10 Clearwater Analytics SQL Interview Questions (Updated 2024)

At Clearwater Analytics, SQL is crucial for extracting and manipulating financial data for analysis, especially in their Prism data reporting division. Because of this, Clearwater Analytics almost always asks SQL questions during interviews for Data Analytics, Data Science, and Data Engineering jobs.

As such, to help you prepare for the Clearwater Analytics SQL interview, we've collected 10 Clearwater Analytics SQL interview questions – can you answer each one?

10 Clearwater Analytics SQL Interview Questions

SQL Question 1: Identify Clearwater Analytics Power Users

Clearwater Analytics is a data-driven company that provides investment portfolio reporting and analytics. They rely on a set of power users who regularly upload financial data, provide extensive feedback, and use their system consistently.

You are given two tables: and . The table stores user details like user_id, name, and registered_date. The table records the daily activities of the users like data upload, request generation, logins, etc.

Let's define a "Power User" as a user who has logged in more than 20 times, uploaded data more than 15 times and generated reports more than 10 times in the past month. Write a SQL query to identify these power users for the past month.

Table Example Input:

Table Example Input:

Answer:

This query identifies the power users by joining the two tables on . It chooses the users who have the required activity number in the past month. We use the clause to set the conditions for 'Power Users'. Each with a statement acts as a filter for each type of user activity.

To practice a similar VIP customer analysis question on DataLemur's free interactive coding environment, try this Microsoft Azure Cloud SQL Interview Question:

SQL Question 2: Analysis of Portfolio Performance

As a part of a team at Clearwater Analytics, you would be working with a lot of financial data. Imagine you are given a table called where each row gives information for a particular portfolio at a particular period end date.

The structure of the table is shown below:

Example Input:

Your task is to write a PostgreSQL query that ranks each portfolio by their return percent for each period and finds the cumulative return for each portfolio by period.

You will output a table with columns portfolio_id, period_end_date, rank, and cumulative_return where portfolios are ranked in a descending order by return_percent for each period. Cumulative return is calculated as the total return until that period for each portfolio.

Answer:

In the provided query, we first create a CTE that calculates the rank of each portfolio's return for each period. Then we create another CTE, , that calculates the cumulative return for each portfolio by period. Finally, we join these two CTEs on and to return the desired columns.

To solve a related window function SQL problem on DataLemur's free interactive SQL code editor, try this Google SQL Interview Question:

SQL Question 3: What is a self-join?

A self-join is a type of JOIN where a table is joined to itself. To execute a self-join, you must include the table name twice in the FROM clause and assign a different alias to each instance. You can then join the two copies of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.

For instance, suppose you had website visitor data for Clearwater Analytics, exported from the company's Google Analytics account. To assist the web-dev team, you needed to analyze pairs of pages for UX or navigational issues. As part of that analysis, you wanted to generate all pairs of URLs, but needed to exclude pairs where both URLs were the same since that is not a valid pair."

You could use the following self-join:

This query returns the url of each page () along with the url of the page that referred to it (). The self-join is performed using the field, which specifies the id of the page that referred the visitor to the current page, and avoids any pages that referred themself (aka data anomalies).

SQL Question 4: Analysis of Assets Portfolio Holdings

Clearwater Analytics is a global SaaS solution for automated investment data aggregation, reconciliation, accounting, and reporting. Suppose, you are tasked with analyzing the assets portfolio holdings for their clients. Each client holds multiple assets and the market value of these assets changes over time. You are asked to design a database that helps in analyzing the change in total portfolio value over a given period.

To solve this problem, your database design will need at least two tables:

Sample Input:

Sample Input:

You need to find the total value of each client's portfolio for a specific date and how it changed over time.

Answer:

The PostgreSQL query to solve this problem would be:

The above query partitions the data by and then orders it by . Then the sum function aggregates the over each partition. The clause restricts the data to the given date range.

Please note, this is a basic example and might need adjustments and additional conditions depending on your specific application and the other data you might have in your database.

SQL Question 5: How does differ from just ?

Both and are used to combine the results of two or more SELECT statements into a single result set.

However, only includes one instance of a duplicate, whereas includes duplicates.

SQL Question 6: Analyzing Ad Click-Through Rates

Clearwater Analytics is interested in understanding the efficacy of its digital marketing campaigns. To do this, they want to analyze the click-through rates (CTR) of their digital ads.

They measure CTR as the number of clicks on an ad divided by the number of impressions (how many times the ad was displayed). They're also interested in knowing the conversion rate to product page viewings from those who clicked the ad.

You are given two tables: and .

• The table records each time an ad was displayed to a user.
• The table records each time a user actually clicked on the displayed ad.

Example Input:

Example Input:

The company wants to know the CTR and average conversions_to_product_view per displayed ad for each ad_id.

Answer:

This SQL query first joins the impressions and clicks tables using LEFT JOIN to ensure all impressions are accounted for, even if they did not result in a click. The CTR calculation yields the click-through rate, while the AVG function calculates the average conversions for each ad.

The final output will be a table showing the ad_id, the click-through rate, and the average conversions to a product view resulting from those clicks, ordered by CTR and avg_conversions in descending order.

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

SQL Question 7: Can you describe the different types of joins in SQL?

Joins in SQL allow you to combine data from different tables based on a shared key or set of keys.

Four JOIN types are available in SQL. For an example of each one, say you had sales data exported from Clearwater Analytics's Salesforce CRM stored in a PostgreSQL database, and had access to two tables: and .

• : retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the Sales table and the Customers table would retrieve only the rows where the customer_id in the Sales table matches the customer_id in the table.
• : retrieves all rows from the left table (in this case, the sales table) and any matching rows from the right table (the table). If there is no match in the right table, NULL values will be returned for the right table's columns.
• : retrieves all rows from the right table (in this case, the customers table) and any matching rows from the left table (the sales table). If there is no match in the left table, NULL values will be returned for the left table's columns.
• : retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, NULL values will be returned for the columns of the non-matching table.

SQL Question 8: Find Customers With Specific Email Domain

As a data analyst in Clearwater Analytics, you are tasked to identify all customers whose email addresses are from the domain 'clearwater.com'. We are interested to find out their full names, city of residence, and the date they joined Clearwater Analytics.

The database stores customer information in a table named .

Example Input:

Example Output:

Answer:

The SQL query will filter customers whose email contains '@clearwater.com'. The LIKE keyword in PostgreSQL allows us to perform pattern matches which is essential in obtaining our desired records. The '%' before '@clearwater.com' checks for any sequences of characters before the domain name.

SQL Question 9: Calculate Percentage Change of Monthly Sales Revenue

Clearwater Analytics is interested in tracking the monthly performance of their sales. Specifically, they would like to calculate the percentage change in total sales revenue for each product from one month to the next.

You have the following table, which contains all sales transactions:

Example Input:

The company would like to see an output that displays the percentage change in total sales revenue for each product, month-on-month.

Calculate this percentage change and round it to two decimal places.

Example Output:

In the above output table, for product_id 300, the monthly revenue in May is 150 (1510.00), in June is 300 (2015.00), so the percentage change from May to June is (300-150)/150*100% = 100.00%.

Answer:

The query first calculates the total revenue for each product for each month. It then calculates the month-over-month percentage change in revenue for each product. The final SELECT statement filters out any rows where a percentage change could not be calculated (i.e., where there was no prior month of sales).

To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for requiring tracking of growth using SQL window functions or this Amazon Highest-Grossing Items Question which is similar for requiring analysis of sales data.

SQL Question 10: What's the difference between a one-to-one and one-to-many relationship?

When designing a database schema, 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 car and a license plate - each car has one license plate, and each license plate belongs to one car.

On the other hand, a one-to-many relationship is when one entity can be associated with multiple instances of the other entity. For example, a person can have multiple email addresses, but each email address only relates back to one person.

Preparing For The Clearwater Analytics SQL Interview

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. In addition to solving the above Clearwater Analytics SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Microsoft, Google, and Facebook.

Each interview question has multiple hints, step-by-step solutions and most importantly, there's an interactive coding environment so you can right online code up your SQL query and have it executed.

To prep for the Clearwater Analytics SQL interview it is also a great idea to practice SQL problems from other tech companies like:

• BlackRock SQL questions

• IHS Markit SQL questions

• Affirm SQL questions

• Adyen SQL questions

But if your SQL coding skills are weak, forget about going right into solving questions – improve your SQL foundations with this free SQL for Data Analytics course.

This tutorial covers topics including sorting results with ORDER BY and joins – both of these pop up routinely in SQL interviews at Clearwater Analytics.

Clearwater Analytics Data Science Interview Tips

What Do Clearwater Analytics Data Science Interviews Cover?

Besides SQL interview questions, the other types of problems covered in the Clearwater Analytics Data Science Interview are:

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

How To Prepare for Clearwater Analytics Data Science Interviews?

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