# 9 Maximus SQL Interview Questions (Updated 2024)

Updated on

August 11, 2024

Maximus employees often use SQL to analyze vast healthcare data, including patient outcomes and treatment efficacy, for performance improvement. They also facilitate data-driven decision-making by querying and manipulating databases to identify areas of cost reduction, the reason why Maximus uses SQL problems during interviews for Data Analyst, Data Science, and BI jobs.

So, to help you prep for the Maximus SQL interview, we'll cover 9 Maximus SQL interview questions – scroll down to start solving them!

## 9 Maximus SQL Interview Questions

### SQL Question 1: Identify Power Users from Maximus Transactional Data

Maximus is a leading provider of fitness and health consulting services. Being a primarily online-driven business, Maximus keeps strict tabs on user activities on their platform. For their business, a power user is defined as a user that has a significantly high frequency of fitness consultation bookings and a high spending amount.

The data from the customer database of Maximus is stored in two tables, and . The table records the booking frequency of a user while the table keeps track of the total spending amount of a user.

The table has the following data:

##### Example Input:
user_idbooked_datebooking_id
1232022-06-08B50001
1282022-06-18B5293
1312022-07-07B6352
1922022-07-26B4517
2652022-07-16B6171

And the table has the following data:

##### Example Input:
user_idamount
1234000.00
1283500.00
1314700.00
1923600.00
2655000.00

Based on these two tables, your task is to write a SQL query to identify the top 3 power users considered by the total number of bookings and the total spending. The output table should include user_id, total bookings, and total spend.

This SQL query first creates two temporary tables: and . The table calculates the total number of bookings for each user, and the table calculates the total spend for each user. Then join these two tables on the column and order them by both and in descending order. Finally, the query limits the result to 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 query instantly graded, try this Walmart Labs SQL Interview Question:

### SQL Question 2: Department vs. Company Salary

Assume there was a table of Maximus employee salaries, along with which department they belonged to. Write a query to compare the average salary of employees in each department to the company's average salary for March 2024. 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.

Try this problem directly within the browser on DataLemur:

The solution is LONG – 30+ lines of SQL. You can find a step-by-step solution with hints here: Department vs. Company Salary.

### SQL Question 3: What does the operator do?

For a tangible example of in PostgreSQL, suppose you were doing an HR Analytics project for Maximus, and had access to Maximus'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:

Note that is available in PostgreSQL and SQL Server, while is the equivalent operator which is available in MySQL and Oracle (but don't worry about knowing which RDBMS supports which exact commands since Maximus interviewers aren't trying to trip you up on memorizing SQL syntax).

### SQL Question 4: Analyze Product Performance by Month

As an analyst at Maximus, you are provided with data about product reviews. Each review includes the , , , , and (a rating out of 5). You need to analyze this data to understand the average star rating for each product per month. Use SQL window functions to help create a report that shows the average star rating for each product, differentiated by month.

##### Example Input:
review_iduser_idsubmit_dateproduct_idstars
61711232022-06-08500014
78022652022-06-10698524
52933622022-06-18500013
63521922022-07-26698523
45179812022-07-05698522

In PostgreSQL:

This will output a result set that looks like:

##### Example Output:
mthproduct_idavg_stars
6500013.5
6698524.0
7698522.5

This query applies a window function, specifically an average function, on the stars column, while partitioning the data by product_id and month. That means it calculates an average stars rating for each product per month. This helps Maximus to easily track the average stars rating month by month.

Pro Tip: Window functions are a frequent SQL interview topic, so practice all the window function problems on DataLemur

### SQL Question 5: What are the similarities and differences between a clustered and non-clustered index?

Both clustered and non-clustered indexes are used to improve query performance, but they have different characteristics.

A clustered index determines the physical order of the data rows in a table, while a non-clustered index does not.This means that a table can have only one clustered index, but it can have multiple non-clustered indexes.

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: Departmental Employee Management

Maximus Inc. is a multinational company with several departments and numerous employees. It maintains two primary tables: one for their employees and another for their departments. The company's management wants to get a list of all departments along with the total number of employees in each department.

The employees table consists of columns for employee_id (unique identifier for each employee), employee_name and department_id (department in which employee works).

The departments table consists of columns for department_id (unique identifier for each department), and department_name.

##### table sample input:
employee_idemployee_namedepartment_id
1John3
2Jane1
3Alex3
4Annie2
5Rick2
##### table sample input:
department_iddepartment_name
1Sales
2Marketing
3IT

The output of the query should list departments along with the total number of employees in each.

##### Expected output:
department_nametotal_employees
Sales1
Marketing2
IT2

This SQL query joins the and tables on the department_id column. The clause divides the result set into groups by department_name. The function then counts the number of employees in each department, resulting in the total number of employees per department.

### SQL Question 7: How does the constraint function, and in what scenarios might it be useful?

The CHECK constraint is used to enforce rules on the data in a specific column. If a row is inserted or updated with data that does not follow the CHECK constraint's rule, the operation will fail. The CHECK constraint is often used with other constraints, such as NOT NULL or UNIQUE, to ensure that data meets certain conditions. You may want to use a CHECK constraint in your database if you want to maintain the quality and reliability of your data by ensuring that it meets specific criteria.

For example, you might use a CHECK constraint to ensure that a column contains only positive numbers, or that a date is within a certain range.

### SQL Question 8: Calculate the Average Duration of Contracts

Suppose that Maximus is a company that provides service contracts to organizations. As part of a business analysis effort, Maximus wants to understand the average duration (in months) of their contracts throughout the last three years. Therefore, the task is to write a SQL query to find out the average duration of all contracts in each year from the year 2019 to the year 2021.

##### Example Input:
contract_idclient_idstart_dateend_date
101355201/01/201912/31/2019
102372505/01/202004/30/2021
103381910/01/202112/31/2021
104382112/01/202011/30/2021
105382408/01/201907/31/2020
##### Example Output:
yearavg_duration_in_months
201912
202011
20213

This query first extracts the starting year from the column and calculates the duration of each contract in months by using the function to compute the difference between and . We then average these durations for each year using the function. The clause limits our analysis to the years from 2019 to 2021, and the and clauses organize our results by year.

To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating year-on-year metrics or this Amazon Average Review Ratings Question which is similar for < calculating average over time period.

### SQL Question 9: Calculate the Click-Through-Rate (CTR) for Maximus' digital ads

Maximus is a company that relies heavily on digital ads for marketing. They track each ad and the resulting clicks and engagements it receives. For each ad, they track the number of impressions (each time an ad is shown) and the number of clicks (each time an ad is clicked). Given this information, can you calculate the click-through-rate (CTR) for each ad? The click-through-rate (CTR) is defined as the number of clicks on an ad divided by the number of impressions for that ad, expressed as a decimal.

The tables you will be working with are and .

##### Example Input:
1112022-06-011000
2222022-06-022000
3332022-06-033000
##### Example Input:
11112022-06-01
21112022-06-01
32222022-06-02
42222022-06-02
52222022-06-02
63332022-06-03
73332022-06-03
83332022-06-03
93332022-06-03

This SQL query first performs a LEFT JOIN on the two tables and based on their common attribute . Then it breaks down the result into groups based on the ad's id, date, and number of impressions. For each group, it calculates the CTR by counting the number of clicks () for that ad and dividing it by the number of impressions (). The is used to ensure that the division result is a decimal number and not an integer.

To solve a similar problem on DataLemur's free interactive coding environment, attempt this Facebook SQL Interview question:

### Maximus SQL Interview Tips

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 earlier Maximus SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like FAANG tech companies and tech startups.

Each exercise has multiple hints, detailed solutions and most importantly, there's an interactive coding environment so you can right online code up your SQL query answer and have it checked.

To prep for the Maximus SQL interview it is also helpful to practice SQL problems from other consulting and professional service companies like:

Learn how Maximus' AI and Advanced Analytics can help businesses optimize operations, reduce costs, and improve outcomes!

However, if your SQL coding skills are weak, forget about going right into solving questions – refresh your SQL knowledge with this free SQL for Data Analytics course.

This tutorial covers things like filtering with LIKE and WHERE with AND/OR/NOT – both of which pop up often during Maximus SQL interviews.

### Maximus Data Science Interview Tips

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

Beyond writing SQL queries, the other types of problems tested in the Maximus Data Science Interview are:

• Probability & Statistics Questions
• Coding Questions in Python or R
• Business Sense and Product-Sense Questions
• ML Modelling Questions
• Behavioral Questions based on Maximus culture and values

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

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

• 201 interview questions sourced from FAANG (FB, Apple, Amazon, Netflix, Google)
• a crash course on Stats, ML, & Data Case Studies
• over 1000+ 5-star reviews on Amazon

Don't forget about the behavioral interview – prepare for it with this list of common Data Scientist behavioral interview questions.