At InterDigital, SQL is used all the damn time for analyzing vast datasets to generate insights for wireless technology advancements, and managing and manipulating data for machine learning models in the telecom industry. That's why InterDigital often tests SQL coding questions in interviews for Data Analyst, Data Science, and BI jobs.
To help you practice for the InterDigital SQL interview, we'll cover 9 InterDigital SQL interview questions – how many can you solve?
InterDigital is a wireless communications company and you are given a dataset that shows the daily usage of their network for each user. Your task: write a SQL query that computes the total network usage for each user per week, considering the week starts from Monday.
Use the following table for the analysis:
id | userId | usageDate | dataConsumed (in GB) |
---|---|---|---|
1 | A | 03/14/2022 | 1.2 |
2 | A | 03/15/2022 | 2.3 |
3 | B | 03/15/2022 | 1.0 |
4 | A | 03/16/2022 | 0.8 |
5 | B | 03/16/2022 | 2.1 |
6 | A | 03/27/2022 | 1.5 |
7 | B | 03/27/2022 | 2.3 |
8 | B | 03/28/2022 | 1.5 |
9 | A | 03/29/2022 | 2.2 |
10 | B | 03/29/2022 | 2.1 |
This SQL query groups the data by and . It calculates the total network usage () for each user's usage per week. The function is used to round down to the nearest week, and it would be regarded as the first date of the week (Monday, by convention). The result is sorted by and for better visualization.
To solve a similar window function question on DataLemur's free online SQL code editor, try this Google SQL Interview Question:
InterDigital is a technology company that specializes in mobile technologies, IoT, and video tech and has been awarded many patents in these areas. As part of a database upgrade, you are tasked with designing a new database system capable of storing all information about patents the company has been awarded. Design the database schema that includes information about the patents (like patent id, patent title, assignee, issue date, technology area), inventors involved (like inventor id, name, address, phone number) and the relationship between patents and inventors (as any patent could be invented by multiple inventors and also, an inventor can hold more than one patent).
It's important that this system be able to quickly identify all patents a particular inventor holds, as well as all inventors involved in a particular patent.
patent_id | title | assignee | issue_date | tech_area |
---|---|---|---|---|
8771932 | Advanced mobile technologies | InterDigital | 2018-07-10 | Mobile |
8772954 | Internet of Things analytics | InterDigital | 2019-05-04 | IoT |
8773921 | High-speed video transmission | InterDigital | 2020-12-22 | Video |
inv_id | name | address | phone_num |
---|---|---|---|
5674 | John Doe | 123 Ash St, DE, USA | +11236740291 |
5675 | Jane Smith | 345 Oak Ave, NY, USA | +18124567253 |
5676 | Adam Brown | 678 Pine Blvd, CA, USA | +19734562239 |
patent_id | inv_id |
---|---|
8771932 | 5674 |
8772954 | 5675 |
8773921 | 5676 |
8771932 | 5675 |
8772954 | 5674 |
To find all inventors involved in a particular patent:
To identify all patents a particular inventor holds:
These queries use JOIN to form relationships between patents, inventors and patent_inventor_relations. It allows us to efficiently determine patents held by a particular inventor and respective inventors for a specific patent.
In SQL, a join retrieves rows from multiple tables and combines them into a single result set.
Four JOIN types can be found in SQL. For an example of each one, suppose you had a table of InterDigital orders and InterDigital customers.
INNER JOIN: Rows from both tables are retrieved when there is a match in the shared key or keys. An between the Orders and Customers tables would return only rows where the in the Orders table matches the in the Customers table.
LEFT JOIN: A retrieves all rows from the left table (in this case, the Orders table) and any matching rows from the right table (the Customers table). If there is no match in the right table, NULL values will be returned for the right table's columns.
RIGHT JOIN: A combines all rows from the right table (in this case, the Customers table) and any matching rows from the left table (the Orders table). If there is no match in the left table, NULL values will be displayed for the left table's columns.
FULL OUTER JOIN: A combines all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, NULL values will be displayed for the columns of the non-matching table.
InterDigital is a company that specializes in designing and developing advanced technologies that enable and enhance mobile communications and capabilities. As an exercise, consider a scenario where you are given a dataset of users and the data (in GB) they've consumed over a period of time. Your task is to write a SQL query to determine the average data consumption per user.
The data is presented in the following table:
user_id | month | data_usage_gb |
---|---|---|
1001 | Jan | 5.2 |
1002 | Jan | 8.6 |
1001 | Feb | 9.2 |
1003 | Jan | 6.2 |
1003 | Feb | 7.1 |
1002 | Feb | 8.8 |
1001 | Mar | 8.9 |
1002 | Mar | 6.3 |
1003 | Mar | 8.2 |
Your output should look like this:
user_id | avg_data_usage_gb |
---|---|
1001 | 7.77 |
1002 | 7.90 |
1003 | 7.16 |
Here's your SQL query:
In this PostgreSQL query, we're using the AVG function to calculate the average data usage per user. The GROUP BY keyword groups the results by the user_id, giving us the average data usage for each user. The AVG function operates on the data_usage_gb column for each group of rows (i.e., each individual user in this case).
To practice a very similar question try this interactive Twitter Histogram of Tweets Question which is similar for aggregating user activity or this Walmart Histogram of Users and Purchases Question which is similar for quantifying user consumption.
To discover records in one table that are not present in another, you can utilize a and filter out any values in the right-side table.
For example, say you had a table of InterDigital customers and a 2nd table of all purchases made with InterDigital. To find all customers who did not make a purchase, you'd use the following
This query returns all rows from the customers table, along with any matching rows from the purchases table. If there is no matching row in the purchases table, values will be returned for all of the right table's columns. The clause then filters out any rows where the purchases.id column is , leaving only customers who have not made a purchase.
You are given a list of clients with their details in a table named . Your task is to write a SQL query that filters the clients who are from the company by detecting the string in their email address.
client_id | firstname | lastname | |
---|---|---|---|
001 | John | Doe | john.doe@interdigital.com |
002 | Jane | Smith | jane.smith@abc.com |
003 | Peter | Johnson | peter.johnson@interdigital.com |
004 | Mary | Lee | mary.lee@xyz.com |
005 | Paul | Brown | paul.brown@interdigital.com |
client_id | firstname | lastname | |
---|---|---|---|
001 | John | Doe | john.doe@interdigital.com |
003 | Peter | Johnson | peter.johnson@interdigital.com |
005 | Paul | Brown | paul.brown@interdigital.com |
The above SQL query uses the keyword in conjunction with the wildcard to filter out clients whose email addresses end with , implying that they are associated with the company . As such, only the relevant records are retrieved from the table.
The UNION operator combines the results from multiple SELECT statements into a single result set.
Here's an example of using the UNION operator to combine the results of two SELECT statements that retrieve data from tables of InterDigital's Facebook ads and their Google ads:
This statement would return a combined result set of both Facebook and Google ads that have a spend greater than $200. The result set would include the following columns: ad_id, ad_name, ad_type, impressions, clicks, and spend.
Note that the two SELECT statements within the UNION must have the same number of columns and the columns must have similar data types. In this example, both SELECT statements have the same number of columns and the data types of the columns are all compatible.
Given two tables: the 'Customers' table which contains the customer’s ID and other details like their subscription plan with InterDigital; and the 'Transactions' table which has each transaction a customer has made.
Write a SQL query to find out the total number of purchases and the total amount spent by each customer. Join both 'Customers' and 'Transactions' tables together using the customers' ID.
customer_id | first_name | last_name | subscription_plan | |
---|---|---|---|---|
101 | James | Smith | james.smith@example.com | Premium |
102 | Mary | Johnson | mary.johnson@example.com | Standard |
103 | John | Williams | john.williams@example.com | Premium |
104 | Patricia | Brown | patricia.brown@example.com | Basic |
transaction_id | customer_id | transaction_date | amount |
---|---|---|---|
1001 | 101 | 07/25/2022 | 60 |
1002 | 102 | 07/26/2022 | 40 |
1003 | 103 | 07/27/2022 | 80 |
1004 | 104 | 07/28/2022 | 30 |
1005 | 101 | 07/29/2022 | 75 |
Here is a PostgreSQL query to solve it:
customer_id | first_name | last_name | subscription_plan | total_purchases | total_amount | |
---|---|---|---|---|---|---|
101 | James | Smith | james.smith@example.com | Premium | 2 | 135 |
102 | Mary | Johnson | mary.johnson@example.com | Standard | 1 | 40 |
103 | John | Williams | john.williams@example.com | Premium | 1 | 80 |
104 | Patricia | Brown | patricia.brown@example.com | Basic | 1 | 30 |
In this query, we join the 'Customers' table and the 'Transactions' table based on the customer_id. Then, we select the fields we are interested in, including customer_id, first_name, last_name, email, and subscription_plan from the 'Customers' table, and the count of transaction_id and sum of amount from the 'Transactions' table. Finally, we group the result by the customer details to get a per-customer summary.
Because joins come up frequently during SQL interviews, take a stab at this SQL join question from Spotify:
InterDigital is a company that develops wireless technologies and has a vast portfolio of intellectual properties, including many patents. In the context of InterDigital, a useful SQL problem could be identifying the frequency of patent filings over time, and whether there are any particular periods of increased activity.
For this problem, consider a database table where each row represents a patent that InterDigital has filed. The columns could include (a unique identifier for each patent), (the date when the patent was officially filed), and (the area of technology the patent belongs to).
patent_id | filing_date | technology |
---|---|---|
001 | 01/03/2021 | 5G |
002 | 01/22/2021 | IoT |
003 | 02/19/2021 | AI |
004 | 02/27/2021 | 5G |
005 | 03/05/2021 | IoT |
Now, to answer the question of how many patents were filed each month per technology, we could write the corresponding SQL query:
This query uses the function to round down each filing date to the start of the month, thus grouping all filings that occurred in the same month together. It then counts the number of patents filed within each of these groups by month and technology, resulting in a count of patent filings for each technology per month. The result is ordered by month in ascending order and by the amount of patent filings in descending order.
The output of this query would show, for each month, how many patents InterDigital has filed in each technology, helping the company identify trends in their patent filing activity.
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the InterDigital SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the above InterDigital 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, fully explained answers along with a discussion board to see how others solved it and crucially, there is an online SQL code editor so you can instantly run your SQL query answer and have it graded.
To prep for the InterDigital SQL interview it is also useful to solve SQL questions from other tech companies like:
In case your SQL coding skills are weak, don't worry about going right into solving questions – refresh your SQL knowledge with this DataLemur SQL Tutorial.
This tutorial covers things like finding NULLs and using ORDER BY – both of which show up frequently during InterDigital interviews.
In addition to SQL query questions, the other topics to prepare for the InterDigital Data Science Interview are:
The best way to prepare for InterDigital Data Science interviews is by reading Ace the Data Science Interview. The book's got: