9 Ventas SQL Interview Questions (Updated 2024)

Ventas employees use SQL for analyzing and managing real estate investment portfolios, including tracking property performance and identifying opportunities for growth. It is also used for forecasting trends in healthcare and senior living, such as predicting demand for senior housing and analyzing market competition, which is why Ventas asks SQL questions in interviews for Data Science, Analytics, and Data Engineering jobs.

So, to help you prepare for the Ventas SQL interview, here's 9 Ventas SQL interview questions in this blog.

9 Ventas SQL Interview Questions

SQL Question 1: Sales Analysis Using Window Functions

As a data analyst at Ventas, you have been provided with a large set of sales data. You are asked to analyze the data in order to identify key trends and patterns. Specifically, your task is to write a query to find out the cumulative sales for each product in each month.

The sales data is stored in a table named , which has the following structure:

Example Input

Your output should include the product id, the month of sale, and the cumulative sale for that product in that month.

The expected format of the output is as follows:

Example Output

Answer:

This query first groups the sales data by product_id and month_of_sale (after truncating the date to month), then calculates the sum of sales for each group (price * quantity). The OVER clause is used along with PARTITION BY to create a window grouped by product_id. Within each window, rows are ordered by month_of_sale. The sum function then calculates a cumulative sum within each window.

p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur

SQL Question 2: Employee Salaries Higher Than Their Manager

Given a table of Ventas employee salary data, write a SQL query to find all employees who earn more money than their own boss.

Ventas Example Input:

Example Output:

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

Code your solution to this problem directly within the browser on DataLemur:

Answer:

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 hard to understand, you can find a step-by-step solution here: Employees Earning More Than Managers.

SQL Question 3: What's a database view, and what's their purpose?

Database views are created to provide customized, read-only versions of your data that you can query just like a regular table. So why even use one if they're just like a regular table?

Views are useful for creating a simplified version of your data for specific users, or for hiding sensitive data from certain users while still allowing them to access other data.

SQL Question 4: Sales Data Analysis

Ventas Inc. is a globally operating company that deals with multiple products and a large customer base. The company wants you to provide insights from their sales data.

The sales department maintains three databases. The first database keeps records of all its products with unique product_id, product_name, and product_price.

The second database maintains the details of their customers, with unique customer_id and other details like customer_name, customer_address, and contact_detail.

The third and final database is used for keeping records of all the sales transactions, which include unique transaction_id, transaction_date (in Date/Time format), product_id, customer_id and quantity.

Here are the sample tables:

Example Input:

Example Input:

Example Input:

The companies wishes you to answer the following question:

For the month of June 2022, who is the customer that has the maximum cumulative sales in terms of the dollar amount? Provide both the maximum sales amount and customer details.

Answer:

This problem requires joining all three tables, grouping by customer and finally ordering by the total spent to find the customer that spent the most. Here is the PostgreSQL query:

This query first joins the three tables on their relations. It then filters the records for the month of June in 2022. The total sales amount is calculated by summing the product price times the quantity sold for each customer and the result is grouped by customer. The records are then ordered by the total sales amount in descending order and the top record is returned.

It's worth noting an alternative strategy would have been to first filter the transactions table to only include June transactions to reduce the size of the data the join operations have to process. For larger tables, this may be more efficient.

SQL Question 5: Can you describe the concept of a database index and the various types of indexes?

In a database, an index is a data structure that improves the speed of data retrieval operations on a database table at the cost of additional writes and the use of more storage space to maintain the index data structure.

There are several types of indexes that can be used in a database:

1. Primary index: a unique identifier for each row in a table and is used to access the row directly.
2. Unique index: used to enforce the uniqueness of the indexed columns in a table. It does not allow duplicate values to be inserted into the indexed columns.
3. Composite index: is created on multiple columns of a table. It can be used to speed up the search process on the combination of columns.
4. Clustered index: determines the physical order of the data in a table. There can be only one clustered index per table.
5. Non-clustered index: does NOT determine the physical order of the data in a table. A table can have multiple non-clustered indexes.

SQL Question 6: Calculate the Click-Through-Rate for Ventas Ads

Ventas is a company that heavily relies on online marketing. They have two major tables in their database. The table containing records of each ad with its respective ID, and a table, recording each click on their ads.

On their table, each row is an ad with a unique ad_id. On the table, each row represents a click event, which is tagged to an ad_id and the date time of the click.

The tables are as follows:

Example Input:

Example Input:

Your task is to write a SQL query that calculates the overall click-through rate (CTR) for Ventas ads. The click-through rate is defined as the total number of click events per ad over the total number of ads.

Answer:

Below is the SQL query in PostgreSQL to solve this:

This SQL statement first counts the total number of clicks per ad, and then divides it by the total number of ads. The resulting column 'click_through_rate' should give the click through rate for each ad.

Please note that the '::float' is used to typecast the integer to float for getting a precise division result.

To practice a similar problem on DataLemur's free interactive SQL code editor, attempt this SQL interview question asked by Facebook:

SQL Question 7: Can you describe the different types of joins in SQL?

In SQL, a join is used to combine rows from different tables based on a shared key or set of keys, resulting in a single merged table of data.

There are four distinct types of JOINs: , , , and .

(INNER) JOIN: Retrieves records that have matching values in both tables involved in the join.

LEFT (OUTER) JOIN: Retrieves all the records/rows from the left and the matched records/rows from the right table.

RIGHT (OUTER) JOIN: Retrieves all the records/rows from the right and the matched records/rows from the left table.

FULL (OUTER) JOIN: Retrieves all the records where there is a match in either the left or right table.

SQL Question 8: Find the Average Price of Sold Properties per State

Ventas is a real estate company dealing in many different types of properties in different states. They are interested in analyzing their sales data at a state level. Write a SQL query to determine the average selling price for each type of property sold in each state in the last year.

Example Input:

Answer:

In the above query, the WHERE clause is used to filter out sales that occurred in the current year. will return the first day of the current year.

The GROUP BY clause is used to group the data by state and type of property. After that, AVG() function is applied to calculate the average selling price for each combination of state and property type.

Example Output:

The output contains each combination of state and property type, along with their average selling price. The result is rounded to the nearest whole number.

SQL Question 9: Analyze Total Payments Per Customer

You are given two tables - and . The table consists of all the information about the customers while the table contains all the payments made by the customers. Your task is to write a SQL query that will find the total payment for each customer by joining the and tables.

Table:

Table:

Answer:

Here is the SQL query that could be used to solve this problem:

This query first joins the and tables on the . It then groups the results by , , and . Finally, it sums up the for each group (which represents each customer) to find the total payment amount for each customer.

Because joins come up so often during SQL interviews, practice this interactive Snapchat JOIN SQL interview question:

Ventas SQL Interview Tips

The best way to prepare for a Ventas SQL interview is to practice, practice, practice. In addition to solving the earlier Ventas SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.

Each problem on DataLemur has hints to guide you, step-by-step solutions and most importantly, there is an interactive SQL code editor so you can right online code up your SQL query answer and have it graded.

To prep for the Ventas SQL interview it is also a great idea to practice interview questions from other insurance companies like:

• American Equity SQL questions
• Brown & Brown SQL questions
• Medical Mutual SQL questions
• Brown & Brown SQL questions

Dive into the[ latest news and updates from Ventas](https://ir.ventasreit.com/news/default.aspx simple) and discover how they're shaping the future of healthcare real estate!

However, if your SQL foundations are weak, forget about jumping right into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.

This tutorial covers SQL topics like filtering data with WHERE and using wildcards with LIKE – both of these show up frequently in SQL job interviews at Ventas.

Ventas Data Science Interview Tips

What Do Ventas Data Science Interviews Cover?

In addition to SQL interview questions, the other types of questions to practice for the Ventas Data Science Interview are:

• Statistics and AB Testing Questions
• Coding Questions in Python or R
• Product-Sense Questions
• Machine Learning Questions
• Behavioral Interview Questions focussed on Ventas values & principles

How To Prepare for Ventas Data Science Interviews?

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

• 201 interview questions taken from tech companies like Google & Microsoft
• a refresher covering Stats, ML, & Data Case Studies
• over 1000+ reviews on Amazon & 4.5-star rating

Also focus on the behavioral interview – prepare for that with this guide on acing behavioral interviews.