At Udemy, SQL is often used for analyzing user course engagement data and generating business intelligence reports to guide strategic decision-making. For this reason Udemy typically asks SQL problems in interviews for Data Science, Data Engineering and Data Analytics jobs.
As such, to help you practice for the Udemy SQL interview, this blog covers 10 Udemy SQL interview questions – how many can you solve?
Given the provided tables and below, write a SQL PostgreSQL query to determine the top 5 users who have purchased the highest number of premium courses in the past year. A premium course is defined as a course with a cost above $50.
user_id | username |
---|---|
1 | john_doe |
2 | jane_smith |
3 | mary_jane |
4 | peter_parker |
5 | clark_kent |
course_id | course_title | course_cost |
---|---|---|
1000 | Data Science course | $60 |
2000 | Basic Python course | $20 |
3000 | Advanced Java course | $70 |
4000 | Web Development course | $30 |
5000 | Machine Learning course | $80 |
purchase_id | user_id | course_id | purchase_date |
---|---|---|---|
9001 | 1 | 1000 | 06/08/2021 |
9002 | 2 | 2000 | 06/10/2021 |
9003 | 3 | 3000 | 06/18/2021 |
9004 | 4 | 4000 | 07/26/2021 |
9005 | 5 | 5000 | 07/05/2021 |
9006 | 3 | 1000 | 09/18/2021 |
9007 | 1 | 5000 | 10/26/2021 |
9008 | 2 | 3000 | 11/05/2021 |
9009 | 3 | 5000 | 12/14/2021 |
The PostgreSQL query could look something like this:
This query joins the , , and tables together by their respective ID fields. It then filters for only premium courses (which are defined as those with a cost above $50) purchased within the past year. The results are grouped by user, and the number of premium courses purchased by each user is counted. The final query is ordered in descending order of the number of premium courses purchased (from highest to lowest), and in ascending order of username (from A to Z), and limited to the top 5 users.
To solve a similar VIP customer analysis question on DataLemur's free online SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:
As an analyst at Udemy, you are being asked to analyze the dataset of reviews to monitor course performance. Your task is to write a SQL query that calculates the average rating (stars) for each course (product_id) per month. The reviews table has details on each review submitted, with its date of submission. Assume that all dates in 'submit_date' are in the format 'MM/DD/YYYY HH24:MI:SS'.
To this end, you would be given a table with the following structure:
review_id | user_id | submit_date | product_id | stars |
---|---|---|---|---|
6171 | 123 | 06/08/2022 00:00:00 | 50001 | 4 |
7802 | 265 | 06/10/2022 00:00:00 | 69852 | 4 |
5293 | 362 | 06/18/2022 00:00:00 | 50001 | 3 |
6352 | 192 | 07/26/2022 00:00:00 | 69852 | 3 |
4517 | 981 | 07/05/2022 00:00:00 | 69852 | 2 |
You are being asked to output a table as follows, ordered by the month and then the product:
mth | product | avg_stars |
---|---|---|
6 | 50001 | 3.50 |
6 | 69852 | 4.00 |
7 | 69852 | 2.50 |
Where 'mth' is the month when the reviews were submitted, 'product' is the product_id of the course, and 'avg_stars' is the average rating of reviews for the course in that month (rounded up to 2 decimal places).
A PostgreSQL query that solves the problem:
This query uses the function to get the month from and then groups by both the month and the . It calculates the (average) of for each group and rounds it to 2 decimal places with the function. The output is ordered by the month and then by the product_id.
p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur
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 Udemy marketing campaigns data:
In this Udemy 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.
As a data analyst at Udemy, you need to track how well courses are being received by users. For this, you decide to create a report on the average rating received by each course per month. You also want to include the total number of enrollments and total revenue for each course in the same period.
From your databases, you have two main tables you can work with: and . The table lists all available courses with their pricing info. The table documents every course enrollment with the associated user, course, enrollment date, and reviews.
Given the following tables, write a query to calculate the average rating, total enrollments, and total revenue per month for each course.
course_id | course_name | price |
---|---|---|
101 | Python for Data Science | 100 |
102 | Advanced SQL | 120 |
103 | Digital Marketing | 80 |
enrollment_id | user_id | course_id | enrollment_date | rating |
---|---|---|---|---|
1001 | 500 | 101 | 2022-06-22 | 4 |
1002 | 501 | 101 | 2022-06-23 | 5 |
1003 | 502 | 102 | 2022-07-02 | 3 |
1004 | 503 | 102 | 2022-08-15 | 4 |
1005 | 504 | 103 | 2022-08-22 | 2 |
This query first joins the and tables on the column. It then groups the enrollments by month and course, using the function to get the month of the enrollment date. For each group, it calculates the average rating, total number of enrollments, and total revenue (number of enrollments times course price). The final result is then sorted by month and course name.
To explain the difference between a primary key and foreign key, let's inspect employee data from Udemy's HR database:
:
+------------+------------+------------+------------+ | employee_id| first_name | last_name | manager_id | +------------+------------+------------+------------+ | 1 | Aubrey | Graham | 3 | | 2 | Marshal | Mathers | 3 | | 3 | Dwayne | Carter | 4 | | 4 | Shawn | Carter | | +------------+------------+------------+------------+
In this table, could be a primary key. It is unique for each row in the table and cannot contain null values.
could be a foreign key. It references the of the manager of each employee in the table, establishing a relationship between the employees and their managers. This foreign key allows you to easily query the table to find out who a specific employee's manager is, or to find out which employees report to a specific manager.
It is also possible for a table to have multiple foreign keys that reference different primary keys in other tables. For example, the table could have additional foreign keys for the of the department where each employee works, and the l of the location where each employee is based.
Given the following tables and , where the table has the id of the course and the course title, and table has the rating submitted by the users, write a SQL query to find out the average rating for each course on Udemy.
The tables are provided below:
id | title |
---|---|
101 | Mastering Python |
102 | Learn SQL from Scratch |
103 | Web Development with JavaScript |
104 | Adobe Photoshop for Beginners |
course_id | rating |
---|---|
101 | 4.5 |
101 | 5.0 |
101 | 4.0 |
102 | 3.0 |
103 | 3.5 |
102 | 4.5 |
104 | 5.0 |
103 | 4.0 |
104 | 4.5 |
This query first joins the table and the table on the course id, and then for each course title (Group By ), it calculates the average rating () from the table.
The result will show the average rating for each course on Udemy. This can provide insights on how well the courses are being received by the users.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating average ratings or this Facebook User's Third Transaction Question which is similar for involving SQL and user data.
A UNIQUE constraint ensures that all values in a column are different. It is often used in conjunction with other constraints, such as NOT NULL, to ensure that the data meets certain conditions.
For example, if you had Udemy sales leads data stored in a database, here's some constraints you'd use:
In this example, the UNIQUE constraint is applied to the "email" and "phone" fields to ensure that each Udemy lead has a unique email address and phone number. This helps to ensure the integrity of the data in the database and prevents errors that could occur if two leads had the same email address or phone number.
Udemy is an online learning platform offering various courses across categories. For understanding the user satisfaction, they often analyze the reviews provided by the users for different courses. Write a SQL query to find out the average rating of each course category per month.
review_id | user_id | submit_date | course_id | stars |
---|---|---|---|---|
6171 | 123 | 2022-08-06 | 101 | 5 |
7802 | 265 | 2022-10-06 | 102 | 4 |
5293 | 362 | 2022-10-18 | 101 | 3 |
6352 | 192 | 2022-26-07 | 103 | 3 |
4517 | 981 | 2022-05-07 | 102 | 2 |
course_id | category |
---|---|
101 | Programming |
102 | Data Science |
103 | Marketing |
month | category | avg_rating |
---|---|---|
7 | Programming | 5.00 |
7 | Data Science | 2.00 |
8 | Programming | 5.00 |
10 | Programming | 3.00 |
10 | Data Science | 4.00 |
In the given SQL block, we first join the and tables on the field. We then group the result by the month of the and the . Within each group, we calculate the average which gives us the average rating of each course category per month. The result is then ordered by and . Please remember that the function extracts the month from the column in PostgreSQL.
You are provided with two tables. The first table contains information about the users including their ID and the city where they live. The second table includes data about the ratings that the users gave for each course they purchased on Udemy.
Write a SQL query to find the average rating of each course for each city, only including cities with more than 100 ratings.
user_id | name | city |
---|---|---|
123 | John Doe | New York |
265 | Jane Smith | Los Angeles |
362 | Alice Johnson | New York |
192 | Bob Jackson | New York |
981 | Charlie Green | Los Angeles |
review_id | user_id | course_id | rating |
---|---|---|---|
6171 | 123 | 101 | 4 |
7802 | 265 | 202 | 4 |
5293 | 362 | 101 | 3 |
6352 | 192 | 202 | 3 |
4517 | 981 | 202 | 2 |
This PostgreSQL query first joins the two tables using the user_id as the common key. It then performs a group by operation on the result, grouping by both the city and the course_id fields. The AVG() function is used to average the rating for each group.
This query filter out the groups that have more than 100 ratings using the HAVING clause. Finally, it orders the result by the average_rating in descending order. This will provide us with the average rating of each course, for each city, with cities having more than 100 ratings.
Because joins come up routinely during SQL interviews, try this interactive Snapchat JOIN SQL interview question:
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 Udemy, it's good to know that companies generally choose to use NoSQL databases:
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Udemy SQL interview is to solve as many practice SQL interview questions as you can! Besides solving the earlier Udemy SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Google, Facebook, Microsoft and Amazon.
Each SQL question has hints to guide you, step-by-step solutions and crucially, there's an online SQL code editor so you can easily right in the browser your SQL query answer and have it checked.
To prep for the Udemy SQL interview you can also be helpful to practice interview questions from other tech companies like:
But if your SQL query skills are weak, don't worry about jumping right into solving questions – refresh your SQL knowledge with this DataLemur SQL tutorial.
This tutorial covers SQL concepts such as handling date/timestamp data and Subqueries – both of which show up frequently in Udemy SQL interviews.
Besides SQL interview questions, the other types of problems covered in the Udemy Data Science Interview are:
The best way to prepare for Udemy Data Science interviews is by reading Ace the Data Science Interview. The book's got: