# 8 Roper Technologies SQL Interview Questions (Updated 2024)

Updated on

February 14, 2024

At Roper Technologies, SQL is used often for analyzing customer and operational data, and pulling data from multiple sources to extract valuable insights for business decision-making. That's why Roper Technologies frequently asks SQL questions during interviews for Data Science, Data Engineering and Data Analytics jobs.

So, to help you study for the Roper Technologies SQL interview, here’s 8 Roper Technologies SQL interview questions – how many can you solve?

## 8 Roper Technologies SQL Interview Questions

### SQL Question 1: Calculate the Average Monthly Revenue for Each Product.

As a data analyst at Roper Technologies, you are required to do a monthly performance analysis of the company's product sales. Write an SQL query to calculate and return the average monthly revenue for each product in the year 2022. Utilize standard SQL techniques and a window function if appropriate.

Here's the structure of the table that contains information about the products sold:

##### Example Input:
sales_idproduct_idsales_datequantityprice
10150001"2022-01-15"3150.00
10269852"2022-02-28"2349.00
10350001"2022-03-20"1150.00
10469852"2022-04-30"6349.00
10550001"2022-05-15"5150.00

You need to return a result set with the following columns:

• The average revenue per month of the product. Round it to two decimal places.

Expected output:

##### Example Output:
monthproduct_idavg_monthly_revenue
150001450.00
269852698.00
350001150.00
4698522094.00
550001750.00

The following SQL query calculates the total monthly revenue for each product first, then it applies the "AVG()" function over a window partitioned by "product_id" to calculate the average monthly revenue for each product in 2022.

The inner query of the above SQL command calculates the total monthly revenue for each product in the year 2022, and the outer query calculates the average of these monthly revenues for each product. The result set is sorted by "product_id" and "month" in ascending order. This query assumes the "sales" table is not empty and has a record for each product for each month; otherwise, this query will not return those months for which there is no sales record for a product.

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

### SQL Question 2: Sales Performance Analysis in Roper Technology

Roper Technologies is a leading distributor of technical products and services. They have recently launched a new sales tracking system. As a database engineer, you need to design a database schema that holds the sales information and then write a query that gives a monthly sales report for each product. {#Question-2}

• The sales table holds the sales record for each product sold. The table has four columns:
• sales_id (integer): the unique ID for each sale
• product_id (integer): the ID of the product sold
• sales_date (date): the date of the sale
• qty (integer): the quantity of product sold
##### Example Input:
sales_idproduct_idsales_dateqty
10112301/02/202250
10245601/05/2022100
10312302/10/202275
10412302/15/2022100
10578903/05/2022200
• The product table holds the information of each product. The table has three columns:
• product_id (integer): the unique ID for each product
• product_name (string): the name of the product
• product_category (string): the category of the product
##### Example Input:
product_idproduct_nameproduct_category
123Product ACategory 1
456Product BCategory 2
789Product CCategory 3

You need to provide a report which provides the total quantity sold per product each month.

Here is the SQL query for PostgreSQL:

This SQL statement aggregates the sales tables by month and product name. It then sums up the quantity of product sold each month. The join operation combines rows from sales and product tables based on the product_id. The result is ordered by year, month and total quantity sold in descending order.

### SQL Question 3: What's an index, and what are the different types?

An index in a database is a data structure that helps to quickly find and access specific records in a table.

For example, if you had a database of Roper Technologies customers, you could create a primary index on the column.

Having a primary index on the column can speed up performance in several ways. For example, if you want to retrieve a specific customer record based on their , the database can use the primary index to quickly locate and retrieve the desired record. The primary index acts like a map, allowing the database to quickly find the location of the desired record without having to search through the entire table.

Additionally, a primary index can also be used to enforce the uniqueness of the column, ensuring that no duplicate values are inserted into the table. This can help to prevent errors and maintain the integrity of the data in the table.

### SQL Question 4: Average Production Time of Manufactured Items

Roper Technologies is a diversified technology company with various business segments, including Industrial Technology. For the Industrial Technology sector, they manufacture various items.

As an SQL professional, your task is to find out the average production time for each item being produced by the Industrial Technology segment of Roper Technologies.

Here are the tables you have with relevant data:

##### Example Input:
product_idproduct_name
1Product A
2Product B
3Product C
##### Example Input:
production_idproduct_idstart_timeend_time
10112022-09-01 9:00:002022-09-01 11:00:00
10212022-09-02 9:00:002022-09-02 12:00:00
10322022-09-01 10:00:002022-09-01 15:00:00
10432022-09-02 8:00:002022-09-02 10:30:00
10532022-09-02 11:00:002022-09-02 14:00:00

Given these tables and data, you need to calculate the average production time (in hours) for each product.

This query first calculates the difference between the end_time and start_time for each row in the production table, extracting the difference in seconds with the help of the EXTRACT function. Next, it converts the result to hours by dividing by 3600. The AVG function then calculates the average production time (in hours) for each product by grouping them with their product name from the products table.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for requiring item analysis or this Tesla Unfinished Parts Question which is similar for needing to analyze production status.

### SQL Question 5: What are the similarities and differences between correleated and non-correlated sub-queries?

A correlated sub-query is one that relies on the outer query and cannot be run independently. It uses the outer query to filter or transform data by referencing a column from it, while the outer query uses the results of the inner query. On the other hand, a non-correlated sub-query is not linked to the outer query and can be run on its own. It does not reference any columns from the outer query and is used to retrieve additional data for the outer query.

An example correlated sub-query:

This correlated subquery retrieves the names and salaries of Roper Technologies employees who make more than the average salary for their department. The subquery references the department column in the main query's FROM clause (e1.department) and uses it to filter the rows of the subquery's FROM clause (e2.department).

An example non-correlated sub-query:

This non-correlated subquery retrieves the names and salaries of Roper Technologies employees who make more than the average salary for the Data Analytics department (which honestly should be very few people since Data Analysts are awesome).

Anways, the subquery is independent of the main query and can be considered a standalone query. Its output (the average salary for the Data Analytics department) is then used in the main query to filter the rows of the table.

### SQL Question 6: Calculate the Average Spend by each Client Monthly

Roper Technologies sells a variety of technology products and services to different clients. They would like to analyze their client's buying behavior. Specifically, they are interested in knowing the average amount spent by each client every month.

##### Example Input:
purchase_idclient_idpurchase_dateproduct_idpurchase_amount
632510505/15/202225700550
135735105/23/202225700450
926389006/09/202275315300
411210506/12/202275315600
752635107/05/202225700550
##### Example Output:
mthclient_idavg_spend
5105550.00
5351450.00
6105600.00
6890300.00
7351550.00

To find out the average monthly spend by each client, we can write the following SQL query:

This SQL script groups the data by the month of the purchase date and the client id. The function is used to calculate the average purchase amount by each client in each month. The function is used to get the month from the date column. The result is then ordered by month and client id.

### SQL Question 7: What's the difference between relational and NoSQL databases?

While both types of databases are used to store data (obviously), there's some key differences in how they store and organize data.

Relational databases try to represent the world into neat little tables, with rows and columns. Non-relational (NoSQL) databases use a variety of data models to represent data, including document, key-value, columnar, and graph storage formats.

While the exact types of NoSQL databases is beyond the scope of a Data Analyst and Data Scientist SQL interview at Roper Technologies, it's good to know that companies generally choose to use NoSQL databases:

• when dealing with unstructured or semi-structured data
• when the database needs to be scaled horizontally easily
• when the data is non-relational (like storing social network data which makes more sense in a graph format)

### SQL Question 8: Analyzing Customer Purchases and Product Details

In your role at Roper Technologies, you have access to two relevant databases. One contains customer purchase records ('purchases') and the other includes detailed information about each product ('products').

A typical SQL interview question could be:

Write a SQL query to find out the total purchase amount for each product, including the product name and product category, sorted by the total purchase amount in descending order.

The sample tables would look like this:

##### Example Input:
purchase_idcustomer_idproduct_idpurchase_amount
1456100100.00
2789200300.00
312310050.00
4456300200.00
5789100150.00
##### Example Input:
product_idproduct_nameproduct_category
100Product AElectronics
200Product BFurniture
300Product CElectronics

This query joins 'purchases' and 'products' table on the common 'product_id' field. It further groups the result of this join operation by the 'product_id', 'product_name', and 'product_category', and computes the total purchase amount for each unique product using the aggregation function. The sorted result in descending order shows the products with the highest total purchase amounts at the top.

Since joins come up frequently during SQL interviews, try an interactive SQL join question from Spotify:

### How To Prepare for the Roper Technologies SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Roper Technologies SQL interview is to solve as many practice SQL interview questions as you can! In addition to solving the earlier Roper Technologies SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.

Each problem on DataLemur has multiple hints, step-by-step solutions and crucially, there is an interactive coding environment so you can right online code up your query and have it graded.

To prep for the Roper Technologies SQL interview you can also be helpful to practice interview questions from other tech companies like:

In case your SQL foundations are weak, forget about jumping right into solving questions – refresh your SQL knowledge with this DataLemur SQL Tutorial.

This tutorial covers SQL concepts such as WHERE with AND/OR/NOT and UNION vs. joins – both of which come up frequently in Roper Technologies SQL assessments.

### Roper Technologies Data Science Interview Tips

#### What Do Roper Technologies Data Science Interviews Cover?

Beyond writing SQL queries, the other question categories tested in the Roper Technologies Data Science Interview are:

• Probability & Statistics Questions
• Python or R Programming Questions
• Business Sense and Product-Sense Questions
• ML Modelling Questions
• Behavioral Interview Questions

#### How To Prepare for Roper Technologies Data Science Interviews?

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

• 201 interview questions taken from Google, Microsoft & tech startups
• a crash course covering Product Analytics, SQL & ML
• over 900+ reviews on Amazon & 4.5-star rating