11 Calix SQL Interview Questions (Updated 2024)

At Calix, SQL is used day-to-day for analyzing network performance data and managing customer's device database in the telecommunication sector. Unsurprisingly this is why Calix frequently asks SQL coding questions in interviews for Data Science, Analytics, and & Data Engineering jobs.

To help you prepare for the Calix SQL interview, we'll cover 11 Calix SQL interview questions – able to solve them?

11 Calix SQL Interview Questions

SQL Question 1: Analyze Product Reviews Using Window Functions

As a data analyst at Calix, you are provided with a table which has records of all the product reviews given by users. The columns of the table includes , , , and the given per product by users. You are tasked to write a query to calculate the average number of stars given to each product per month.

The column is in the format .

You could represent this table in markdown like this:

Example Input:

Your output should include the month of submission (as ), product_id (as ), and the average rating (as ). For example:

Expected Output:

Answer:

You can solve this using SQL window functions, specifically the function:

This query first uses the function to get the month value from each submission date. The function is then used to calculate the average rating for each product within each month. This is done using a window defined by the clause, which groups the data by product and month. The clause ensures that the result is sorted by month and product.

For more window function practice, try this Uber SQL problem on DataLemur's online SQL coding environment:

SQL Question 2: Database Design for Calix Equipment Inventory

As a network equipment provider, Calix needs to manage its inventory of various hardware equipment. They need to track each product's information, including its unique product ID, name, category, and price. Additionally, they want to track the stock levels for these products in different warehouses across the globe.

For our purposes, we will assume that each warehouse can store multiple types of products and each product can be stored in multiple warehouses.

We will create two separate tables to model this: a table and a table. We will also create a table that will represent the many-to-many relationship between and .

Table

Table

Table

Write a PostgreSQL query to retrieve the inventory of all products in the New York warehouse.

Answer:

This query joins the , , and tables on their common elements ( and ) and filters the results based on the location of New York, giving us the product inventory information for the New York warehouse.

SQL Question 3: In database normalization, what's the distinction between 1NF, 2NF, and 3NF?

The three levels of database normalization (also known as normal forms) are:

First Normal Form (1NF):

• Each column should contain the same type of data (no mixing strings vs. integers)
• Each column in a table contains a single value (no lists or containers of data)
• Each row in the table is unique

Second Normal Form (2NF)

• It's in 1st Normal Form
• All non-key attributes are dependent on the primary key

Said another way, to achieve 2NF, besides following the 1NF criteria, the columns should also be dependent only on that table's primary key.

Third normal form (3NF) if it meets the following criteria:

• It's in 2nd Normal Form
• There are no transitive dependencies in the table.

A transitive dependency means values in one column are derived from data in another column. For example, it wouldn't make sense to keep a column called ""vehicle's age"" and ""vehicle's manufacture date" (because the vehicle's age can be derived from the date it was manufactured).

Although there is a 4NF and 5NF, you probably don't need to know it for the Calix interview.

SQL Question 4: Filter Customers Based on Subscription and Location

As a business analyst for Calix, your task is to filter out customers who have subscribed to the 'Premium' tier and are located in 'New York' or 'San Francisco'. You are required to fetch their customer ID, name, location and subscription_type. Use the table outlined below:

Example Input

Answer

This SQL query fetches customers who have 'Premium' subscription and resides in either 'New York' or 'San Francisco'. The 'WHERE' clause is used to impose both conditions on the 'subscription_type' and 'location' rows, respectively. If both conditions are met, the row is returned in the query. The 'AND' operator ensures both conditions are met while the 'OR' operator requires either of the locations to be true.

SQL Question 5: How do and differ when it comes to ranking rows in a result set?

While both and are used to rank rows, the key difference is in how they deal with ties.

RANK(): When there's a tie, leaves a gap in the ranking. For example, if three rows are tied for 2nd place, the RANK() function will assign a rank of 2 to the first of these rows, a rank of 3 to the 2nd row in the tie, and a rank of 4 to the the 3rd tie.

DENSE_RANK(): For ties, does not leave a gap in the ranking. Instead, it assigns the same rank to all tied rows, and then makes the next row 1 bigger. Confusing, I know, but here's an example to make it more clear: if three rows are tied for 3rd place, the function will assign a rank of 3 to all three rows, and then assign a rank of 4 to the next row.

Suppose we had data on how many deals different salespeople at Calix:

To rank these salespeople, we could execute the following query:

The result of this query would be:

As you can see, the function assigns a rank of 1 to the first row (Akash), a rank of 2 to the second row (Brittany), and so on. In contrast, the , gives both Akash and Brittany a rank of 1, since they are tied, then moves on to rank 2 for Carlos.

SQL Question 6: Calculating Average Data Usage by Customers

Calix, a telecommunications company, continuously monitors data usage levels of its customers. Suppose you have access to their daily data usage database. Your task is to write a SQL query which will find the average data usage (in GB) per customer for the month of August 2022.

Example Input:

Example Output:

Answer:

This SQL query calculates the average data used in GB for each customer for the month of August 2022. It uses the AVG() function to calculate the average data usage. The WHERE clause is used to filter the data for the month of August 2022. Finally, the GROUP BY clause groups the data by customer id.

To practice a very similar question try this interactive Facebook Active User Retention Question which is similar for aggregating monthly usage data or this Amazon Average Review Ratings Question which is similar for calculating averages over a monthly period.

SQL Question 7: What's database denormalization?

Denormalization is the practice of altering a database schema in a way that breaks the normalization rules (1st, 2nd, 3rd normal forms).

Denormalization is done to improve the performance of the database when it is being used for online analytics processing (OLAP), rather than online transaction processing (OLTP) use cases.

For these OLAP use cases, you're bottleneck frequently is joining multiple tables, but de-normalizing your database cuts these outs.

Denormalization can improve query performance by reducing the number of expensive joins required to retrieve data, but it comes with its own drawbacks too. By adding redundant columns, you incur more data storage costs, and there's need for more complex update and delete operations in order to maintain data integrity across all the duplicated data. Thus, it's important to carefully consider the trade-offs involved before implementing denormalization.

SQL Question 8: Analyzing click-through and conversion rates

You are working as a data analyst at Calix. The marketing team uses various digital ads to attract customers to the website. The E-commerce team at the company is also interested in studying the journey of a customer from viewing a product to adding it to the cart on the website.

The marketing team has an table that tracks every time a user clicks on an ad. The table stores the information about the products and the table records any user's activity on the website.

Your task is to write a SQL query to calculate the click-through rate (Clicks/Impressions) of the ads and the conversion rate from viewing a product to adding a product to the cart (Add to cart/Views).

Table:

Table:

Table:

Answer:

These queries will provide you with the click-through and conversion rates for the ads and product actions respectively. The first query groups the ad clicks based on ad_id to find the number of clicks and unique clicks on each ad.

The second query uses the Postgres clause to count the number of 'View' and 'Add to Cart' actions for each product and then calculates the conversion rate. Note that we are treating 'View' as impressions and 'Add to Cart' as successful clicks in e-commerce scenario.

To solve a related SQL problem on DataLemur's free interactive coding environment, try this Facebook SQL Interview question:

SQL Question 9: Calculate the total number of sales for each type of product

Assuming Calix is a company that deals with equipment for communication service providers, each product may have a different type, such as broadband, router, or switch. As a data analyst working with Calix, you want to find out which product type has the highest total sales quantity to identify the best selling product type. You need to answer the following question:

For each type of product, what is the total sales?

Assume that you have access to the following tables and .

Example Input:

Example Input:

Answer:

This query joins the and tables on the field. It then groups the results by and calculates the total quantity of products sold for each type using the aggregate function. The result is a list of product types along with the total quantity of each type that was sold.

Example Output:

This shows the total sales of each product type. For this simulated data, Broadband and Switch are the best selling product types with a cumulative sales quantity of 300.

SQL Question 10: Can you explain the purpose of the SQL constraint?

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.

SQL Question 11: Find Customer Records With Name Containing 'John'

You are provided with customer records of 'Calix' company. Can you write a SQL query to return all records of customers whose first name contains 'John'?

Example Input:

Answer:

This query works by using the keyword in SQL, which allows us to find patterns within strings using wildcard characters. The '%' is a wildcard character that matches any sequence of characters (including zero characters). Therefore, will match any names that contain 'John' anywhere within them. With this query, customers with 'John' within their first name will be returned, including 'John Doe', 'Johnny Appleseed', and 'Johannes Bach'.

Preparing For The Calix SQL Interview

The best way to prepare for a Calix SQL interview is to practice, practice, practice. Beyond just solving the earlier Calix SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Microsoft, Google, Amazon, and tech startups.

Each exercise has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there is an online SQL code editor so you can right in the browser run your SQL query answer and have it graded.

To prep for the Calix SQL interview you can also be useful to solve SQL problems from other tech companies like:

• Huawei SQL questions

• Nokia SQL questions

• ZTE SQL questions

• verizon SQL questions

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

This tutorial covers SQL concepts such as RANK vs. DENSE RANK and filtering data with boolean operators – both of which show up routinely in SQL job interviews at Calix.

Calix Data Science Interview Tips

What Do Calix Data Science Interviews Cover?

In addition to SQL interview questions, the other types of questions tested in the Calix Data Science Interview are:

• Probability & Stats Questions
• Python Pandas or R Coding Questions
• Product-Sense Questions
• ML Interview Questions
• Behavioral & Resume-Based Questions

How To Prepare for Calix Data Science Interviews?

To prepare for Calix Data Science interviews read the book Ace the Data Science Interview because it's got:

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