At PowerSchool, SQL is used often for extracting and analyzing educational data, and structuring large-scale databases to track student performance and outcomes. That's why PowerSchool often tests SQL coding questions during interviews for Data Analyst, Data Science, and BI jobs.
So, to help you study for the PowerSchool SQL interview, here’s 10 PowerSchool SQL interview questions – can you answer each one?
PowerSchool is a leading education technology platform that provides various products for K-12 education. An essential aspect for PowerSchool is to understand its users' engagements, particularly those who are the most active or top contributors to its platform. These power users could be teachers, students or parents who frequently log in or perform substantial activities on the PowerSchool system. Write a SQL query to identify the top 10 users who have the highest number of logins in the last month.
activity_id | user_id | login_date | user_type |
---|---|---|---|
29150 | 785 | 06/11/2022 22:00:00 | teacher |
38372 | 379 | 06/14/2022 20:00:00 | student |
27451 | 547 | 06/20/2022 14:00:00 | teacher |
48930 | 785 | 06/21/2022 18:00:00 | teacher |
25812 | 879 | 06/22/2022 11:00:00 | parent |
30195 | 379 | 06/24/2022 09:00:00 | student |
42761 | 547 | 06/28/2022 22:00:00 | teacher |
38391 | 785 | 06/28/2022 20:00:00 | teacher |
This SQL query first filters the users who have logged in within the last month. It then groups the results by each user_id and user_type, and counts the number of records for each group, resulting in the number of logins for each user. The query finally sorts all users by their number of logins in descending order and only returns the top 10 users.
To practice a similar customer analytics SQL question where you can solve it interactively and have your SQL code automatically checked, try this Walmart SQL Interview Question:
PowerSchool is commonly used for managing student information, so let's consider a scenario where we have a large dataset of student grades and course enrollments.
Design a SQL query that, for each student, returns their average grade within each subject, as well as their rank within that subject based on their average grade. Assume that a higher grade represents a better performance.
For simplicity, we can assume that each course belongs to exactly one subject, and each student receives exactly one grade in each course.
Here's what the input and output should look like:
student_id | name |
---|---|
1 | Alice |
2 | Bob |
3 | Charlie |
course_id | subject |
---|---|
1 | Math |
2 | Math |
3 | English |
student_id | course_id | grade |
---|---|---|
1 | 1 | 90 |
1 | 2 | 95 |
1 | 3 | 85 |
2 | 1 | 95 |
2 | 2 | 90 |
2 | 3 | 80 |
3 | 1 | 92 |
3 | 2 | 94 |
3 | 3 | 90 |
name | subject | avg_grade | rank_in_subject |
---|---|---|---|
Alice | Math | 92.5 | 2 |
Alice | English | 85.0 | 3 |
Bob | Math | 92.5 | 2 |
Bob | English | 80.0 | 1 |
Charlie | Math | 93.0 | 1 |
Charlie | English | 90.0 | 2 |
This query first joins the , , and tables so that we have a combined dataset that includes each student's name, the subject of each course they enrolled in, and the grade they received in that course.
Then, it groups this dataset by student and subject, and calculates the average grade each student received within each subject.
Finally, it uses the window function to compute each student's rank within each subject, based on their average grade. The clause ensures that we compute ranks separately for each subject, and the clause determines the order of the ranks based on the average grade, with higher grades receiving a higher rank.
To practice another window function question on DataLemur's free online SQL coding environment, solve this Amazon BI Engineer interview question:
Using a join in SQL, you can retrieve data from multiple tables and merge the results into a single table.
In SQL, there are four distinct types of JOINs. To demonstrate each kind, Imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.
: An INNER JOIN retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.
: A LEFT JOIN retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.
: A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.
: A FULL OUTER JOIN retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.
PowerSchool is a leading education technology platform that works with K-12 schools. One of their products is a Student Information System (SIS), where teachers input student grades and attendance. They have a table where each row is a grade that a student received for a course.
Your task is to design a SQL query which finds the average grade, maximum grade, and minimum grade per course, only considering courses where more than 10 grades have been given.
grade_id | student_id | course_id | grade |
---|---|---|---|
1 | 1001 | 55 | 89 |
2 | 1002 | 55 | 95 |
3 | 1003 | 60 | 73 |
4 | 1002 | 60 | 87 |
5 | 1003 | 55 | 78 |
6 | 1001 | 60 | 92 |
7 | 1005 | 55 | 82 |
8 | 1005 | 60 | 87 |
9 | 1004 | 55 | 88 |
10 | 1004 | 60 | 80 |
11 | 1003 | 55 | 91 |
12 | 1001 | 55 | 84 |
13 | 1003 | 60 | 84 |
14 | 1005 | 55 | 88 |
15 | 1003 | 60 | 88 |
course_id | average_grade | max_grade | min_grade |
---|---|---|---|
55 | 89.14 | 95 | 78 |
60 | 84.33 | 92 | 73 |
This query groups the grades by the course and calculates the average, max, and min grade for each course. If the course has more than 10 grades, it includes those in the final result. It uses the GROUP BY clause to separate the data into groups of unique course_ids and conglomerates each group into a single row, thereby allowing it to provide an average, maximum, and minimum grade for each course. The HAVING clause filters out courses that have less than 10 grades given.
The operator merges the output of two or more statements into a single result set. The two SELECT statements within the UNION must have the same number of columns and the data types of the columns are all compatible.
For example, if you were a Data Analyst on the marketing analytics team at PowerSchool, this statement would return a combined result set of both PowerSchool's Google and Facebook ads that have more than 300 impressions:
PowerSchool, an education technology platform, has launched several new features and is running a series of in-app promotional campaigns. These campaigns take the form of various digital ads and popups that are shown to users as they navigate through PowerSchool's different platforms. To understand which features are attracting the most interest, the team wants to calculate the click-through rates for these campaigns. A click-through rate is calculated as the number of clicks an ad receives divided by the number of impressions (times the ad was shown).
You are given two tables, one recording impressions and another recording clicks. Each row in the clicks table signifies that a user has clicked an ad to view more details about a feature.
impression_id | user_id | datetime | feature_id |
---|---|---|---|
5643 | 098 | 07/05/2022 00:00:00 | f1001 |
8972 | 123 | 07/05/2022 00:00:00 | f1002 |
2134 | 456 | 07/05/2022 00:00:00 | f1003 |
9827 | 789 | 07/06/2022 00:00:00 | f1001 |
4736 | 012 | 07/06/2022 00:00:00 | f1002 |
click_id | user_id | datetime | feature_id |
---|---|---|---|
7654 | 123 | 07/05/2022 00:00:00 | f1002 |
7832 | 456 | 07/06/2022 00:00:00 | f1003 |
1819 | 789 | 07/06/2022 00:00:00 | f1001 |
1726 | 012 | 07/06/2022 00:00:00 | f1002 |
Write a SQL query to calculate the click-through-rate for each product feature.
This SQL query starts by joining the impressions and clicks tables on the user_id and feature_id fields. It then groups the results by feature_id and calculates the click-through rate for each feature by counting the number of clicks and dividing it by the number of impressions.
To solve a related SQL problem on DataLemur's free interactive coding environment, attempt this SQL interview question asked by Facebook:
The operator merges the output of two or more statements into a single result set. It ignores duplicated rows, and makes sure each row in the result set is unique.
For a concrete example, say you were a Data Analyst at PowerSchool working on a Marketing Analytics project. If you needed to get the combined result set of both PowerSchool's Google and Facebook ads you could execute this SQL query:
The operator works in a similar way to combine data from multiple statements, but it differs from the operator when it comes to handling duplicate rows. Whereas filters out duplicates (so if the same ad_name is run on both Facebook and Google, it only shows up once), outputs duplicate rows.
PowerSchool has two important tables - '' and ''. The '' table contains data about all the subscribers who have purchased PowerSchool products. The '' table contains data about the subscribers' activities.
The '' table has the following structure:
subId | name | product_bought | |
---|---|---|---|
1 | John Doe | johndoe@email.com | PowerTeacher Pro |
2 | Jane Doe | janedoe@email.com | Unified Classroom |
3 | Tom Brady | tombrady@email.com | Student Information System |
4 | Sarah Brown | sarahbrown@email.com | PowerTeacher Pro |
5 | Mike Wang | mikewang@email.com | Unified Classroom |
The '' table has the following structure:
actId | subId | date | activity |
---|---|---|---|
1 | 1 | 06/08/2022 00:00:00 | Logged in |
2 | 2 | 06/10/2022 00:00:00 | Updated profile |
3 | 3 | 06/18/2022 00:00:00 | Logged in |
4 | 1 | 07/26/2022 00:00:00 | Updated profile |
5 | 4 | 07/05/2022 00:00:00 | Logged in |
Write a SQL query that joins these two tables and provides each subscriber's name, the product they bought and their last activity.
In this query, we join the '' and '' tables on the '' field. We group by the subscriber's name, the product they bought, and their activity. The function gets the latest activity for each group. We order the results by the latest date first.
Since join questions come up frequently during SQL interviews, practice this Snapchat Join SQL question:
As a school management platform, PowerSchool stores a large amount of data about student grades. Write a query to calculate the total number of students for each subject, the average rounded grade, the absolute distance between each student's grade and the average, and the square root of the highest grade in each subject.
subject_id | student_id | grade |
---|---|---|
1 | 701 | 76 |
1 | 945 | 85 |
1 | 634 | 81 |
2 | 701 | 90 |
2 | 945 | 92 |
2 | 634 | 94 |
3 | 701 | 88 |
3 | 945 | 84 |
3 | 634 | 92 |
subject_id | num_students | avg_grade | abs_dist_from_avg | sqrt_max_grade |
---|---|---|---|---|
1 | 3 | 81 | 3 | 9.22 |
2 | 3 | 92 | 1 | 9.70 |
3 | 3 | 88 | 3 | 9.61 |
In this query, we use the ABS() function to get the absolute difference between each student's grade and the average grade for each subject. Furthermore, we calculate the square root of the highest grade with the SQRT() function. The ROUND function is used to have a neat output.
To practice a very similar question try this interactive Google Odd and Even Measurements Question which is similar for calculating odd and even stats or this Amazon Average Review Ratings Question which is similar for calculating average values.
The primary key of a table is a column or set of columns that serves as a unique identifier for each row. It ensures that all rows are distinct and does not allow null values.
For example, say you had stored some Facebook ad campaign data that PowerSchool ran:
The column uniquely identifies each row in the table, and the PRIMARY KEY constraint ensures that no two rows have the same . This helps to maintain the integrity of the data in the table by preventing duplicate rows.
The primary key is also an important part of the table because it allows you to easily identify and reference specific campaigns in your Facebook Ad data. You can use it to join to other tables in the database, such as a table containing data on the results of the campaigns.
The key to acing a PowerSchool SQL interview is to practice, practice, and then practice some more! Besides solving the above PowerSchool SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Microsoft, Google, and Facebook.
Each DataLemur SQL question has multiple hints, full answers and most importantly, there's an interactive SQL code editor so you can right online code up your query and have it checked.
To prep for the PowerSchool SQL interview it is also a great idea to practice SQL problems from other tech companies like:
In case your SQL skills are weak, don't worry about jumping right into solving questions – improve your SQL foundations with this SQL tutorial for Data Scientists & Analysts.
This tutorial covers SQL concepts such as SUM/AVG window functions and sorting data with ORDER BY – both of these pop up routinely during SQL job interviews at PowerSchool.
Besides SQL interview questions, the other types of questions covered in the PowerSchool Data Science Interview are:
The best way to prepare for PowerSchool Data Science interviews is by reading Ace the Data Science Interview. The book's got: