9 Pegasystems SQL Interview Questions (Updated 2024)
Pegasystems frequently asks SQL questions in interviews for Data Analyst, Data Science, and BI jobs. To help you prepare for the Pegasystems SQL interview, this blog covers 9 Pegasystems SQL interview questions – can you answer each one?
9 Pegasystems SQL Interview Questions
SQL Question 1: Calculate Average Monthly Product Ratings
Given a table called , write a SQL query to calculate the average star rating for each product on a monthly basis. The table has the following columns: , , , , and .
The output should be a table with columns: , , and .
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 1 | 234 | 2022-01-07 | 1001 | 3 |
| 2 | 235 | 2022-01-07 | 1001 | 4 |
| 3 | 236 | 2022-01-07 | 1002 | 2 |
| 4 | 237 | 2022-02-08 | 1002 | 5 |
| 5 | 238 | 2022-02-08 | 1001 | 4 |
| 6 | 239 | 2022-03-09 | 1001 | 1 |
| 7 | 240 | 2022-03-10 | 1002 | 3 |
Example Output:
| mth | product | avg_stars |
|---|---|---|
| 1 | 1001 | 3.5 |
| 1 | 1002 | 2 |
| 2 | 1001 | 4 |
| 2 | 1002 | 5 |
| 3 | 1001 | 1 |
| 3 | 1002 | 3 |
Answer:
This SQL query extracts the month from , and then groups the data by month and product. For each group, calculates the average star rating, which is selected in the result. The clause makes sure the result is ordered by month and then product.
To practice a related window function SQL problem on DataLemur's free interactive coding environment, solve this Amazon SQL Interview Question:
SQL Question 2: Filtering Customer Records for a Specific Product
As part of the sales team at Pegasystems, you have been tasked with identifying key metrics about our customers. Specifically, you are interested in customers who have purchased our Product X within the last year and are located in the United States. Additionally, you only want this information for customers who have an 'active' status. Can you write a query to filter the customer records database to meet these conditions?
Example Input:
| customer_id | first_name | last_name | country | status |
|---|---|---|---|---|
| 123 | John | Doe | United States | Active |
| 456 | Jane | Smith | Canada | Inactive |
| 789 | Sarah | Johnson | United States | Active |
| 112 | Michael | Brown | Germany | Active |
| 235 | Emily | Davis | United States | Inactive |
Example Input:
| order_id | customer_id | product | order_date |
|---|---|---|---|
| 1001 | 123 | Product X | 01/20/2022 |
| 1002 | 456 | Product Y | 03/12/2022 |
| 1003 | 789 | Product X | 07/30/2021 |
| 1004 | 112 | Product X | 08/05/2021 |
| 1005 | 235 | Product Y | 09/20/2021 |
Answer:
The following PostgreSQL query can be used to meet these conditions:
This query joins the and tables on . It then applies a clause to filter for customers who are active, located in the United States, and have ordered Product X within the last year. The output of this query would be a table of qualifying customers from the United States who have ordered Product X in the last year.
Execution of the given query with the provided sample data would produce no results as there is no record that satisfies all the conditions. To test the query, you can modify the sample input data accordingly. For example, change the 'order_date' of the Product X purchased by an active customer from the United States.
SQL Question 3: Can you explain the purpose of the constraint and give an example of when you might use it?
The CHECK constraint is used to set a rule for the data in a column. If a row is inserted or updated and the data in the column does not follow the rule specified by the CHECK constraint, the operation will be unsuccessful.The CHECK constraint is often used in conjunction with other constraints, such as NOT NULL or UNIQUE.
You might consider implementing the CHECK constraint in your database if you want to ensure that certain data meets specific conditions. This can be helpful for maintaining the quality and reliability of your data.
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 4: Average Support Tickets Closed per Month
For the company Pegasystems which provides business process management software, we could have a question around their Support Tickets system. How about we find out the average number of Support Tickets closed by each support agent on a monthly basis, for each year?
Assuming, there is a table with fields , , , (, , etc), and .
Example Input:
| ticket_id | agent_id | close_date | product_id | status |
|---|---|---|---|---|
| 201 | 14 | 06/12/2019 00:00:00 | 546 | closed |
| 202 | 27 | 06/15/2019 00:00:00 | 781 | closed |
| 203 | 14 | 06/25/2019 00:00:00 | 546 | closed |
| 204 | 14 | 07/02/2019 00:00:00 | 781 | open |
| 205 | 27 | 07/05/2019 00:00:00 | 546 | closed |
We want to output the average number of tickets closed per month by each agent in each year.
Example Output:
| year | agent_id | avg_tickets_closed |
|---|---|---|
| 2019 | 14 | 1.5 |
| 2019 | 27 | 1.0 |
The SQL Query to obtain this would be:
Answer:
In the inner subquery, the total number of tickets closed per month by each agent every year are counted. Then, the average counts per month for every year are calculated in the outer query. The overall result is the average number of tickets closed per month by each agent in each year.
SQL Question 5: What's the difference between and ?
Both and are used to combine the results of two or more SELECT statements into a single result set.
However, only includes one instance of a duplicate, whereas includes duplicates.
SQL Question 6: Find Clients With Specific Email Domain
As a part of Pegasystems data team, we often need to filter out our client records and analyze the client data based on different conditions. Recently we wanted to run an email campaign targeting all clients with emails from a specific domain, 'pega.com'. Please write a SQL query that fetches all records from the client database where the email address of the client ends with '@pega.com'.
Example Input:
| client_id | name | signup_date | product_subscription | |
|---|---|---|---|---|
| 101 | John Doe | johndoe@pega.com | 06/08/2022 | Advanced |
| 102 | Jane Doe | janedoe@gmail.com | 06/10/2022 | Basic |
| 103 | Frank White | frankwhite@pega.com | 06/18/2022 | Premium |
| 104 | Alice Smith | alicesmith@pega.com | 07/26/2022 | Advanced |
| 105 | Bob Johnson | bob_johnson@yahoo.com | 07/05/2022 | Premium |
Example Output:
| client_id | name | signup_date | product_subscription | |
|---|---|---|---|---|
| 101 | John Doe | johndoe@paga.com | 06/08/2022 | Advanced |
| 103 | Frank White | frankwhite@pega.com | 06/18/2022 | Premium |
| 104 | Alice Smith | alicesmith@pega.com | 07/26/2022 | Advanced |
Answer:
This query will filter out the rows from the table, selecting only the clients whose email addresses end with '@pega.com'. The '%' symbol is a wildcard character in SQL representing zero or more characters. The usage of the symbol before '@pega.com' ensures that any character sequence preceding '@pega.com' in the email column is matched. Hence, this query will return all clients whose email domain is 'pega.com'.
SQL Question 7: What are the benefits of normalizing a database?
Database normalization is a good idea to implement because it can reduce redundancy which can improve performance and database flexibility.
By dividing larger tables into smaller, more modular and specific tables which are linked via foreign keys, this can usually improve the speed of some queries because it minimizes the amount of random data the query has to sift through. However, it's not always 100% true that there is a query speed-up, because joins are an expensive operation.
Nonetheless, by reducing redundancy, besides improved performance you also get more database flexibility. By making tables more modular and reducing overlap, you're able to more easily, since one table can be changed more effortlessly without affecting others. This makes it easier to adapt the database schema to Pegasystems's evolving business needs.
SQL Question 8: Calculate Average Sales and Rounded Commission
Pegasystems Inc.'s sales department wants to evaluate the performance of their sales representatives. They are interested in calculating the average sales and the rounded commission for each sales representative. The commission is calculated as 10% of the total sales, and it must be rounded to the nearest whole number.
Assume you have the following table:
Example Input:
| sales_rep_id | sales_amount |
|---|---|
| 101 | 5000 |
| 102 | 4000 |
| 103 | 5500 |
| 101 | 3500 |
| 102 | 6200 |
| 103 | 4500 |
Expected output:
Example Output:
| sales_rep_id | average_sales | rounded_commission |
|---|---|---|
| 101 | 4250.00 | 425 |
| 102 | 5100.00 | 510 |
| 103 | 5000.00 | 500 |
Answer:
Here's the SQL query that calculates the average sales and rounded commission for each sales representative:
This query first groups the sales by each sales representative using the clause. It then calculates the average sales amount of each representative using the function. The commission is calculated as 10% of the average sales amount, which is then rounded to the nearest whole number using the function. The result is a table with the sales representative id, their average sales, and their rounded commission.
To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating sales performance or this Amazon Average Review Ratings Question which is similar for calculating average values.
SQL Question 9: Retrieve Monthly Active Users (MAUs)
Given a table that records the timestamp () of every action performed by each user () in the Pegasystems app, write a PostgreSQL query to determine the monthly active users (MAUs) for the first half of 2022 (January - June). An active user in a given month is a user who has performed at least one action in that month.
Example Input
| activity_id | user_id | timestamp |
|---|---|---|
| 1 | 123 | 01/07/2022 10:15:00 |
| 2 | 456 | 02/01/2022 15:30:00 |
| 3 | 123 | 03/20/2022 09:45:00 |
| 4 | 789 | 02/11/2022 08:00:00 |
| 5 | 123 | 06/30/2022 12:30:00 |
| 6 | 456 | 02/15/2022 14:22:00 |
| 7 | 789 | 06/06/2022 11:11:00 |
| 8 | 123 | 04/30/2022 22:00:00 |
| 9 | 456 | 05/15/2022 20:19:00 |
| 10 | 789 | 01/01/2022 00:01:00 |
Example Output
| month | year | maus |
|---|---|---|
| 1 | 2022 | 2 |
| 2 | 2022 | 2 |
| 3 | 2022 | 1 |
| 4 | 2022 | 1 |
| 5 | 2022 | 1 |
| 6 | 2022 | 2 |
Answer:
In the above SQL command, we make use of the function to divide the timestamp into year and month. Then we use to count all the unique active users for each month. The clause allows us to limit our search to the first half of 2022. Finally, we 'GROUP BY' both month and year, and order our result by the same. This provides us with the required monthly active users for the first half of 2022.
Pegasystems 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.
In addition to solving the above Pegasystems SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Google, Uber, and Microsoft.
Each interview question has hints to guide you, step-by-step solutions and best of all, there is an online SQL coding environment so you can right in the browser run your SQL query answer and have it graded.
To prep for the Pegasystems SQL interview you can also be a great idea to practice SQL questions from other tech companies like:
However, if your SQL foundations are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.
This tutorial covers things like how window functions work and WHERE vs. HAVING – both of which pop up routinely during SQL interviews at Pegasystems.
Pegasystems Data Science Interview Tips
What Do Pegasystems Data Science Interviews Cover?
Beyond writing SQL queries, the other types of questions to prepare for the Pegasystems Data Science Interview are:
- Stats Interview Questions
- Python Pandas or R Coding Questions
- Analytics and Product-Metrics Questions
- ML Modelling Questions
- Behavioral & Resume-Based Questions
How To Prepare for Pegasystems Data Science Interviews?
The best way to prepare for Pegasystems Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from FAANG, tech startups, and Wall Street
- A Refresher on Stats, ML, & Data Case Studies
- Amazing Reviews (900+ reviews, 4.5-star rating)