At Harmonic, SQL is used frequently for analyzing video network data trends and managing cloud-based digital media storage. For this reason Harmonic often tests SQL query questions during interviews for Data Science, Data Engineering and Data Analytics jobs.
Thus, to help you practice, here's 11 Harmonic SQL interview questions – able to solve them?
As a database manager at Harmonic, you are tasked with identifying users who frequently use Harmonic's services. Specifically, Harmonic identifies power users as those who make at least 5 transactions per month. Write a SQL query to give a list of user_ids and corresponding names of power users.
Consider the following tables:
user_id | user_name |
---|---|
1 | John |
2 | Emma |
3 | Jack |
4 | Mary |
5 | Steve |
transaction_id | user_id | transaction_date | amount |
---|---|---|---|
101 | 1 | 06/01/2022 | 50 |
102 | 2 | 06/02/2022 | 100 |
103 | 3 | 06/03/2022 | 70 |
104 | 2 | 06/05/2022 | 120 |
105 | 1 | 06/06/2022 | 60 |
106 | 2 | 06/07/2022 | 80 |
107 | 1 | 06/08/2022 | 50 |
108 | 2 | 06/10/2022 | 110 |
109 | 1 | 06/10/2022 | 60 |
110 | 1 | 06/15/2022 | 70 |
In this query, we get the count of transactions made by each user in each month using the clause. We then select those users who have made more than or equal to 5 transactions in a month with the clause, indicating that they are power users. These will be joined with the users table to get the list of user_ids along with their names.
To solve a similar VIP customer analysis question on DataLemur's free online SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:
Given a table of Harmonic employee salaries, write a SQL query to find the 2nd highest salary at the company.
employee_id | salary |
---|---|
1 | 2500 |
2 | 800 |
3 | 1000 |
4 | 1200 |
second_highest_salary |
---|
1200 |
You can solve this interview question and run your code right in the browser:
You can find a step-by-step solution here: 2nd Highest Salary.
The clause is used to filter rows from the result set of a , , or statement. It allows you to specify a condition that must be met for a row to be included in the result set.
The clause is used to filter groups created by the clause. It is similar to the clause, but it is used to specify conditions on the groups created by the clause, rather than on the individual rows of the table.
Say you were working on a social media analytics project for Harmonic.
Here is an example of a SQL query that you might write which uses both the WHERE and HAVING clauses:
This query retrieves the total impressions and average conversions for each platform in the table, the date of the campaign is in January 2023. The rows are grouped by platform and the clause filters the groups to include only those with more than 5000 impressions and an average conversion rate above 0.2.
Given a list of product reviews, we want to analyze user feedback on our products on a monthly basis. Write a SQL query that will calculate the average star rating for each product at the end of each month.
review_id | user_id | submit_date | product_id | stars |
---|---|---|---|---|
1 | 101 | 2022-06-08 | 1 | 4 |
2 | 102 | 2022-06-10 | 2 | 3 |
3 | 103 | 2022-06-18 | 1 | 5 |
4 | 104 | 2022-07-26 | 2 | 1 |
5 | 105 | 2022-07-05 | 2 | 5 |
month | product_id | avg_rating |
---|---|---|
6 | 1 | 4.5 |
6 | 2 | 3.0 |
7 | 1 | null |
7 | 2 | 3.0 |
This query groups the reviews by month and product_id using the GROUP BY clause. It then calculates the average star rating for each group using the AVG function. The result of this operation is the average rating for each product per month. The ORDER BY clause orders the output by month and product_id. Note that we use the date_part function to extract the month from the submit_date column. If the submit_date column stores dates as strings, you would first need to convert it to a date type.
For more window function practice, solve this Uber SQL problem on DataLemur's interactive coding environment:
Denormalization is a technique used to improve the read performance of a database, typically at the expense of some write performance.
By adding redundant copies of data or grouping data together in a way that does not follow normalization rules, denormalization improves the performance and scalability of a database by eliminating costly join operations, which is important for OLAP use cases that are read-heavy and have minimal updates/inserts.
Harmonic Inc. has a database containing records of all their customers. As a Database Analyst at Harmonic, your task is to write an SQL query that filters customers who have spent more than $1000 in the past year and reside in either 'New York' or 'Los Angeles'. Additionally, these customers must be active users of Harmonic, defined by having logged in within the last 30 days.
user_id | user_name | city | last_login_date | total_spent_past_year |
---|---|---|---|---|
123 | Eddie Morten | New York | 2022-08-15 | 1500 |
265 | Ann Coop | Los Angeles | 2022-09-01 | 1600 |
362 | Peter Griffin | Chicago | 2022-08-15 | 3000 |
192 | Samantha Waters | New York | 2022-09-18 | 900 |
981 | John Pace | Los Angeles | 2022-07-05 | 800 |
user_id | user_name | city | last_login_date | total_spent_past_year |
---|---|---|---|---|
123 | Eddie Morten | New York | 2022-08-15 | 1500 |
265 | Ann Coop | Los Angeles | 2022-09-01 | 1600 |
This PostgreSQL query uses the WHERE clause to filter rows in the table that meet the following conditions:
The AND and OR operators are used to combine these conditions, and each condition must be met for a row to be included in the result set.
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 Harmonic 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.
As a database manager at Harmonic, you are asked to calculate the average salary by seniority level of the company's employees. Harmonic categorizes their employees into junior, mid and senior levels. Your task is to write a SQL query that will give the average salary for each seniority level.
Here are the sample tables for the employees and salaries:
employee_id | first_name | last_name | seniority_level |
---|---|---|---|
1 | John | Doe | Junior |
2 | Jane | Doe | Mid |
3 | Jim | Brown | Senior |
4 | Jill | White | Mid |
5 | Jack | Black | Junior |
employee_id | salary |
---|---|
1 | 50000 |
2 | 70000 |
3 | 90000 |
4 | 80000 |
5 | 55000 |
You should produce an output table with the fields 'seniority_level' and 'average_salary'.
seniority_level | average_salary |
---|---|
Junior | 52500 |
Mid | 75000 |
Senior | 90000 |
This SQL query performs a join on the employees and salaries tables, and then groups the rows by 'seniority_level'. The AVG function is used on the 'salary' column within each group to find the average salary by each seniority level. The resulting table is ordered by 'seniority_level' for easy comparison.
To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for grouping data and calculating averages or this Uber User's Third Transaction Question which is similar for <using SQL functions on grouped data.
Imagine you work for Harmonic, a company that sells musical instruments. You have been tasked to find customers who have purchased guitars, and who live in a city that starts with 'New'. The dataset available for this consists of and tables.
The table has these columns: , , , , .
cust_id | first_name | last_name | city | |
---|---|---|---|---|
001 | John | Doe | johndoe@example.com | New York |
002 | Jane | Smith | janesmith@example.com | Chicago |
003 | James | Brown | jamesbrown@example.com | Los Angeles |
004 | Emily | Johnson | emilyjohnson@example.com | New Orleans |
005 | Michael | Williams | michaelwilliams@example.com | New York |
The table has these columns: , , , .
purchase_id | cust_id | product_name | purchase_date |
---|---|---|---|
0001 | 001 | Acoustic Guitar | 2022-01-15 |
0002 | 002 | Electric Guitar | 2022-01-21 |
0003 | 001 | Piano | 2022-02-01 |
0004 | 004 | Acoustic Guitar | 2022-02-08 |
0005 | 003 | Violin | 2022-02-15 |
The result should show all customer details and the matching from the 'purchase' table.
This SQL query first joins and tables on . The WHERE clause then filters for customers who have purchased a product with a name containing 'Guitar' and live in a city that starts with 'New'. So, the output will contain only customers who live in cities named 'New York', 'New Orleans', etc. and have bought a product named like 'Acoustic Guitar', 'Electric Guitar', etc.
A non-relational (NoSQL) database is any database that does not use the typical tabular format of rows and columns like in relational databases.
While knowing the four different types of NoSQL databases is beyond the scope of most Data Analyst & Data Science interviews, Data Engineers at Harmonic should vaguely refresh these concepts:
Given two tables named and , write a SQL query to analyze the Harmonic database. The query should provide customer information joined with their respective purchase data. Specifically, it should output the customer's first name, last name, and e-mail, the purchased product's name, and the purchase date sorted in the descending order.
customer_id | first_name | last_name | |
---|---|---|---|
1001 | John | Doe | johndoe@mail.com |
2002 | Jane | Smith | jane@mail.com |
3003 | Bob | Johnson | bjohnson@mail.com |
purchase_id | customer_id | product_name | purchase_date |
---|---|---|---|
5001 | 1001 | Harmonic Prod A | 2022-06-08 00:00:00 |
5002 | 2002 | Harmonic Prod B | 2022-06-10 00:00:00 |
5003 | 3003 | Harmonic Prod C | 2022-06-18 00:00:00 |
This SQL query uses a JOIN operation to combine rows from two tables based on a related column between them, which is . The clause is used to sort the result-set in descending order by .
Since join questions come up routinely during SQL interviews, try this SQL join question from Spotify:
The best way to prepare for a Harmonic SQL interview is to practice, practice, practice. Beyond just solving the above Harmonic SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Netflix, Airbnb, and Amazon.
Each SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and crucially, there is an interactive SQL code editor so you can instantly run your query and have it executed.
To prep for the Harmonic SQL interview you can also be helpful to solve interview questions from other tech companies like:
But if your SQL skills are weak, don't worry about diving straight into solving questions – go learn SQL with this DataLemur SQL tutorial.
This tutorial covers things like INTERCEPT/EXCEPT and creating pairs via SELF-JOINs – both of which show up frequently during Harmonic SQL assessments.
Beyond writing SQL queries, the other question categories to practice for the Harmonic Data Science Interview are:
I'm sort of biased, but I believe the best way to prepare for Harmonic Data Science interviews is to read the book Ace the Data Science Interview.
The book covers 201 data interview questions sourced from FAANG, tech startups, and Wall Street. It also has a crash course covering SQL, Product-Sense & ML. And finally it's vouched for by the data community, which is how it's gotten to be an Amazon best-seller with over 1000+ 5-star reviews.