At RingCentral, SQL is used day-to-day for extracting and manipulating customer communication data for analysis, and for managing the databases that store crucial business and user information. That's why RingCentral frequently asks SQL coding questions during interviews for Data Analyst, Data Science, and BI jobs.
To help you ace the RingCentral SQL interview, we've curated 10 RingCentral SQL interview questions – able to answer them all?
Given the business nature of RingCentral, an important task could be to identify the most important (power, VIP, whale) users of their services, given two parameters: call duration and call frequency. These users make calls frequently and each call lasts longer than the average call.
To achieve this you're provided with two tables.
Your task is to identify these power users for the past 30 days, i.e., who have both a higher call frequency AND a longer duration than the average.
You can work this out via these SQL queries -
This query first calculates the total call frequency and average call duration for each user over the last 30 days. Then it compares each user against the average frequency and duration to identify the users who exceed both criteria.
The result would be a list of , , , values representing the most active/power users on RingCentral over the last 30 days.
To practice a similar power-user data analysis problem question on DataLemur's free online SQL coding environment, try this Microsoft Teams Power User SQL Interview Question:
RingCentral is a provider of cloud-based communications and collaboration solutions for businesses. Suppose we have a table named that logs every call made through RingCentral's system. Each record includes an extension number, the start and end time of the call, and whether the call was inbound or outbound.
The business needs to better understand how their system is being used. Specifically, they want to know the total call duration (in minutes) per extension for the last 7 days, ranked by total call duration, separately for both inbound and outbound calls. The total call duration is the sum of the duration of all calls (either inbound or outbound) for each extension.
call_id | extension | start_time | end_time | direction |
---|---|---|---|---|
125 | 1001 | 2022-09-01 08:00:00 | 2022-09-01 08:31:00 | Outbound |
126 | 1001 | 2022-09-01 09:30:00 | 2022-09-01 09:45:00 | Inbound |
245 | 1002 | 2022-09-02 10:15:00 | 2022-09-02 10:25:00 | Inbound |
316 | 1002 | 2022-09-02 11:50:00 | 2022-09-02 12:10:00 | Outbound |
427 | 1003 | 2022-09-02 14:05:00 | 2022-09-02 14:30:00 | Inbound |
528 | 1003 | 2022-09-02 15:00:00 | 2022-09-02 15:55:00 | Outbound |
direction | extension | total_duration | rank |
---|---|---|---|
Inbound | 1001 | 15 | 1 |
Inbound | 1002 | 10 | 2 |
Inbound | 1003 | 25 | 3 |
Outbound | 1003 | 55 | 1 |
Outbound | 1001 | 31 | 2 |
Outbound | 1002 | 20 | 3 |
This query first calculates the duration of each call in minutes within the past 7 days. It then sums the durations of all calls by extension and call direction. Finally, it ranks the extensions within each call direction group based on the total call duration.
To solve a related window function SQL problem on DataLemur's free interactive SQL code editor, try this Amazon SQL Interview Question:
Database denormalization is when you add redundancy to a database, and break typical normalization rules (specified by 1st, 2nd, 3rd normal forms). There's a few reasons to denormalize a database:
Improved performance: Denormalization often reduces the the number of costly join operations that are needed to retrieve data. This is helpful when the database is being used for OLAP (Online Analytical Processing) use cases, as joins can be expensive and slow.
Simplification: Denormalization can also be used to simplify the design of a database by reducing the number of tables and relationships that need to be managed. This can make it easier to understand and maintain the database.
Ease of use: Denormalization can also make it easier for users to work with a database by providing them with a more intuitive and straightforward data model.
While denormalization can be a useful tool for improving performance and scalability, it's important to keep in mind that it can make update and delete operations more complex. This is because denormalization can create data duplicates, which can make it harder to maintain data integrity. So, to avoid any headaches, it's a good idea to start with a well-normalized database design and then consider denormalization only if it's absolutely necessary for your specific performance and scalability needs. In other words, denormalization can be a bit of a wild card, so it's best to handle it with care!
RingCentral as a company offers cloud-based phone systems designed for today’s mobile and distributed businesses. The company's services include video meetings, team messaging, integrated fax and voice systems, and call auto-attendant. Thus, there could be potential daily transactions that involve customer subscription, purchase of communication tools, data usage etc.
A typical SQL question could be around the design of tables to effectively track the various transactions for each customer and query to retrieve a summary of monthly transactions for a specific service.
The database could contain three tables:
Customers table: Contains customer details.
Products table: Contains product details RingCentral offers.
Transactions table: Contains purchase transaction details, which includes the customer_id, product_id, date_of_purchase, and pricing.
customer_id | name | |
---|---|---|
101 | John Doe | john.doe@gmail.com |
102 | Richard Roe | richard.roe@gmail.com |
103 | Jane Smith | jane.smith@gmail.com |
product_id | product_name |
---|---|
201 | Voice System |
202 | Video Meeting |
203 | Team Messaging |
204 | Integrated Fax |
transaction_id | customer_id | product_id | date_of_purchase | price |
---|---|---|---|---|
501 | 101 | 202 | 06/08/2022 | 50 |
502 | 102 | 202 | 06/09/2022 | 50 |
503 | 101 | 202 | 07/08/2022 | 50 |
504 | 101 | 201 | 07/09/2022 | 40 |
505 | 103 | 203 | 08/10/2022 | 30 |
Calculate total revenue from each product for a given month, e.g., July 2022
This query computes the total revenue generated from each product for the month of July 2022. It joins the transaction table with the product table on the product_id field and filters out transactions of July 2022. Then it groups by product_name and uses the SUM aggregate function to calculate the total revenue for each product.
Clustered and non-clustered indexes are both used to improve query performance, but they differ in how they are implemented.
A clustered index determines the physical order of the data rows in a table, while a non-clustered index does not. As a result, a table can have only one clustered index, but it can have multiple non-clustered indexes.
In terms of query efficiency & performance, a clustered index is generally faster for SELECT queries (reads) but updates (writes) to a clustered index are slower, as they require the data rows to be physically rearranged.
Given the RingCentral database of customer records, you are to filter down the customer records based on their 'subscription_status' and a specific date range using SQL commands. Specifically, find all customers who have an 'Active' subscription status and were updated between '2022-01-01' and '2022-12-31'.
Let's assume the 'customer_records' table is structured as follows:
customer_id | customer_name | subscription_status | last_updated |
---|---|---|---|
117 | John Doe | Active | 2022-05-15 |
202 | Jane Smith | Inactive | 2022-07-10 |
323 | Michael Johnson | Active | 2021-12-01 |
424 | Emily Davis | Active | 2022-03-20 |
525 | Daniel Miller | Inactive | 2022-10-30 |
Your task is to use SQL commands to filter the customer records and return the desired results.
This SQL query filters the 'customer_records' table where the 'subscription_status' is 'Active' and the 'last_updated' date is between '2022-01-01' and '2022-12-31'. Thus, the query will return all customer records who have an active subscription and were updated anytime within the year 2022.
In database schema design, a one-to-one relationship between two entities is characterized by each entity being related to a single instance of the other. An example of this is the relationship between a US citizen and their social-security number (SSN) - each citizen has one SSN, and each SSN belongs to one person.
On the other hand, a one-to-many relationship is when one entity can be associated with multiple instances of the other entity. A teacher's relationship with their classes is an example of this - a teacher can teach many classes, but each class is only associated with one teacher.
As a RingCentral user, you have access to detail records of each call that took place through the RingCentral platform. Given a database, , where each row represents a phone call with fields for , , , and , can you write a SQL query to find the average duration of all calls for each user?
Sample Data:
call_id | user_id | call_start_time | call_end_time |
---|---|---|---|
101 | 501 | 2022-09-22 09:00:00.00 | 2022-09-22 09:10:00.00 |
102 | 502 | 2022-09-22 09:30:00.00 | 2022-09-22 09:40:00.00 |
103 | 501 | 2022-09-22 10:00:00.00 | 2022-09-22 10:30:00.00 |
104 | 502 | 2022-09-22 10:30:00.00 | 2022-09-22 10:45:00.00 |
105 | 501 | 2022-09-22 11:00:00.00 | 2022-09-22 11:10:00.00 |
In this query, we are subtracting from for each call to find the duration which yields an INTERVAL result. The EXTRACT(EPOCH FROM interval) is used to convert this INTERVAL result into a number of seconds. Then, we take the average of these durations (which will be in seconds) and divide it by 60 to convert it into minutes.
To practice a very similar question try this interactive Verizon International Call Percentage Question which is similar for calculating percentage on call data or this Twitter Tweets' Rolling Averages Question which is similar for computing average on user based records.
RingCentral is a company that provides cloud-based phone systems and other communication solutions. For a recent marketing campaign, they are targeting partners whose email IDs are associated with specific domains. The team would like to filter out those businesses with email addresses containing the domain "@partnercompany.com".
The existing customer database table 'customers' registers fields such as 'customer_id', 'name', 'email', 'city', and 'deal_value'.
The structured task is to write an SQL query that will find the 'customer_id', 'name', and 'email' for those customers whose 'email' field contains the domain "@partnercompany.com".
This SQL query will return rows with a customer's ID, name, and email if their email address domain is "@partnercompany.com". The "%" in the SQL LIKE clause is a wildcard character that matches any number of characters. Therefore, any email address, regardless of the characters before "@partnercompany.com", will be selected by this query.
Expected output:
A UNIQUE constraint ensures that all values in a column are different. This provides uniqueness for the column(s) and helps identify each row uniquely. Unlike primary key, there can be multiple unique constraints defined per table.
The key to acing a RingCentral SQL interview is to practice, practice, and then practice some more!
Beyond just solving the earlier RingCentral SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.
Each problem on DataLemur has hints to guide you, fully explained answers along with a discussion board to see how others solved it and most importantly, there's an online SQL coding environment so you can right online code up your SQL query answer and have it executed.
To prep for the RingCentral SQL interview you can also be helpful to solve SQL questions from other tech companies like:
But if your SQL skills are weak, forget about diving straight into solving questions – go learn SQL with this SQL tutorial for Data Scientists & Analysts.
This tutorial covers SQL concepts such as handling date/timestamp data and using LIKE – both of which pop up often during SQL job interviews at RingCentral.
Beyond writing SQL queries, the other topics to practice for the RingCentral Data Science Interview are:
The best way to prepare for RingCentral Data Science interviews is by reading Ace the Data Science Interview. The book's got: