RedBeryl Tech Solutions Frontend Developer Intern Interview Questions and Answers

Simple questions of quant and coding output

3 coding question and one pattern question

Q1. Discussions on questions of prev round
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Q2. One SQL query need to implement
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MCQ - 20 (aptitude), 20(c+ and sql)

Pattern, array and sql questions

Giva a Full stack project. based on MERN AND MEAN stack

Q1. Dsa , were easy to medium
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Q2. Some backend and azure related questions
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40 Minutes. 40 Question in office Test.
20 Questions Programming related and 20 Questions Aptitude

Basic Aptitude question were asked around 20 Question of Aptitude and 20 of basic debugging of C language code. Before aptitude there was a essay writing on "factors which increases the market of E-commerce platforms"

There were 4 coding question and 2 SQL questions. Basic pattern printing question and easy question of leetcode were there in coding and in SQL from "joins" topic.

Same as the previous round more question of Coding and SQL, plus in the starting they would ask about your tech stack and then assign you a stack for the same.

Basic knowledge required for the Aptitude Test. You need to understand the questions and their technicality and then each question is very easy.

Need to focus more on the SQL Queries and some average coding skills. This test is used to check the code understanding of the candidate.

Little more complex problems, need to understand the logic and some complex SQL Queries.
More Focus on JOINS in SQL.

Q1. Intro about Experience
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Q2. Knowledge on tools
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Q1. Sdfsfd kjdk dvfikjsf vsjv
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Q2. Sdjvks sdkvjsk skdcj
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Q1. What is normalization why use this
Ans. 
Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity.
• Normalization helps in reducing data redundancy by breaking down large tables into smaller ones.

• It ensures data integrity by minimizing data anomalies such as update, insert, and delete anomalies.

• Normalization follows a set of rules (normal forms) like 1NF, 2NF, 3NF, etc., to organize data efficiently.

• Example: ...read more
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