11 Bayanat AI SQL Interview Questions (Updated 2024)

At Bayanat AI, SQL is crucial for extracting and manipulating data from databases for AI model training, and running complex queries on geospatial data to find patterns and insights. That's the reason behind why Bayanat AI frequently asks SQL query questions in interviews for Data Science and Data Engineering positions.

So, to help you practice for the Bayanat AI SQL interview, we've curated 11 Bayanat AI SQL interview questions – able to answer them all?

11 Bayanat AI SQL Interview Questions

SQL Question 1: Identifying Power Users at Bayanat AI

Bayanat AI has a table , where each row represents an activity performed by the user. This could be uploading a new dataset, training a machine learning model, or making predictions with a model. Each activity has a weight associated with it, representing its importance to Bayanat AI's business.

Your task is to write a SQL query that identifies power users – users who have a total activity weight in the top 1% of all users for the previous month.

example input:

Answer:

In this query, the CTE sums the activity weights per user for the previous month. The CTE then calculates the percentile rank of these sums. Finally, the main query filters on users who fall in the top 1% according to their percentile rank.

To work on a similar customer analytics SQL question where you can solve it right in the browser and have your SQL code automatically checked, try this Walmart SQL Interview Question:

SQL Question 2: Compute the Monthly Average Rating of Each Product

Bayanat AI would surely be interested in understanding how their products perform over time. For this task, you're tasked to compute the monthly average rating of each product based on user reviews. Analyze the table, which has the following columns:

• : the unique identifier for each review.
• : the unique identifier of the reviewing user.
• : the date the review was submitted.
• : the unique identifier of the reviewed product.
• : the star rating of the product by the user, from 1 to 5.

You can utilize SQL window functions to compute the monthly average ratings.

Example Input:

Answer:

This SQL query is using a window function to calculate the average () rating for each product () at each month (. The clause is used to calculate the average for each combination of product and month separately.

The clause is then used to order the results by the month and product_id.

Example Output:

As per the output, it shows the average star rating of each product for every month.

To solve another window function question on DataLemur's free online SQL code editor, solve this Amazon SQL Interview Question:

SQL Question 3: What does do?

The function can take in multiple paramaters, and returns the first input paramater that is not null. If all arguments are null, the COALESCE function will return null too.

Suppose you have a table of Bayanat AI salespeople and the number of deals they closed. If a salesperson didn't close any deals, the data from the 3rd-party CRM system exports a NULL value.

To change these NULLs to zeros, you can use the function in the following way:

This would result in the following data:

SQL Question 4: Analyzing Traffic Data for Safety Measures

Bayanat AI is a leading data company that leverages AI to extract insights and promote safer environments. Let's assume that they are working on a project on traffic management for a city. They have a table which has recorded traffic data of all the roads in the city for each day. The company wants to identify the roads which have seen an average daily traffic of more than 5000 in the last 30 days.

The table has the following schema:

Example Input:

You need to write a PostgreSQL query to fetch the and average per day for the roads which have seen an average daily traffic of more than 5000 in the last 30 days. The result should be sorted by the .

Answer:

This query first filters the table for the entries in the last 30 days. Then it calculates the average for each using the and functions. The clause filters the results to only show the roads having an average of more than 5000. Finally, the results are sorted by the in ascending order.

SQL Question 5: Does a typically give the same results as a ?

No, in 99% of normal cases a and do NOT produce the same result.

You can think of more as set addition when it combines the results of two tables.

You can think of a more as set multiplication, producing all combos of table 1 with combos of table 2.

SQL Question 6: Filter Bayanat AI Customers Based on Subscription and Activity

Imagine you have a list of customers for Bayanat AI. The customer data includes the , , , and the . Write a query to filter out all customers who have a select_product of "Premium" and have been active in the last 30 days.

Example Input:

Example Output:

Answer:

This query filters out all the customers from the table where the is 'Premium' and the is within the last 30 days. It subtracts an interval of 30 days from the current date to capture customers active within this period.

SQL Question 7: What does the clause do vs. the clause?

The clause is used to filter the groups created by the clause. It's similar to the clause, but it is used to specify conditions on the groups created by the clause, rather than on the individual rows of the table.

For example, say you were analyzing salaries for analytics employees at Bayanat AI:

This query retrieves the total salary for each Analytics department at Bayanat AI and groups the rows by the specific department (i.e. "Marketing Analytics", "Business Analytics", "Sales Analytics" teams).

The clause then filters the groups to include only Bayanat AI departments where the total salary is greater than $1 million

SQL Question 8: Find the Total AI Models Used by Clients

Bayanat AI is a company specialized in AI technologies. Consider a situation where the company provides different types of AI models to its clients. Each client can use multiple models and each model usage would be saved in a log table. The task is to write a SQL query that shows the count of each AI model usage grouped by the clients for a given month.

Assume we have the following log data recorded in the table:

We want to see the result for January 2022 in the following format:

Answer:

Here is the PostgreSQL query to get the count of AI models usage grouped by clients:

This query first filters the logs for the month of January in the year 2022. It then groups records by month, client id, and model id to calculate the usage counts. The output of the query gives us the number of usages for each AI model by each client for the given month.

SQL Question 9: Filter Customer Records with a Specific Pattern

Assume you are an analyst in Bayanat AI and one of your tasks is to extract customer records based on their email domain for analysis. Your team is specifically interested in customers who use Gmail and Yahoo for their emails. Write a SQL query to filter all the customer records where the email domain is either Gmail or Yahoo.

Example Input:

Example Output:

Answer:

In the above query, we use the SQL keyword to filter all customer records where the email domain is either Gmail or Yahoo. The character is a wildcard in SQL that may represent zero, one, or multiple characters. Here, it is being used to match any string that precedes or ; in other words, any email that ends with or will be selected.

SQL Question 10: In SQL, Are NULL values the same as a zero or blank space?

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A value represents a missing or unknown value. It is different from a zero or a blank space, which are actual values.

It's important to handle values properly in SQL because they can cause unexpected results if not treated correctly. For example, comparisons involving values always result in . Also values are not included in calculations. For example, will ignore values in the column.

SQL Question 11: Calculating Monthly Average Sales With Round-Off

You work for Bayanat AI, and you are given sales data of your company that contains transaction_id, product_id, sales_date, and sales_amount. The task requires you calculate the monthly average sales rounded to two decimal places for each product separately, across the entire data.

Example Input:

Example Output:

Answer:

This SQL query first extracts the month from each transaction date, then groups all the entries by month and product_id. It computes the average sales_amount for each group, and rounds the result to two decimal places. The result is a table that displays the monthly average sales rounded to two decimal places for each product separately.

To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating sales metrics over time or this Amazon Average Review Ratings Question which is similar for averaging and grouping data per product.

Preparing For The Bayanat AI SQL Interview

The key to acing a Bayanat AI SQL interview is to practice, practice, and then practice some more! Besides solving the above Bayanat AI 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 problem on DataLemur has multiple hints, detailed solutions and best of all, there is an online SQL code editor so you can right in the browser run your SQL query and have it checked.

To prep for the Bayanat AI SQL interview you can also be helpful to solve SQL problems from other tech companies like:

• Palantir SQL questions

• C3.ai SQL questions

• Splunk SQL questions

• Databricks SQL questions

However, if your SQL query skills are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this SQL tutorial for Data Scientists & Analysts.

This tutorial covers SQL concepts such as manipulating string/text data and WHERE vs. HAVING – both of these pop up often during SQL interviews at Bayanat AI.

Bayanat AI Data Science Interview Tips

What Do Bayanat AI Data Science Interviews Cover?

In addition to SQL query questions, the other types of questions tested in the Bayanat AI Data Science Interview are:

• Probability & Statistics Questions
• Coding Questions in Python or R
• Product-Sense and Business Case Questions
• ML Interview Questions
• Behavioral & Resume-Based Questions

How To Prepare for Bayanat AI Data Science Interviews?

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