10 Gartner SQL Interview Questions (Updated 2024)

Gartner employees use SQL to extract specific datasets for predictive analysis, such as identifying emerging technology trends from industry reports, as well as manage vast amounts of industry-related intelligence data, including market research and customer feedback. That is why Gartner asks SQL questions in interviews for Data Science, Analytics, and Data Engineering jobs.

Thus, to help you prepare, we've collected 10 Gartner SQL interview questions – able to solve them?

10 Gartner SQL Interview Questions

SQL Question 1: Identify "Power Users"

In Gartner, a significant factor that contributes to the overall growth of the business is the frequency of reports purchased by the customers. Power users for Gartner can be defined as customers who purchased reports more frequently than others. Write a SQL query to analyze the table that involves information about each customer’s id and their purchases, to find the customers who purchased more than 100 reports in the last six months. Also, note that customers who have purchased in the last six months but did not meet the power user criteria should not be displayed in the results.

Example Input:

Answer:

This query first filters out orders that were placed in the last six months using the WHERE clause. Then it groups the remaining rows by customer_id and counts the number of purchases for each customer using the GROUP BY and COUNT functions. Finally, it uses the HAVING clause to filter the groups by the condition that more than 100 reports must have been purchased.

To solve a super-customer analysis question on DataLemur's free online SQL coding environment, try this Microsoft Azure Cloud SQL Interview Question:

SQL Question 2: Second Highest Salary

Given a table of Gartner employee salary data, write a SQL query to find the 2nd highest salary at the company.

Gartner Example Input:

Example Output:

Test your SQL query for this problem directly within the browser on DataLemur:

Answer:

You can find a detailed solution here: 2nd Highest Salary.

SQL Question 3: What's the difference between a one-to-one and one-to-many relationship?

In database schema design, a one-to-one relationship between two entities means that each entity is linked to a single instance of the other. For example, the relationship between a car and a license plate is one-to-one because each car has only one license plate, and each license plate belongs to one car.

In contrast, a one-to-many relationship is when one entity can be associated with multiple instances of the other entity. An example of this is the relationship between a teacher and their classes - a teacher can teach multiple classes, but each class is only associated with one teacher.

SQL Question 4: Calculate Monthly Average Review Score by Product

As a data analyst at Gartner, you've been given the task to gain insights on product performance over time. Write a SQL query to calculate the average review score for each product on a monthly basis.

Regarding input data, you have access to the table, which has the following schema:

Example Input:

The expected output of your query is a table with the following format, displaying each product's average review score by month:

Example Output:

Answer:

This query uses window function to calculate the average review score partitioned by product_id and month. helps us to get the month part from the date, creating a monthly perspective. The query then groups the results by month and product_id, and sorts in ascending order.

To solve a related window function SQL problem on DataLemur's free online SQL code editor, solve this Google SQL Interview Question:

SQL Question 5: In what circumstances might you choose to denormalize a database?

There are several advantages to normalizing a database, including less redundancy, more flexibility, and better performance.

• Less Redundancy: Normalization reduces redundancy by breaking down a larger, more general table into smaller, more specific tables. This reduces the amount of data that needs to be accessed for queries.

• More Flexibility: Normalization makes it easier to modify the structure of the database, as there is less redundancy, so it allows you to make changes to one table without affecting others. This makes it easier to adapt the database to changing business needs (a very real reality at Gartner!)

• Better Performance: Normalization can improve the performance of the database by reducing the amount of data that needs to be stored and accessed in a single table. This can result in faster query times and better overall performance.

SQL Question 6: Average Duration of Consultations

With your expertise in SQL, Gartner would like you to calculate the average duration of consultations made by their clients within a particular month. Gartner, being a global research and advisory firm providing information, advice, and tools for businesses, has a table that stores all the consultation details.

Here is an example of how the table might look like:

Example Input:

You are expected to write an SQL query to return the average duration of consultations per month, and the output should be:

Example Output:

Answer:

Here is a PostgreSQL query that solves the problem:

This query works by extracting the month from each consultation date in the table. It then groups the results by month, and for each group, it calculates the average . The statement is used to sort the results in ascending order of the month.

To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating average metrics for activities of users over a time period or this Alibaba Compressed Mean Question which is similar for deriving mean values from a set of data.

SQL Question 7: When it comes to database normalization, what's the difference between 1NF, 2NF, and 3NF?

The three levels of database normalization (also known as normal forms) are:

First Normal Form (1NF):

• Each column should contain the same type of data (no mixing strings vs. integers)
• Each column in a table contains a single value (no lists or containers of data)
• Each row in the table is unique

Second Normal Form (2NF)

• It's in 1st Normal Form
• All non-key attributes are dependent on the primary key

Said another way, to achieve 2NF, besides following the 1NF criteria, the columns should also be dependent only on that table's primary key.

Third normal form (3NF) if it meets the following criteria:

• It's in 2nd Normal Form
• There are no transitive dependencies in the table.

A transitive dependency means values in one column are derived from data in another column. For example, it wouldn't make sense to keep a column called "vehicle's age" and "vehicle's manufacture date" (because the vehicle's age can be derived from the date it was manufactured).

Although there is a 4NF and 5NF, you probably don't need to know it for the Gartner interview.

SQL Question 8: Calculate Click-Through Conversion Rate

Gartner has been running digital marketing campaigns and wants to analyze how successful they've been. In the context of assessing the Click-through conversion rate from viewing a product to adding a product to the cart, provide SQL query that calculates the click-through conversion rate for each product in the catalog. Use the following table schema:

Example Input:

Example Input:

Answer:

To calculate the click-through conversion rate we're essentially calculating the ratio of 'adds to cart' to 'product views' for each product. Here's the SQL query that would do this:

In this query, we join the product views and the product adds to cart together for the same user and product where the add date is the same or after the view date. For each product, we calculate the conversion rate as the count of adds to cart divided by the count of views. The '1.0' is there to ensure we do floating point division, not integer division.

To practice a similar problem about calculating rates, try this SQL interview question from TikTok within DataLemur's online SQL code editor:

SQL Question 9: Analyze customer database and join with orders

You are given two tables, and . The table contains the customer's information, whereas the table contains the order information made by the customers. Your task is to write a SQL query that retrieves all customers and their respective total amount spent in all their orders. For the customers with no orders, display a total amount of $0.

Example Input:

Example Input:

Example Output:

Answer:

This SQL query uses a LEFT JOIN to combine the and tables. The GROUP BY clause groups the results by the customer's information. The COALESCE function is used to display $0 for the customers who haven't made any orders (this is where the would be ).

Because join questions come up frequently during SQL interviews, practice this interactive Snapchat SQL Interview question using JOINS:

SQL Question 10: What is the function of a primary key in a database?

A primary key is a column or group of columns that uniquely identifies a row in a table. For example, say you had a database of Gartner marketing campaigns data:

In this Gartner example, the CampaignID column is the primary key of the MarketingCampaigns table. The constraint ensures that no two rows have the same CampaignID. This helps to maintain the integrity of the data in the table by preventing duplicate rows.

Preparing For The Gartner SQL Interview

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. Besides solving the earlier Gartner SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like FAANG tech companies and tech startups.

Each problem on DataLemur has hints to guide you, fully explained answers along with a discussion board to see how others solved it and best of all, there's an online SQL coding environment so you can easily right in the browser your query and have it graded.

To prep for the Gartner SQL interview you can also be a great idea to practice SQL questions from other consulting and professional service companies like:

• Concentrix SQL questions
• CACI SQL questions
• SAIC SQL questions
• Booz Allen SQL questions

Explore the latest press releases and announcements from Gartner and stay up-to-date on industry developments!

But if your SQL foundations are weak, forget about jumping right into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Scientists & Analysts.

This tutorial covers SQL concepts such as CASE/WHEN/ELSE statements and working with string/text data – both of these pop up routinely during SQL interviews at Gartner.

Gartner Data Science Interview Tips

What Do Gartner Data Science Interviews Cover?

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

• Statistics and Probability Questions
• Coding Questions in Python or R
• Business Sense and Product-Sense Questions
• ML Interview Questions
• Behavioral Interview Questions centered on Gartner values & principles

How To Prepare for Gartner Data Science Interviews?

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

• 201 interview questions taken from Facebook, Google, & Amazon
• a crash course on SQL, Product-Sense & ML
• over 1000+ 5-star reviews on Amazon

Don't forget about the behavioral interview – prep for it with this list of behavioral interview questions for Data Scientists.