10 MicroStrategy SQL Interview Questions (Updated 2025)

At MicroStrategy, SQL crucial for extracting and analyzing data from vast databases for business intelligence solutions, and managing data integration from multiple sources for reporting purposes. Because of this, MicroStrategy almost always evaluates jobseekers on SQL coding questions during interviews for Data Science, Analytics, and & Data Engineering jobs.

So, to help you practice for the MicroStrategy SQL interview, we've collected 10 MicroStrategy SQL interview questions – can you solve them?

10 MicroStrategy SQL Interview Questions

SQL Question 1: Calculate Monthly Average Review Rating for Each Product

Within MicroStrategy, you are required to analyze the reviews information in order to understand product performance. Write a SQL query to calculate the monthly average review rating for each product.

Here is a sample input provided in the reviews table:

reviews Example Input

We expect the output to show the month, product_id and avg_stars (average of review stars) of each month:

Example Output

Answer:

In this instance, we don't actually need to use window functions to solve the problem.

Here is a PostgreSQL query to solve the problem:

SELECT 
    EXTRACT(MONTH FROM submit_date)::int AS mth,
    product_id AS product,
    ROUND(AVG(stars), 2 ) AS avg_stars
FROM 
    reviews
GROUP BY
    mth,
    product
ORDER BY
    mth,
    product;

This SQL query groups the data by month (extracted using the EXTRACT function) and product_id. It then calculates the average review stars for each group using the AVG function, and rounds the results to 2 decimal places.

To solve a similar window function interview problem which uses RANK() on DataLemur's free interactive coding environment, try this Amazon BI Engineer interview question:

SQL Question 2: Analyzing Software Purchase and Usage

MicroStrategy is a company that specializes in business intelligence, mobile software, and cloud-based services. You are provided with two tables, Purchases and Usage. The Purchases table contains information about the various software purchases made by customers, and the Usage table contains information about the usage statistics of these purchased software.

Your task is to write a query that will help MicroStrategy understand the most frequently used software in terms of total time spent among all the users for every purchased software to improve their customer engagement efforts. This query should return the software name, total times purchased and total time spent on the software across all purchases.

Here are the schemas for the Purchases and Usage tables:

Purchases Example Input:

Usage Example Input:

Answer:

SELECT p.software_name,
       COUNT(distinct p.purchase_id) as total_purchases,
       SUM(u.usage_time) as total_usage_time
FROM Purchases p
JOIN Usage u ON p.customer_id = u.customer_id AND p.software_name = u.software_name
GROUP BY p.software_name
ORDER BY total_usage_time DESC;

This query works by first joining the Purchases and Usage tables on the customer_id and software_name columns. This ensures that we are looking at the usage time for each purchased software per customer. It then groups the results by software_name and computes the total number of times each software is purchased (total_purchases) and the total usage time (total_usage_time) across all purchases of each software. The results are sorted in descending order of total_usage_time to get the most frequently used software at the top.

SQL Question 3: When would you use the COALESCE() function?

The COALESCE() function can be used to replace NULL values with a specified value. For instance, if you are a Data Analyst at a company and are working on a customer analytics project to identify the most engaged customers, you may have access to the following data in the microstrategy_customers table:

Before you could procede with your analysis, you would need to remove the NULLs, and replace them with the default value for email engagement (not_active), and the default sms_engagement level (not_opted_in).

To do this, you'd run the following query:

SELECT customer_id, 
COALESCE(email_engagement, "not_active") as email_engagement,
COALESCE(sms_engagement, "not_opted_in") as sms_engagement
FROM microstrategy_customers;

This would get you the following output:

SQL Question 4: Average usage time of services

Imagine you work at MicroStrategy and you're tasked with better understanding users' behaviour. To specifically understand how different services are used, you want to compute the average usage time for each service in the company's portfolio. A user logs in to use a service and logs out when finished, capturing a timestamp of both events. Can you write an SQL query that calculates the average time spent on each service by all users?

service_usage Example Input:

Example Output:

Answer:

SELECT
    service_id,
    AVG(EXTRACT(EPOCH FROM logout_time - login_time)/60) AS avg_usage_time_min
FROM 
    service_usage
GROUP BY
    service_id;

This query calculates the time difference between login_time and logout_time in minutes for each record in the service_usage table. It then groups all these time differences by service_id and computes the average. The result is the average usage time in minutes for each service.

To practice a very similar question try this interactive Snapchat Sending vs. Opening Snaps Question which is similar for calculating the time spent on activities or this Amazon Server Utilization Time Question which is similar for computing the total time of usage.

SQL Question 5: What is the purpose of the SQL constraint UNIQUE?

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A UNIQUE constraint ensures that all values in a column are different. This provides uniqueness for the column(s) and helps identify each row uniquely. Unlike primary key, there can be multiple unique constraints defined per table.

CREATE TABLE Students (   /* Create table with a single field as unique */
   ID INT NOT NULL UNIQUE
   Name VARCHAR(255)
);

CREATE TABLE Students (   /* Create table with multiple fields as unique */
   ID INT NOT NULL
   LastName VARCHAR(255)
   FirstName VARCHAR(255) NOT NULL
   CONSTRAINT PK_Student
   UNIQUE (ID, FirstName)
);

ALTER TABLE Students   /* Set a column as unique */
ADD UNIQUE (ID);
ALTER TABLE Students   /* Set multiple columns as unique */
ADD CONSTRAINT PK_Student   /* Naming a unique constraint */
UNIQUE (ID, FirstName);

SQL Question 6: Calculate The Average Rating For Each Product Per Month

In MicroStrategy, we have a product review system where customers can rate our products. We would like to calculate the average rating for each product for each month. Provide a list of products with their corresponding average ratings and the months when they were reviewed.

product_reviews Example Input:

Example Output:

Answer:

SELECT
    EXTRACT(MONTH from submit_date) AS month,
    product_id,
    AVG(stars) as avg_stars
FROM
    product_reviews
GROUP BY
    month,
    product_id;

This SQL query extracts the month from the submission date and groups the data by month and product_id. It then calculates the average rating for each product for each month using the AVG() function.

SQL Question 7: What are the similarities and difference between relational and non-relational 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 MicroStrategy, 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: Retrieve Total Web Traffic per Application Version From MicroStrategy Weblogs

Your task is to analyze MicroStrategy's weblogs, which records each user's interactions with the different versions of MicroStrategy's application. Your goal is to write a SQL query that retrieves the total number of user interactions for each version of the MicroStrategy application. Join this with the applications table to provide the context for each of these application versions.

weblogs Example Input:

applications Example Input:

Answer:

SELECT a.app_version_id, COUNT(w.log_id) AS total_traffic
FROM weblogs w
JOIN applications a ON w.app_version_id = a.app_version_id
GROUP BY a.app_version_id
ORDER BY total_traffic DESC;

This query joins the weblogs table and the applications table on the field app_version_id. The GROUP BY statement groups the data according to application version. The COUNT function counts the number of logs (user interactions) per application version, which represents the total traffic. Finally, the results are ordered in descending order, so the versions with the highest traffic are listed first.

Since joins come up so often during SQL interviews, try this interactive Snapchat Join SQL question:

SQL Question 9: Find the Total Sales and Average Profit Margin Per Category

In this question, you are an analyst at MicroStrategy. You are dealing with the 'sales' table which stores the data of all the sales transactions. The table includes information about the product, the category it belongs to, the selling price, and cost price of each product.

The task is to write a SQL query to find the total sales and average profit margin for each product category for the year 2022. The profit margin for each item is calculated as (selling price - cost price)/ selling price and it should be rounded to two decimal places. Report the total sales and average profit margin for each category in the descending order of total sales.

sales Example Input:

Example Output:

Answer:

The following is a PostgreSQL query that will solve the problem:

SELECT category, 
       SUM(selling_price) AS total_sales,
       ROUND(AVG((selling_price - cost_price)/ selling_price)::numeric, 2) AS avg_profit_margin
FROM sales
WHERE transaction_date BETWEEN '2022-01-01' AND '2022-12-31'
GROUP BY category
ORDER BY total_sales DESC;

This query first filters the data for the year 2022. It uses the SUM() function to calculate total sales and AVG() function to calculate average profit margin for each category. The ROUND() function is used to round off the profit margin to 2 decimal places.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for needing to aggregate sales data by product category or this Wayfair Y-on-Y Growth Rate Question which is similar for focusing on yearly financial analysis.

SQL Question 10: Consider unique indexes, and non-unique indexes. What are some similarities and differences?

Some similarities between unique and non-unique indexes include:

1. Both types improve the performance of SQL queries by providing a faster way to lookup the desired data.
2. Both types use an additional data structure to store the indexed data, which requires additional storage space which impacts write performance.
3. Both types of indexes can be created on one or more columns of a table.

Some differences between unique and non-unique indexes include:

1. A unique index enforces the uniqueness of the indexed columns, meaning that no duplicate values are allowed in the indexed columns. A non-unique index allows duplicate values in the indexed columns.
2. A unique index can be used to enforce the primary key of a table, but a non-unique index cannot.
3. A unique index can have a maximum of one NULL value in the indexed columns, but a non-unique index can have multiple NULLs

How To Prepare for the MicroStrategy SQL Interview

The key to acing a MicroStrategy SQL interview is to practice, practice, and then practice some more! Beyond just solving the above MicroStrategy SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Microsoft, Google, Amazon, and tech startups.

Each interview question has multiple hints, step-by-step solutions and crucially, there's an online SQL code editor so you can right in the browser run your SQL query and have it executed.

To prep for the MicroStrategy SQL interview you can also be wise to solve SQL questions from other tech companies like:

• Tableau SQL questions

• microsoft SQL questions

• Power BI SQL questions

• Looker SQL questions

However, if your SQL foundations are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this free SQL for Data Analytics course.

This tutorial covers things like sorting results with ORDER BY and CASE/WHEN statements – both of these come up frequently during SQL job interviews at MicroStrategy.

MicroStrategy Data Science Interview Tips

What Do MicroStrategy Data Science Interviews Cover?

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

• Statistics & Probability Questions
• Python or R Coding Questions
• Product Data Science Interview Questions
• ML Modelling Questions
• Behavioral Interview Questions

How To Prepare for MicroStrategy Data Science Interviews?

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

• 201 interview questions sourced from FAANG, tech startups, and Wall Street
• a crash course on Product Analytics, SQL & ML
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