10 CCC Intelligent Solutions SQL Interview Questions (Updated 2024)
At CCC Intelligent Solutions, SQL is used frequently for extracting and analyzing accident and claims data, and managing the large databases of insurance and automotive data. So, it shouldn't surprise you that CCC Intelligent Solutions LOVES to ask SQL query questions in interviews for Data Science, Data Engineering and Data Analytics jobs.
As such, to help you practice for the CCC Intelligent Solutions SQL interview, we've collected 10 CCC Intelligent Solutions SQL interview questions – can you solve them?
10 CCC Intelligent Solutions SQL Interview Questions
SQL Question 1: Identify Most Frequent Customers
For "CCC Intelligent Solutions", an important metric might be which customers are purchasing services the most frequently, as these could be wholesale customers bringing significant revenue to the business. We'll look at a database where we have a table with fields , , , , and . The goal is to identify the top 5 customers in terms of the number of purchases they make.
Example Input
| purchase_id | user_id | service_id | purchase_date | amount |
|---|---|---|---|---|
| 1234 | 001 | 101 | 01/01/2022 | 500.00 |
| 2345 | 002 | 102 | 02/01/2022 | 300.00 |
| 3456 | 001 | 105 | 03/01/2022 | 400.00 |
| 4567 | 003 | 101 | 04/01/2022 | 700.00 |
| 5678 | 001 | 102 | 05/01/2022 | 600.00 |
Answer:
Here is the SQL query that can find this information:
This SQL query counts the number of purchases for each user, sorts the users by their total number of purchases in descending order, and returns the top 5 users. In the context of CCC Intelligent Solutions, these would likely be the 'whale users' or 'power users' who make frequent purchases and may represent a significant proportion of the company's revenue.
To practice a related super-user data analysis question on DataLemur's free online SQL coding environment, try this recently asked Microsoft SQL interview question:
SQL Question 2: Monthly Average Ratings for CCC Intelligent Solutions Products
Suppose you've been given access to a reviews database table for CCC Intelligent Solutions. The table contains review entries where each entry has an ID, the user's ID who submitted it, the date the review was submitted, the product's ID, and the stars given for the review.
Your task is to write a SQL query to determine the average star rating for each product on a monthly basis. We want to see how our product's ratings vary month by month.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2022-06-08 | 50001 | 4 |
| 7802 | 265 | 2022-06-10 | 69852 | 4 |
| 5293 | 362 | 2022-06-18 | 50001 | 3 |
| 6352 | 192 | 2022-07-26 | 69852 | 3 |
| 4517 | 981 | 2022-07-05 | 69852 | 2 |
Answer:
This query first extracts the month from the submit date by using the function and groups by month and product_id. Then it calculates the average stars for each group by using the function and orders the result by month and product_id for better view.
Example Output:
| mth | product | avg_stars |
|---|---|---|
| 6 | 50001 | 3.50 |
| 6 | 69852 | 4.00 |
| 7 | 69852 | 2.50 |
p.s. Window functions show up super often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 3: What is a database index, and what are the different types of indexes?
A database index is a way to optimize the performance of a database by reducing the amount of data that needs to be searched to retrieve a record.
There are several 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 CCC Intelligent Solutions customer payments with the following columns: payment_id, customer_id, payment_amount, and payment_date.
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.
Having a clustered index on the column can speed up queries that filter or sort the data based on the payment_date, 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 January, the database can use the clustered index to quickly locate and retrieve the desired records without having to search through the entire table.
SQL Question 4: Designing a Database for CCC Intelligent Solutions Sales Data
CCC Intelligent Solutions provides SaaS solutions, let's say the company has a range of software products and wants to track sales. The main entities to consider would be , , and .
Provide sample tables:
Example Input:
| product_id | product_name | price |
|---|---|---|
| 1 | Software A | 1000 |
| 2 | Software B | 2000 |
| 3 | Software C | 1500 |
Example Input:
| customer_id | customer_name |
|---|---|
| 101 | Company X |
| 102 | Company Y |
| 103 | Company Z |
Example Input:
| order_id | customer_id | order_date |
|---|---|---|
| 5001 | 101 | 06/08/2022 |
| 5002 | 102 | 06/10/2022 |
| 5003 | 103 | 06/18/2022 |
Example Input:
| order_id | product_id | quantity |
|---|---|---|
| 5001 | 1 | 2 |
| 5002 | 3 | 1 |
| 5003 | 2 | 3 |
The SQL question might be to determine the total revenue by product and customer for the month of June.
Answer:
This query joins the four tables together, filtering for orders made in the month of June. It then groups by product name and customer name to calculate the total revenue for each product for each customer. The total revenue is calculated as the quantity of the product ordered multiplied by its price.
SQL Question 5: Can you provide an example of two entities that have a one-to-one relationship, and another example of a one-to-many relationship?
In database schema design, a one-to-one relationship between two entities means that each entity is linked to a single instance of the other. For example, the relationship between a car and a license plate is one-to-one because each car has only one license plate, and each license plate belongs to one car.
In contrast, a one-to-many relationship is when one entity can be associated with multiple instances of the other entity. An example of this is the relationship between a teacher and their classes - a teacher can teach multiple classes, but each class is only associated with one teacher.
SQL Question 6: Average Resolution Time for Tickets
CCC Intelligent Solutions is a technology company that provides software solutions for insurance and automotive industries. There are product support engineers who resolve support tickets raised by customers. You have been given a task to find out the average resolution time for the tickets handled by each engineer. For simplicity, consider only the tickets closed and calculate resolution time in hours.
We have two tables:
Example Input:
| engineer_id | engineer_name |
|---|---|
| 1 | John Smith |
| 2 | Jane Doe |
| 3 | Harry Potter |
Example Input:
| ticket_id | engineer_id | raised_at | closed_at |
|---|---|---|---|
| 101 | 1 | 2022-01-01 09:00:00 | 2022-01-01 12:30:00 |
| 102 | 1 | 2022-02-01 10:00:00 | 2022-02-01 14:00:00 |
| 103 | 2 | 2022-03-01 10:30:00 | 2022-03-01 15:00:00 |
| 104 | 3 | 2022-01-01 11:00:00 | 2022-01-01 16:00:00 |
Answer:
This query first calculates the difference between and for each ticket (in hours). It then averages these differences for each engineer. The function is used to convert the interval to seconds, and then we divide by 3600 to get the result in hours. By grouping by , we get the average resolution time for each engineer.
To practice a very similar question try this interactive Microsoft Teams Power Users Question which is similar for calculating top performers based on number or this Stripe Repeated Payments Question which is similar for dealing with time-based measurements.
SQL Question 7: What is database normalization?
Normalization involves dividing a large table into smaller, more specific ones and establishing connections between them. This helps to reduce redundancy, creating a database that is more adaptable, scalable, and easy to manage. Additionally, normalization helps to maintain the integrity of the data by minimizing the risk of inconsistencies and anomalies.
SQL Question 8: Analyzing Click-Through Rates for CCC Intelligent Solutions
CCC Intelligent Solutions, an insurance technology company, tracks user interaction with its digital ads and the subsequent customer journeys throughout its website. The company wants to measure the click-through conversion rates for users viewing an ad, clicking on it, and eventually adding a product to their cart.
Given two tables:
Example Input:
Example Input:
Calculate the click-through conversion rate for each ad in June 2022. The click-through conversion rate is defined as the number of users who added a product to their cart after clicking on an ad divided by the total number of users who clicked on that ad.
Answer:
This query first joins the table with the table on to track the same user's journey from clicking on an ad to adding a product to the cart. The conversion rate is then calculated by dividing the number of unique users who added a product to the cart after clicking the ad by the total number of unique users who clicked the ad. It requires that the action of adding to the cart (tracked by ) happens after the ad click (tracked by ), ensuring the action is a result of the ad click. It uses the function to filter the data to June 2022.
To solve a similar problem on DataLemur's free interactive SQL code editor, try this Meta SQL interview question:
SQL Question 9: Filtering customer records for CCC Intelligent Solutions
CCC Intelligent Solutions has a customer records database. They want to filter down their customer records database and find customers residing in California whose first name starts with 'J'. Bear in mind that the column records state names in abbreviated form, for example, California is 'CA'.
Example Input:
| customer_id | first_name | last_name | customer_state | |
|---|---|---|---|---|
| 101 | John | Doe | john.doe@gmail.com | CA |
| 102 | James | Smith | james.smith@gmail.com | CA |
| 103 | Marie | Johnson | marie.johnson@gmail.com | NY |
| 104 | Julia | Martz | julia.martz@gmail.com | PA |
| 105 | Jake | Thornton | jake.thornton@gmail.com | CA |
Example Output:
| customer_id | first_name | last_name | customer_state | |
|---|---|---|---|---|
| 101 | John | Doe | john.doe@gmail.com | CA |
| 102 | James | Smith | james.smith@gmail.com | CA |
| 105 | Jake | Thornton | jake.thornton@gmail.com | CA |
Answer:
This query will return all records where the customer's first name starts with 'J' and customer resides in California. The '%' symbol is a wildcard that matches any number of characters. In this case, it will match any name that starts with 'J'. And the comparison with 'CA' in the customer_state column will narrow it down to customers residing in California.
SQL Question 10: Can you explain the purpose of the constraint and give an example of when you might use it?
The CHECK constraint is used to enforce rules on the data in a specific column. If a row is inserted or updated with data that does not follow the CHECK constraint's rule, the operation will fail. The CHECK constraint is often used with other constraints, such as NOT NULL or UNIQUE, to ensure that data meets certain conditions. You may want to use a CHECK constraint in your database if you want to maintain the quality and reliability of your data by ensuring that it meets specific criteria.
For example, you might use a CHECK constraint to ensure that a column contains only positive numbers, or that a date is within a certain range.
How To Prepare for the CCC Intelligent Solutions SQL Interview
The key to acing a CCC Intelligent Solutions SQL interview is to practice, practice, and then practice some more!
In addition to solving the earlier CCC Intelligent Solutions SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Netflix, Google, and Amazon.
Each interview question has multiple hints, step-by-step solutions and most importantly, there's an interactive SQL code editor so you can right online code up your query and have it graded.
To prep for the CCC Intelligent Solutions SQL interview you can also be useful to solve interview questions from other tech companies like:
However, if your SQL skills are weak, don't worry about going right into solving questions – go learn SQL with this free SQL tutorial.
This tutorial covers things like LEAD/LAG window functions and how window functions work – both of these pop up frequently in CCC Intelligent Solutions SQL assessments.
CCC Intelligent Solutions Data Science Interview Tips
What Do CCC Intelligent Solutions Data Science Interviews Cover?
In addition to SQL interview questions, the other types of problems to prepare for the CCC Intelligent Solutions Data Science Interview are:
- Probability & Stats Questions
- Coding Questions in Python or R
- Data Case Study Questions
- Machine Learning Questions
- Resume-Based Behavioral Questions
How To Prepare for CCC Intelligent Solutions Data Science Interviews?
The best way to prepare for CCC Intelligent Solutions Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from tech companies like Google & Microsoft
- A Crash Course on SQL, AB Testing & ML
- Amazing Reviews (900+ reviews, 4.5-star rating)