10 AspenTech SQL Interview Questions (Updated 2024)

Updated on

March 1, 2024

At AspenTech (part of Emerson Electric), SQL is used often for analyzing process manufacturing data and managing supply chain databases. Because of this, AspenTech almost always asks SQL questions during interviews for Data Science and Data Engineering positions.

As such, to help you prepare for the AspenTech SQL interview, we've collected 10 AspenTech SQL interview questions – can you solve them?

10 AspenTech SQL Interview Questions

SQL Question 1: Analyze Product Usage

AspenTech is a process optimization software company. Suppose you're given a table called that keeps track of the usage data of their products. Every time a user logs into a product, a new record is created in the table with the current timestamp. The table has the following columns:

  • log_id: An identifier for the log entry
  • user_id: An identifier for the user
  • product_id: An identifier for the product
  • login_timestamp: The timestamp when the user logged into the product

As an interview question, can you write a SQL query to determine the average number of daily logins for each product, ordered by the product with the highest average daily logins to the product with the lowest?

Pay attention to , it contains both the date and time information. The daily logins should be counted based on the date information not time.

Example Input:
1107/01/2022 08:00:001
2207/1/2022 09:00:001
3307/01/2022 10:00:002
4407/01/2022 11:00:002
5507/02/2022 08:00:001
6107/02/2022 09:00:001
7207/02/2022 10:00:002
8307/02/2022 11:00:002
Example Output:


The SQL query can be written using the function to extract the date from the , and the function inside an clause to create a window that computes the average number of daily logins for each product.

This query first groups the login records by product and date, counting the number of logins for each group. Then, for each product, it averages the daily login counts. Finally, it orders the products by the average daily logins from highest to lowest.

To practice a similar window function interview problem which uses RANK() on DataLemur's free online SQL code editor, solve this Amazon SQL Interview Question: Amazon Highest-Grossing Items SQL Analyis Question

SQL Question 2: Calculate the Average Usage of a Software Product

As an analyst at AspenTech, a company that creates software to optimize asset performance in industries such as energy, chemicals, and engineering, you are tasked with monitoring the utilization of their software products. Write a SQL query to find the average daily usage duration (in hours) of each software product.

Example Input:
usage_iduser_idusage_dateproduct_idusage_duration (hours)
10140101/03/2023 00:00:0020015
10256701/03/2023 00:00:0020013
10335001/04/2023 00:00:0020026
10429401/06/2023 00:00:0020012
10556701/07/2023 00:00:0020038
Example Output:
product_idavg_usage_duration (hours)


This query first groups the rows in the table by using the GROUP BY clause. For each group of usage records belonging to the same product, it then calculates the average of their usage durations using the AVG function, which returns the average value of a numeric column.

The result set includes each unique from the table, along with the corresponding average daily usage duration (in hours).

To practice a very similar question try this interactive Microsoft Teams Power Users Question which is similar for analysing software product usage or this Amazon Server Utilization Time Question which is similar for calculating total usage duration.

SQL Question 3: Can you define what a database index is, and give some examples of different types of indexes?


A database index is a way to optimize the performance of a database by reducing the amount of data that needs to be searched to retrieve a record.

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

  1. Primary index: a unique identifier is used to access the row directly.
  2. Unique index: used to enforce the uniqueness of the indexed columns in a table.
  3. Composite index: created on multiple columns of a table, is used to speed up the search process for multiple columns
  4. Clustered index: determines the physical order of the data in a table

For a concrete example, say you had a table of AspenTech customer payments with the following columns: payment_id, customer_id, payment_amount, and payment_date.

Here's what a clustered index on the column would look like:

A clustered index on the column would determine the physical order of the records in the table based on the . This means that the records with the earliest values would be stored together physically in the table, followed by records with later payment_date values.

Having a clustered index on the column can speed up queries that filter or sort the data based on the payment_date, as the records are already physically sorted in the table. For example, if you want to retrieve all the payments made in the month of January, the database can use the clustered index to quickly locate and retrieve the desired records without having to search through the entire table.

AspenTech SQL Interview Questions

SQL Question 4: Analyze click-through rates of advertisements in AspenTech

Given two tables, and , where the table records each time a user clicks on an advertisement for a product, and the table keeps track of each product bought by users. Product conversion rate is defined as the number of products bought per click on the related advertisement.

Write a SQL query to find out the product conversion rate for the company, sorted by the conversion rate in descending order.

Example Input:
110106/08/2022 00:00:00pro1
210206/08/2022 00:01:00pro2
310306/10/2022 00:00:00pro1
410106/10/2022 00:01:00pro2
510206/18/2022 00:00:00pro1
Example Input:
110106/09/2022 00:00:00pro1
210206/10/2022 00:00:00pro2
310106/12/2022 00:00:00pro1
410206/18/2022 00:00:00pro2
510306/18/2022 00:00:00pro1


This query calculates the conversion rate by counting the number of purchases and dividing it by the number of clicks for each product. We're using a here to ensure that we account for all clicks, even those that did not lead to a purchase (in which case the count of purchase_id would be 0).

To practice a related SQL problem on DataLemur's free online SQL coding environment, solve this Facebook SQL Interview question: Facebook Click-through-rate SQL Question

SQL Question 5: Can you describe the meaning of a constraint in SQL in layman's terms?

Think of SQL constraints like the rules of a game. Just like a game needs rules to keep things fair and fun, a database needs constraints to keep things organized and accurate.

There are several types of SQL constraints like:

NOT NULL: This constraint is like a bouncer at a nightclub - it won't let anything NULL through the door. UNIQUE: This constraint is like a VIP list - only special, one-of-a-kind values get in. PRIMARY KEY: This constraint is like an elected official - it's made up of NOT NULL and UNIQUE values and helps identify each row in the table. FOREIGN KEY: This constraint is like a diplomatic ambassador - it helps establish relationships between tables. CHECK: This constraint is like a referee - it makes sure everything follows the rules. DEFAULT: This constraint is like a backup plan - it provides a default value if no other value is specified.

So, whether you're playing a game or organizing a database, constraints are an important part of the process!

SQL Question 6: Extract Customer Information

As an analyst at AspenTech, you have been asked to filter down customers from the 'customers' database who have 'aspen' in their company name. You are required to use the SQL keyword LIKE for this operation.

The 'customers' database is described by the following table:

Example Input:
1001AspenTech SolutionsJohn Doe123 Aspen StAspen81611
1002TechAspen IndustriesJane Doe456 Elm StSpringfield62704
1003Pine SolutionsJimmy Dean789 Pine StShelbyville35143
1004AspenSoftMichael Scott101 Software AveScranton18505
1005RedgateJohn Smith102 Software AveScranton18505

Your task is to write a PostgreSQL query that filters and returns the customer records that contain 'aspen' (case-insensitive) in the company name.


This query will return all records from the 'customers' table where the company name contains the string 'aspen', regardless of case. The '%' before and after the pattern '%aspen%' is a wildcard that matches any sequence of characters. The function LOWER is used to make the comparison case-insensitive.

Example Output:
1001AspenTech SolutionsJohn Doe123 Aspen StAspen81611
1002TechAspen IndustriesJane Doe456 Elm StSpringfield62704
1004AspenSoftMichael Scott101 Software AveScranton18505

SQL Question 7: What is the function of a primary key in a database?

The primary key of a table is a column or combination of columns that serves to uniquely identify each row in the table. To define a primary key in a SQL database, you can use the constraint.

For instance, consider a table of :

In this example, the column is the primary key of the AspenTech employees table.

Primary keys are important in databases for several reasons:

  • Uniqueness: A primary key is used to uniquely identify each row in a table. This means that no two rows in the table can have the same primary key value. This is important because it helps to ensure the accuracy and integrity of the data in the table.
  • Non-nullability: A primary key is typically defined as a non-null column, which means that it cannot contain a null value. This helps to ensure that every row in the table has a unique identifier.
  • Relationship-building: Primary keys are often used to establish relationships between tables in a database. For example, you might use a primary key to link the table to the table.

SQL Question 8: Identify Most Valuable Customers

As a data analyst at AspenTech, your manager has asked you to identify the "Most Valuable Customers" in the last quarter. A valuable customer is defined as one who has spent the most on AspenTech's products in the last quarter (90 days period). In addition to the customer name, you should also identify the total amount they have spent within the time period.

You have been provided with two tables, and .

The table has the following format:


The table has the following format:


Please write a SQL query that provides a list of AspenTech's "Most Valuable Customers" in the last quarter.


This query first joins the and tables on the field. It then filters out any transactions that did not occur in the last quarter. The clause groups the results by customer, and the function calculates the total amount spent by each customer. Finally, the results are ordered by in descending order, which gives a list of the most valuable customers.

Because joins come up so often during SQL interviews, try this interactive Snapchat Join SQL question: Snapchat SQL Interview question using JOINS

SQL Question 9: Calculate Adjusted Production Rate

Assume AspenTech has an oil production chain that includes oil wells. Each well has varying production rates per day due to geological factors, machinery performance, or human factors, among other things.

You are provided with a database that records the daily oil production output of each oil well (in barrels per day). These daily outputs are recorded at each well during the working days (Monday to Friday) of each month over the course of a year.

For financial and operational performance analysis, the company wants to calculate an adjusted monthly production rate that captures the standard deviation and variance in the daily production rate, as well as the absolute difference between the maximum and minimum production rates observed in a month.

The table named contains the data. It contains four columns:

  1. (integer): a unique identifier for each data entry.
  2. (integer): a unique identifier for each oil well.
  3. (date): the date when the oil output was recorded.
  4. (float): the number of barrels of oil produced per day.
Example Input:

The company wants a query to calculate for each well, in each month:

  1. The adjusted production rate, calculated as and rounded to 2 decimal places.
  2. The month and year of production.
Example Output:


This query first uses the function to create a new column for each oil well's production month and year. It then calculates the required mathematical expressions within the function before grouping the result by month, year, and .

To practice a very similar question try this interactive Google Odd and Even Measurements Question which is similar for requiring analysis of fluctuating readings or this Twitter Tweets' Rolling Averages Question which is similar for needing to calculate a rolling rate related to production activity.

SQL Question 10: Could you describe the function of UNION in SQL?


is used to combine the output of multiple statements into one big result!

For a concrete example, say you were a Data Analyst supporting the Sales Analytics team at AspenTech, and data on potential sales leads lived in both Salesforce CRM and Hubspot. To write a query to analyze leads created after 2023 started, across both CRMs, you could use in the following way:


How To Prepare for the AspenTech SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the AspenTech SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the earlier AspenTech SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Facebook, Google and unicorn tech startups. DataLemur Questions

Each interview question has multiple hints, detailed solutions and crucially, there is an interactive SQL code editor so you can right online code up your SQL query and have it executed.

To prep for the AspenTech SQL interview it is also wise to solve SQL questions from other tech companies like:

But if your SQL skills are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this interactive SQL tutorial.

DataLemur SQL tutorial

This tutorial covers SQL concepts such as handling dates and filtering data with WHERE – both of these come up frequently during AspenTech interviews.

AspenTech Data Science Interview Tips

What Do AspenTech Data Science Interviews Cover?

In addition to SQL interview questions, the other types of questions tested in the AspenTech Data Science Interview are:

  • Probability & Statistics Questions
  • Coding Questions in Python or R
  • Data Case Study Questions
  • ML Modelling Questions
  • Behavioral & Resume-Based Questions

AspenTech Data Scientist

How To Prepare for AspenTech Data Science Interviews?

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