# 11 Clear Channel SQL Interview Questions (Updated 2024)

Updated on

June 30, 2024

Data Analysts & Data Scientists at Clear Channel use SQL for analyzing advertising campaign success through stored data and for tracking real-time digital billboard performance. Because of this, Clear Channel frequently asks jobseekers SQL coding interview questions.

So, to help you practice, here’s 11 Clear Channel Outdoor SQL interview questions – can you solve them?

## 11 Clear Channel Outdoor SQL Interview Questions

### SQL Question 1: Identify VIP Users for Clear Channel

Clear Channel is a multinational outdoor advertising company. VIP users for Clear Channel are likely to be advertisers who frequently purchase significant advertising space across several channels.

You are provided a database with two tables - and . The table has information about each advertiser, including their and . The table records each purchase made by an advertiser, including the , , (the channel on which the ad space was bought), and (the size of the ad space bought).

Your task is to write a SQL query to identify VIP users, defined as advertisers who have bought more than 10000 square feet of ad space on average each month over the past year.

1CompanyA
2CompanyB
3CompanyC
4CompanyD
##### Example Input:
106/10/202215000
206/15/202227000
107/20/202216000
408/01/202225000
109/15/2022110000

The following SQL query will return the VIP users (advertiser_id) who bought more than 10000 square feet of ad space on average each month over the past year.

The above solution begins by creating a subquery on the purchases table, where it groups by and calculates the average for the past year. This is achieved using a clause to filter the results where the average is more than 10000. This subquery returns the id of VIP advertisers. The outer query then joins this subquery result with the table on to get the actual advertiser names.

To solve a related customer analytics question on DataLemur's free interactive SQL code editor, try this Microsoft Teams Power User SQL Interview Question:

### SQL Question 2: Highly-Paid Employees

Given a table of Clear Channel employee salary data, write a SQL query to find all employees who make more than their own boss.

#### Clear Channel Example Input:

employee_idnamesalarydepartment_idmanager_id
1Emma Thompson38001
2Daniel Rodriguez2230110
3Olivia Smith800018
4Noah Johnson680028
5Sophia Martinez1750110
8William Davis70002NULL
10James Anderson40001NULL

#### Example Output:

employee_idemployee_name
3Olivia Smith

This is the output because Olivia Smith earns \$8,000, surpassing her manager, William Davis who earns 7,800.

Test your SQL query for this problem and run your code right in DataLemur's online SQL environment:

First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.

If the solution above is confusing, you can find a detailed solution with hints here: Well Paid Employees.

### SQL Question 3: Can you describe a cross-join and its purpose?

A cross-join, also referred to as a cartesian join, is a type of JOIN that returns the cross-product of two tables. In a cross-join, each row from the first table is paired with every row from the second table, resulting in a new table with a row for each possible combination of rows from the two input tables.

For example, say you worked on the Marketing Analytics team at Clear Channel, and were tasked to understand what advertising copy (text) goes best with what advertising creative (the photo that gets used along with the text copy).

Here is an example of a cross-join between a table of ad_copy and a table of ad_creative:

You could this query to generate all possible combinations of ad copy and ad creative to help you create more effective ads for Clear Channel. Just be careful: if you had 1,000 rows of ad copy and 1,000 different image creatives, the resulting cross-join would have 1 million rows! As a result, it's important to use cross-joins judiciously, and make sure that you're not generating more data than you need to.

### SQL Question 4: Billboard Data Analysis

##### Example Input:
101billboard
102bus_shelter
103airport
104billboard
105bus_shelter

The table records every viewing of an advertisement (an "impression"). The viewing is considered happening when a device carried by a person passes near enough to an advertisement location:

##### Example Input:
device_idlocation_idview_date
110106/08/2022
210306/10/2022
310506/18/2022
410307/26/2022
510107/05/2022

As a data analyst, your task is to write a query to find the total number of impressions each ad type accumulated each month over time. The result should be sorted by the date and type of ad.

##### Example Output:
6billboard1
6airport1
6bus_shelter1
7billboard1
7airport1

This SQL query uses a window function . The PARTITION BY clause divides the result set into partitions (groups). The count function is applied to each partition separately and computation restarts for each partition. In your case, impressions are partitioned by the month of the view date and the advertisement type.

Pro Tip: Window functions are a frequent SQL interview topic, so practice every window function problem on DataLemur

### SQL Question 5: What would you do to optimize a SQL query that was running slow?

First things first, figure out why the query is slow! You can use and commands in PostgreSQL to identify any performance bottlenecks. You might discover that your query is inefficient, or that there are many database writes at the same time you are doing a read, or maybe too many people are concurrently running queries on the same database server.

For Data Analyst and Data Science positions, knowing the ins-and-outs of SQL performance tuning is out-of-scope for the SQL interview round. However, knowing that joins are expensive, and indexes can speed up queries, is generally enough of an answer for Clear Channel SQL interviews.

### SQL Question 6: Billboard Performance Analysis

Clear Channel owns numerous billboards across various city locations. They provide advertisement placements for different clients. Assume the company wants to analyze the performance of their billboards to see which ones generate the most views. A 'view' is considered as any vehicle that passes by the billboard.

You have been provided with two tables. The table contains information about all the billboards including their ID and location. The table keeps a record of the traffic data for each billboard on a daily basis, including the date and number of vehicle views.

Design a SQL query that will return the top 5 billboards with the highest average daily views for the month of October, 2022.

##### Example Input:
billboard_idcitylocation
1Los AngelesDowntown
2New YorkTimes Square
3ChicagoMag Mile
4San FranciscoMarket Street
5MiamiSouth Beach
##### Example Input:
traffic_idbillboard_iddateviews
9731110/01/20221200
8732210/02/20221800
9921110/03/20221500
8991310/05/20221300
7911210/10/20221600
6791410/20/2022900
5912210/30/20221700
##### Example Output:
billboard_idcityaverage_views
2New York1700
1Los Angeles1350
3Chicago1300
4San Francisco900
5MiamiNo data

The query joins and tables together by . It filters the data for October 2022 and calculates the average views by billboard. The result is then ordered in descending order by and limited to the top 5. If no traffic data exists for a billboard, 'No Data' is displayed.

### SQL Question 7: What are the different types of database indexes?

A database index is a data structure that improves the speed of data retrieval operations on a database table.

There are few different types of indexes that can be used in a database:

• Primary index: a unique identifier is used to access the row directly.
• Unique index: used to enforce the uniqueness of the indexed columns in a table.
• Composite index: created on multiple columns of a table, is used to speed up the search process for multiple columns
• Clustered index: determines the physical order of the data in a table

For a concrete example, say you had a table of Clear Channel customer payments with the following columns:

Here's what a clustered index on the column would look like:

A clustered index on the column would determine the physical order of the records in the table based on the . This means that the records with the earliest values would be stored together physically in the table, followed by records with later payment_date values. This speeds up queries that filter or sort the data based on the , as the records are already physically sorted in the table. For example, if you want to retrieve all the payments made in the month of June, the database can use the clustered index to quickly locate and retrieve the desired records without having to search through the entire table.

Clear Channel is a mass medial company that offers advertising opportunities. For this question, imagine you're working with a database that contains two tables: and .

The table contains detailed information about each client, including client ID, client name and client industry.

Write an SQL query to find all ads that were displayed after the 1st of January 2020, cost more than \$500 and were sponsored by clients from the 'Retail' industry.

##### Example Input:
1012706/08/2020650
1025104/01/20201200
1033902/28/2020500
1042701/15/2021800
1054512/30/2019700
##### Example Input:
client_idclient_nameclient_industry
27Widget Co.Retail
51Trial Inc.Medical
45MedCoMedical

This query joins the and table on the field. The clause filters for ads displayed after the 1st of January 2020, with a cost higher than \$500, and where the client's industry is 'Retail'. The result will be a list of ads that match these criteria, along with the display date, cost, and client name for each ad.

### SQL Question 9: Calculating Click-Through-Rate for Clear Channel Campaigns

Clear Channel is interested in analyzing the click-through rates (CTR) of its ad campaigns. The metric is defined as the number of users who clicked on an ad divided by the number of users who were shown the ad. For a particular campaign, Clear Channel wants to calculate the CTR on a daily basis.

You have been given two tables – , which logs the ad impressions, and , which logs the ad clicks.

#### Example Input:

imp_iduser_idcampaign_idimp_date
3232111012022-07-25
1253121022022-07-25
9476231012022-07-25
6161241022022-07-26
1739351012022-07-26

#### Example Input:

click_iduser_idcampaign_idclick_date
1123521022022-07-25
1365311012022-07-26
1865151012022-07-26

Clear Channel expects output listing CTR per day for each campaign. For e.g.

#### Example Output:

datecampaign_idctr
2022-07-251010
2022-07-251021
2022-07-26101.50
2022-07-261020

This query calculates the number of clicks per impression for each campaign organized by date. It uses a LEFT JOIN to combine the impressions with the clicks data, grouping by date and campaign_id. The ctr is calculated as the ratio of distinct clicks to unique impressions. If there are no clicks for a campaign on a certain day, the ctr will be zero.

To solve another question about calculating rates, try this TikTok SQL Interview Question on DataLemur's interactive coding environment:

### SQL Question 10: Can you explain the concept of a constraint in SQL?

Constraints are used to specify the rules concerning data in the table. It can be applied for single or multiple fields in an SQL table during the creation of the table or after creating using the ALTER TABLE command. The constraints are:

Say you were storing sales analytyics data from Clear Channel's CRM inside a database. Here's some example constraints you could use:

• PRIMARY KEY constraint: You might use a PRIMARY KEY constraint to ensure that each record in the database has a unique identifier. For example, you could use the "opportunity_id" field as the primary key in the "opportunities" table.

• FOREIGN KEY constraint: You might use a FOREIGN KEY constraint to link the data in one table to the data in another table. For example, you could use a foreign key field in the "opportunities" table to reference the "account_id" field in the "accounts" table.

• NOT NULL constraint: You might use a NOT NULL constraint to ensure that a field cannot contain a NULL value. For example, you could use a NOT NULL constraint on the "opportunity_name" field in the "opportunities" table to ensure that each opportunity has a name.

• UNIQUE constraint: You might use a UNIQUE constraint to ensure that the data in a field is unique across the entire table. For example, you could use a UNIQUE constraint on the "email" field in the "contacts" table to ensure that each contact has a unique email address.

• CHECK constraint: You might use a CHECK constraint to ensure that the data in a field meets certain conditions. For example, you could use a CHECK constraint to ensure that the "deal_probability" field in the "opportunities" table is a value between 0 and 100.

• DEFAULT constraint: You might use a DEFAULT constraint to specify a default value for a field. For example, you could use a DEFAULT constraint on the "stage" field in the "opportunities" table to set the default value to "prospecting"

### SQL Question 11:

Imagine you're a data analyst for Clear Channel, a company that facilitates outdoor advertising. You're given two tables: a customer table that gives you information about the customers' IDs and cities, and another table that provides revenue information for each transaction with a customer ID, transaction date, and revenue value.

The two tables have the following structure:

##### Example Input:
customer_idcity
1001San Francisco
1002New York
1003Los Angeles
1004Chicago
1005San Francisco
##### Example Input:
trans_idcustomer_idtrans_daterevenue
110012022-02-15200.00
210022022-03-10350.00
310012022-03-20150.00
410032022-04-25500.00
510052022-05-15250.00

The management has given you a task to write a query that will tell them the total revenue for each city for transactions that happened in the month of March 2022.

This query works by joining the and tables on the field so that we can access the and columns within the same query. Then, it restricts the records to those from March 2022 by using the function. Finally, it groups the results by city and calculates the total revenue for each city using the function.

Because join questions come up routinely during SQL interviews, take a stab at this Snapchat SQL Interview question using JOINS:

### Clear Channel SQL Interview Tips

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 Clear Channel SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Google, Microsoft and Silicon Valley startups.

Each interview question has hints to guide you, detailed solutions and crucially, there's an online SQL code editor so you can right online code up your SQL query and have it checked.

To prep for the Clear Channel SQL interview you can also be helpful to solve interview questions from other advertising companies like:

However, if your SQL skills are weak, don't worry about diving straight into solving questions – refresh your SQL knowledge with this DataLemur SQL tutorial.

This tutorial covers things like window functions like RANK() and ROW_NUMBER() and cleaning text data – both of which come up frequently in SQL job interviews at Clear Channel.

### Clear Channel Outdoor Data Science Interview Tips

#### What Do Clear Channel Data Science Interviews Cover?

In addition to SQL query questions, the other types of problems covered in the Clear Channel Data Science Interview are:

#### How To Prepare for Clear Channel Data Science Interviews?

I'm sorta biased, but I think the optimal way to prep for Clear Channel Data Science interviews is to read my book Ace the Data Science Interview.

The book covers 201 data interview questions taken from companies like Google, Tesla, & Goldman Sachs. It also has a crash course covering SQL, AB Testing & ML. And finally it's helped a TON of people, which is why it's got over 1000+ 5-star reviews on Amazon.