9 DaVita SQL Interview Questions (Updated 2024)
At DaVita, SQL is essential for analyzing patient health records, helping them assess the effectiveness of various treatments and make informed decisions about patient care. They also utilize SQL to manage inventory data for medical supplies, ensuring that resources are allocated efficiently to meet patient needs, that is the reason why DaVita asks SQL problems during interviews for Data Analytics, Data Science, and Data Engineering roles.
So, to help you prepare, we've collected 9 DaVita SQL interview questions – can you answer each one?
9 DaVita SQL Interview Questions
SQL Question 1: Identify the Top Revenue Generating Patients for DaVita
A leading provider of kidney care in the United States, DaVita wants to identify its power patients. These are patients who have frequent dialysis sessions because these sessions generate the most revenue for the company. Write a SQL query that identifies the top 10 patients who have had the most dialysis sessions in the last six months.
The table has the following columns:
- (date of birth)
The table has the following columns:
Example Input:
| patient_id | name | dob | gender |
|---|---|---|---|
| 1 | John Doe | 01/31/1968 | M |
| 2 | Jane Doe | 09/12/1972 | F |
| 3 | Bob Smith | 10/03/1980 | M |
| 4 | Alice Johnson | 03/22/1956 | F |
| 5 | Charlie Brown | 04/05/1975 | M |
Example Input:
| session_id | patient_id | session_date | session_cost |
|---|---|---|---|
| 1 | 1 | 01/01/2022 | 100 |
| 2 | 2 | 01/02/2022 | 100 |
| 3 | 1 | 01/03/2022 | 100 |
| 4 | 3 | 01/04/2022 | 100 |
| 5 | 2 | 01/05/2022 | 100 |
| 6 | 1 | 01/06/2022 | 100 |
Answer:
This query first joins the and tables based on . It filters the sessions to include only those from the past six months. The function is used to determine the total number of sessions for each patient, while the function calculates the total revenue generated by each patient. The results are ordered by the number of sessions and total revenue, both in descending order, to identify the patients with the most sessions and highest revenue. The clause ensures that only the top 10 patients are returned.
To solve a related super-user data analysis question on DataLemur's free interactive coding environment, try this Microsoft Teams Power User SQL Interview Question:
Explore DaVita's commitment to innovation as they advance new models of care and develop proprietary technology to enhance kidney health! Understanding DaVita's innovative approaches can provide valuable insights into how they are transforming patient care and improving outcomes in the healthcare industry.
SQL Question 2: Second Highest Salary
Imagine you had a table of DaVita employee salary data. Write a SQL query to find the 2nd highest salary at the company.
DaVita Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
You can solve this interview question and run your code right in the browser:
Answer:
You can find a detailed solution here: 2nd Highest Salary.
SQL Question 3: Can you describe a cross-join and its purpose?
A cross-join, also known as a cartesian join, is a type of join that returns the cross-product of two tables. In a cross-join, each row from the first table is paired with every row from the second table, resulting in a new table that has a row for each possible combination of rows from the two input tables.
For example, say you worked on the Marketing Analytics team at DaVita, and needed to understand what advertising copy (text) goes best with what advertising creative (the photo that gets posted with the advertisement copy).
Here is an example of a cross-join between a table of and a table of :
You could this query to generate all possible combinations of ad copy and ad creative to help you create more effective ads for DaVita. Just be careful: if you had 1,000 rows of ad copy and 1,000 different image creatives, the resulting cross-join would have 1 million rows!
SQL Question 4: Analyzing Patient Visits Per Clinic
DaVita is a health care organization primarily serving patients with kidney conditions. Having data on patient visits per clinic over a period of time would be invaluable for the company.
Consider two tables, and , where contains information about each clinic, including its unique and , and stores records of each patient's visit details, including the , , and .
Example Input:
| clinic_id | clinic_name |
|---|---|
| 1 | Clinic A |
| 2 | Clinic B |
| 3 | Clinic C |
| 4 | Clinic D |
Example Input:
| visit_id | clinic_id | patient_id | visit_date |
|---|---|---|---|
| 1001 | 1 | 5007 | 2019-08-15 |
| 1002 | 1 | 5012 | 2019-08-16 |
| 1003 | 2 | 5003 | 2019-08-16 |
| 1004 | 1 | 5007 | 2019-08-17 |
| 1005 | 3 | 5020 | 2019-08-17 |
| 1006 | 4 | 5001 | 2019-08-18 |
| 1007 | 1 | 5012 | 2019-08-19 |
| 1008 | 2 | 5003 | 2019-08-19 |
| 1009 | 3 | 5020 | 2019-08-20 |
The task: Write a SQL query to calculate the running total of patient visits for each clinic per day for the last 7 days.
Answer:
This SQL query uses the window function , which calculates the running total of patient visits for each clinic. The clause divides the table into partitions by , and it orders the data within each partition by . The number of rows in each partition is determined by the clause, providing a count between the current row and the preceding seven days. The clause limits the rows to the last seven days, and the output is ordered by and .
p.s. Window functions show up pretty often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: In the context of a database transaction, what does ACID mean?
A DBMS (database management system), in order to ensure transactions are reliable and correct, tries to maintain the following ACID properties: Atomicity, Consistency, Isolation, and Durability
Here is what each of the ACID properties stands for:
Atomicity: ensures that a transaction is either completed in its entirety, or not completed at all. If a transaction fails halfway, the database does a rollback on the commit.
Consistency: ensures that a transaction will only be completed if adheres to the constraints defined in the database of the DB.
Isolation: ensures that concurrent transactions are isolated from each one another, so that the changes made by one transaction cannot be seen by a 2nd transaction until the 1st transaction is done.
Durability: ensures that once a transaction has been committed, the database permanently stores the results in the DB.
As you can see, it's pretty important for DaVita's data systems to be ACID compliant, else they'll be a big problem for their customers!
SQL Question 6: Patient Record Management in DaVita
DaVita is a notable American healthcare company that operates various clinical laboratories and dialysis centers. Let's consider a scenario where they are redesigning their patient management system.
In this patient management system, they store patient information, the treatments they receive, and the doctors who assist in the treatments. The company wants to extract a few details to help them analyze their operations, particularly they want to know the number of patients each doctor has treated, the average patient age per doctor, and the average treatment cost per patient for each doctor.
Utilize the following table schema:
Example Input:
| doctor_id | doctor_name |
|---|---|
| 101 | Dr.Smith |
| 102 | Dr.Jones |
| 103 | Dr.Sanders |
Example Input:
| patient_id | patient_age |
|---|---|
| 201 | 35 |
| 202 | 45 |
| 203 | 50 |
Example Input:
| treatment_id | patient_id | doctor_id | cost |
|---|---|---|---|
| 301 | 201 | 101 | 1000 |
| 302 | 202 | 102 | 750 |
| 303 | 203 | 103 | 850 |
| 304 | 201 | 101 | 1050 |
| 305 | 202 | 101 | 1100 |
Answer:
The problem can be solved using joins and aggregate functions. Here's the SQL query for PostgreSQL:
In the SQL above, we join the three tables on the relevant fields. We use to find the number of unique patients treated by each doctor. calculates the average age of the patients, while computes the average cost of treatment per patient. We group by doctor to get the aggregate statistics per doctor.
SQL Question 7: What are some similarities and differences between unique and non-unique indexes?
Some similarities between unique and non-unique indexes include:
- Both indexes improve the performance of SQL queries by providing a faster way to lookup the desired data.
- Both indexes use an additional data which requires more storage space which impacts write performance.
- Both indexes can be created on one or more columns of a table
Some differences between unique and non-unique indexes include:
- A unique index enforces the uniqueness of the indexed columns, meaning that no duplicate values are allowed in the indexed columns. A non-unique index allows duplicate values in the indexed columns.
- A unique index can be used to enforce the primary key of a table, but a non-unique index cannot.
- A unique index can have a maximum of one NULL value in the indexed columns, but a non-unique index can have multiple NULLs
SQL Question 8: Average Monthly Number of Dialysis Sessions For Each Patient
As a data analyst at DaVita, which is a healthcare provider focusing on dialysis and kidney care, you've been tasked to find the average number of dialysis sessions per month for each patient in a given year. This will help to understand the frequency of treatment given to patients and monitor their health status.
Example Input:
| treatment_id | patient_id | treatment_date | session_number |
|---|---|---|---|
| 6181 | 124 | 05/01/2021 00:00:00 | 13 |
| 7852 | 265 | 05/03/2021 00:00:00 | 14 |
| 5394 | 361 | 05/05/2021 00:00:00 | 15 |
| 6432 | 195 | 05/07/2021 00:00:00 | 16 |
| 4597 | 985 | 05/09/2021 00:00:00 | 17 |
Example Output:
| mth | patient_id | avg_sessions |
|---|---|---|
| 5 | 124 | 13.00 |
| 5 | 265 | 14.00 |
| 5 | 361 | 15.00 |
| 5 | 195 | 16.00 |
| 5 | 985 | 17.00 |
Answer:
Here is an SQL block that can provide the answer:
This SQL block extracts the month from the column and groups the data by month and . It calculates the average of per month for each patient. The results are refined to the year 2021 by adding a clause. This provides the average number of dialysis sessions per month for each patient in the year 2021.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating average metrics grouped by certain periods or this Twitter Tweets' Rolling Averages Question which is similar for handling time series data in averages.
SQL Question 9: Find the average rating of each Dialysis Center in a certain time period
DaVita is a healthcare company specializing in dialysis services for patients suffering from kidney diseases. They often receive feedback from patients about their services. Each dialysis center is evaluated based on the feedback. The SQL question is about assessing patient satisfaction from the feedback data.
Let's assume the company maintains the following table that holds ratings given by patients to the dialysis centers:
Example Input:
| feedback_id | patient_id | submit_date | center_id | stars |
|---|---|---|---|---|
| 3571 | 123 | 06/08/2022 00:00:00 | 40001 | 4 |
| 4362 | 265 | 06/10/2022 00:00:00 | 29852 | 4 |
| 7743 | 362 | 06/18/2022 00:00:00 | 40001 | 3 |
| 8765 | 192 | 07/26/2022 00:00:00 | 29852 | 3 |
| 6254 | 981 | 07/05/2022 00:00:00 | 29852 | 2 |
With the above data, we want to calculate the average rating for each dialysis center for the month of June, 2022.
Answer:
This query will return a table like the one below, showing the average star rating for each Dialysis center for June 2022.
Example Output:
| month | center_id | avg_rating |
|---|---|---|
| 6 | 40001 | 3.50 |
| 6 | 29852 | 4.00 |
This result tells us that the average rating for the center with the id 40001 was 3.5 stars and for the center with the id 29852 was 4 stars for the month of June 2022.
How To Prepare for the DaVita SQL Interview
The key to acing a DaVita SQL interview is to practice, practice, and then practice some more! Besides solving the above DaVita SQL interview questions, you should also solve the 200+ DataLemur interview questions which come from companies like FAANG (FB, Apple, Amazon, Netflix, Google).
Each interview question has multiple hints, detailed solutions and crucially, there's an interactive coding environment so you can easily right in the browser your SQL query and have it graded.
To prep for the DaVita SQL interview it is also wise to solve interview questions from other healthcare and pharmaceutical companies like:
- Boston Scientific SQL questions
- Community Health Systems SQL questions
- Henry Schein SQL questions
- Universal Health Services SQL questions
But if your SQL skills are weak, don't worry about diving straight into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.
This tutorial covers SQL topics like CASE/WHEN statements and using LIKE – both of these show up often in SQL job interviews at DaVita.
DaVita Data Science Interview Tips
What Do DaVita Data Science Interviews Cover?
Besides SQL interview questions, the other question categories to practice for the DaVita Data Science Interview include:
- Probability & Stats Questions
- Python or R Coding Questions
- Analytics and Product-Metrics Questions
- Machine Learning Questions
- Behavioral & Resume-Based Questions
How To Prepare for DaVita Data Science Interviews?
To prepare for the DaVita Data Science interview have a strong understanding of the company's values and company principles – this will be clutch for acing the behavioral interview. For technical interviews get ready by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG & startups
- A Refresher covering SQL, AB Testing & ML
- Amazing Reviews (1000+ 5-star reviews on Amazon)