure you have a deep understanding of the company's cultural values – this will be important for acing the behavioral interview. For the technical Data Science interviews, prepare by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from Facebook, Google, & Amazon
- A Refresher covering Python, SQL & ML
- Great Reviews (1000+ reviews, 4.5-star rating)