DaMENSCH Business Analyst Interview Questions and Answers

Basic coding qns and aptitude questions which can be done easily

They gave guesstimate questions where scenarios will be given and you have to give an approximate estimate to it based on various factors

SQL, excel, tableau , looker studio

Q1. What is your notice period.
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Q1. Difference between logistic regression and svm
Ans. 
Logistic regression is a linear model used for binary classification, while SVM is a non-linear model that can handle complex decision boundaries.
• Logistic regression is a probabilistic model that predicts the probability of a binary outcome based on input features.

• SVM aims to find the hyperplane that best separates the classes in a high-dimensional space.

• Logistic regression is more interpretable and easier to implement...read more
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Q2. Data augmentation related questions
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Q1. Introduce yourself
Ans. 
I am a dedicated and experienced professional with a background in marketing and a passion for driving results.
• Experienced in marketing strategies and campaigns

• Strong track record of achieving goals and targets

• Passionate about driving results and exceeding expectations
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Q2. Strengths and weaknesses
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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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Q1. There was just 1 to on chatting - i believe the interviewer himself doesn't know anything
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Q2. What's your name?
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Q3. Previous job detials
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Q4. Expectations in this company
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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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