HyperVerge Data Analyst Interview Questions and Answers

Q1. Difference between Drop and Truncate ?
Ans. 
Drop deletes the table structure and data, while truncate only deletes the data.
• Drop is a DDL (Data Definition Language) command, while truncate is a DML (Data Manipulation Language) command.

• Drop removes the table from the database, while truncate only removes the rows from the table.

• Drop is slower and requires more permissions than truncate.

• Example: DROP TABLE table_name; TRUNCATE TABLE table_name;
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Q2. To write SQL queries
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Q1. Why you are switching to non-core?
Ans. 
I am switching to non-core because I want to explore new opportunities and challenges outside of my current field.
• Seeking new challenges and opportunities

• Exploring different industries and roles

• Developing new skills and gaining diverse experience
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Q2. What are your expected salary?
Ans. 
I am looking for a competitive salary that reflects my skills and experience in the data analysis field.
• Research the average salary for Data Analysts in your area to have a realistic expectation

• Consider your level of experience, education, and any specialized skills you bring to the table

• Be prepared to negotiate based on the company's budget and benefits package
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SQL -- LeetCode style questions Medium lvl

Q1. Past experiences
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Q2. How one can help with eshopbox
Ans. 
One can help with eshopbox by analyzing data to improve customer experience and optimize sales.
• Conduct data analysis to identify trends and patterns in customer behavior

• Use data to personalize marketing strategies and recommend products to customers

• Optimize website layout and user experience based on data insights

• Implement data-driven pricing strategies to maximize sales and profits
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Was asked about a case study regarding cost and profit, interviewer was observing my logical thinking and approach towards the problem.
Basically they'll check if you are covering all aspects or not.

SQL easy to medium level

Q1. Medium level SQL question
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Q2. Case study on Bigbasket/Instagram
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Prepare basics such as group by, case functions, aggregation and some theoretical part such as sequence of sql query execution, basic concepts of dbms

Case study on analytics side like think like a product analyst and define metrics for a feature for example feature that count your daily steps.

Q1. Culture related Queries
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Q2. Salary expectations and negotiation deal
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2 questions dsa based

Q1. Recursion based coding questions
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Q2. Resume , grill on projects
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Q1. Why sde inspite of having different background
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