Crown Castle employees write SQL queries often for analyzing large telecom datasets for infrastructure optimization. Unsurprisingly this is why Crown Castle asks SQL coding questions in interviews for Data Science, Data Engineering and Data Analytics jobs.
To help prep you for the Crown Castle SQL interview, we'll cover 10 Crown Castle International SQL interview questions can you solve them?
Given the following tables:
transaction_id | user_id | transaction_date | amount |
---|---|---|---|
1 | 123 | 2022-06-01 00:00:00 | 1000 |
2 | 456 | 2022-06-05 00:00:00 | 7000 |
3 | 789 | 2022-06-20 00:00:00 | 2500 |
4 | 123 | 2022-07-10 00:00:00 | 1200 |
5 | 456 | 2022-07-15 00:00:00 | 8000 |
Assuming power users are defined as users who have spent more than $5000 in transactions over the past 30 days, write PostgreSQL query to identify these power users from the Crown Castle customer database.
The above query is designed to filter out the high-value "power" users. It will sum the amount of all transactions that occurred in the last 30 days for each user. If the total surpasses $5000, this user will be considered a "power" user and their user_id will be returned in the output, along with the total amount they spent.
Please be aware this answer needs the CURRENT_DATE function to work properly, and it assumes that the transaction_date column in the transactions table holds a or type, otherwise further casting might be required.
To work on a similar customer analytics SQL question where you can code right in the browser and have your SQL code instantly graded, try this Walmart SQL Interview Question:
Imagine there was a table of Crown Castle employee salary data, along with which department they were in. Write a query to compare the average salary of employees in each department to the company's average salary for March 2024. Return the comparison result as 'higher', 'lower', or 'same' for each department. Display the department ID, payment month (in MM-YYYY format), and the comparison.
You can solve this problem interactively on DataLemur:
The answer is LONG – 30+ lines of SQL. You can find a step-by-step solution here: Department Salaries.
Read about how Crown Castle makes comprehensive solutions for today's educator's.
To normalize a database, tables are divided into smaller, more specialized ones and relationships between them are defined via primary and foreign keys. This minimizes redundancy, making the database more flexible, scalable, and easier to maintain. Normalization also helps to ensure the accuracy of the data by reducing the likelihood of inconsistencies and errors.
Crown Castle is a large provider of shared communications infrastructure – towers, fiber and small cell networks. Suppose that we have the following dataset containing rental fee information for different assets. Write a SQL query to calculate the monthly average rental fee and count of assets using Window Functions.
rental_id | asset_id | rental_date | fee |
---|---|---|---|
123456 | A1 | 2021-07-01 | 250 |
123457 | A1 | 2021-07-02 | 250 |
123458 | A2 | 2021-08-01 | 150 |
123459 | A3 | 2021-08-01 | 200 |
123460 | A2 | 2021-08-02 | 150 |
123461 | A1 | 2021-09-01 | 250 |
123462 | A2 | 2021-09-01 | 150 |
123463 | A3 | 2021-09-01 | 200 |
The corresponding PostgresSQL query would be:
In this query, the function is used to truncate the date to the month, effectively grouping by the month. The window function calculates the number of different assets rented in each month. The window function calculates the average rental fee for each month. The results are then ordered by the month.
Pro Tip: Window functions are a popular SQL interview topic, so practice every window function problem on DataLemur
"In SQL, a join generally retrieves rows from multiple tables and combines them into a single result set. For an example of the difference between a left vs. right join, suppose you had a table of Crown Castle orders and Crown Castle customers.
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.
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.
Crown Castle, being a leading provider of communications infrastructure such as cell towers and fiber, would need an efficient way of tracking and managing its operations. For this exercise, suppose Crown Castle would like an SQL query that can help manage the current capacity of its cell towers.
Each tower can serve a fixed number of telecom providers simultaneously (capacity). The business needs to know which of their towers have slots available to accommodate more providers.
Two tables are involved: and . The table contains the tower id, location and its capacity. The table records which provider is using which tower.
tower_id | location | capacity |
---|---|---|
1 | Houston | 3 |
2 | Austin | 2 |
3 | Dallas | 4 |
provider_id | tower_id |
---|---|
100 | 1 |
101 | 1 |
102 | 2 |
103 | 3 |
104 | 3 |
105 | 3 |
You are required to write a query which will return the towers which still have capacity to serve more telecom providers.
This query first performs a left join on the table with the table based on the . Then, it groups the result by the , , and . The clause is used to filter out the towers where the count of providers is less than the tower's capacity. The result of this query shows the list of towers and their locations with available capacity to serve more telecom providers.
A self-join is a operation in which a single table is joined to itself. To perform a self-join, you must specify the table name twice in the clause, giving each instance a different alias. You can then join the two instances of the table using a clause, and specify the relationship between the rows in a clause.
Think of using a self-joins whenever your data analysis involves analyzie pairs of the same things, like comparing the salaries of employees within the same department, or identifying pairs of products that are frequently purchased together (which you can do in this real SQL question from a Walmart interview).
For another self-join example, suppose you were conducting an HR analytics project and needed to examine how frequently employees within the same department at Crown Castle interact with one another, you could use a self-join query like the following to retrieve all pairs of Crown Castle employees who work in the same department:
This query returns all pairs of Crown Castle employees who work in the same department, and excludes pairs where the employee's id is the same (since this would represent the same Crown Castle employee being paired with themselves).
Crown Castle is interested in determining the click-through rate of their digital ad campaigns on various online platforms. They are defined as the number of unique users who clicked on an ad divided by the number of unique users who viewed the ad. The company would like a breakdown of the campaign's performance for each platform.
You are provided with two tables:
view_id | user_id | view_date | ad_id | platform |
---|---|---|---|---|
1112 | 301 | 04/17/2023 16:45:00 | 7089 | |
1819 | 299 | 04/17/2023 17:00:00 | 7089 | |
2923 | 152 | 04/17/2023 17:30:00 | 6023 | |
8123 | 251 | 04/19/2023 10:00:00 | 4546 | |
9017 | 303 | 04/19/2023 11:10:00 | 6023 |
click_id | user_id | click_date | ad_id | platform |
---|---|---|---|---|
4215 | 301 | 04/17/2023 16:45:30 | 7089 | |
6229 | 251 | 04/19/2023 10:00:45 | 4546 | |
8233 | 152 | 04/17/2023 17:31:00 | 6023 |
This query joins and on and to achieve a row-level representation of individual ad impressions that resulted in a click.
The click-through rate is calculated for each platform by counting unique users who clicked an ad and dividing it by the number of unique users who viewed an ad. To prevent division by zero, we use the function to assign a minimum denominator of 1.
The result is the click-through rate for each platform.
To practice a similar SQL interview question on DataLemur's free online SQL code editor, attempt this Facebook SQL Interview question:
Crown Castle is a leading provider of shared communications infrastructure across the US. For the company's locations database, you are tasked with a project to find all facilities in the state of Texas. Can you write a SQL query to filter all records where the address detail contains the word "Texas"?
facility_id | facility_name | facility_address |
---|---|---|
001 | Tower One | 123 Main St, Dallas, Texas |
002 | Site Alpha | 500 Mapple Dr, Houston, Texas |
003 | Station Zeta | 76 Broad St, New York, New York |
004 | Hub Echo | 33 Elm St, San Francisco, California |
005 | Point Bravo | 90 Liberty Ave, Austin, Texas |
This query will return all the records in the 'facilities' table where the 'facility_address' contains the word "Texas". The '%' character is a wildcard in SQL that matches any number of characters.
facility_id | facility_name | facility_address |
---|---|---|
001 | Tower One | 123 Main St, Dallas, Texas |
002 | Site Alpha | 500 Mapple Dr, Houston, Texas |
005 | Point Bravo | 90 Liberty Ave, Austin, Texas |
The output would be all the facilities that are located in the state of Texas.
Unique indexes help ensure that there are no duplicate key values in a table, maintaining data integrity. They enforce uniqueness whenever keys are added or changed within the index.
To define a unique index in PostgreSQL, you can use the following syntax:
To define a non-unique index in PostgreSQL, you can use the following syntax:
Non-unique indexes on the other hand, are used to improve query performance by maintaining a sorted order of frequently used data values, but they do not enforce constraints on the associated table.
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews. Besides solving the earlier Crown Castle SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Netflix, Airbnb, and Amazon.
Each interview question has hints to guide you, detailed solutions and crucially, there's an interactive SQL code editor so you can right online code up your query and have it graded.
To prep for the Crown Castle SQL interview you can also be useful to practice interview questions from other telecom and REIT companies like:
In case your SQL foundations are weak, forget about going right into solving questions – go learn SQL with this SQL tutorial for Data Analytics.
This tutorial covers things like functions like SUM()/COUNT()/AVG() and turning a subquery into a CTE – both of these pop up routinely during Crown Castle SQL interviews.
Beyond writing SQL queries, the other types of problems tested in the Crown Castle Data Science Interview include:
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