iOPEX Technologies Data Analyst Interview Questions and Answers

Q1. Tableau interview questioins
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Q2. SQl based quetions
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Q1. Introduce yourself
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It was an on campus recruitment drive with questions mostly on basic statistics and algebra.

In round 2 the interviewer asked to explain one of my project and then write code for longest common substring problem.

One Simple coding problem followed with couple of probability questions and explaining the Simple Linear model in detail.

2nd round consists of 10 MCQ and 2 python coding Question

1. 2 coding questions - easy to medium type.
2. Basic machine learning/data science MCQ's

Q1. 1. Resume based questions. 3. Machine learning/deep learning/data science related common questions. 4.Data proprocessing, data cleaning common interview questions.
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Q2. Questions related to projects done.
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Basic data structures, puzzles questions and statistics problems

Q1. What was your previous company project
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Q2. What are different types of indexing
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Different types of indexing include primary indexing, secondary indexing, clustered indexing, and non-clustered indexing.
• Primary indexing: Index based on the primary key of a table, typically implemented using a B-tree structure.

• Secondary indexing: Index based on a non-primary key column, allowing for faster retrieval of data based on that column.

• Clustered indexing: Physically reorders the table based on the indexed co...read more
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Q3. How does random forest work
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Random forest is an ensemble learning method that builds multiple decision trees and merges their predictions.
• Random forest creates a set of decision trees from randomly selected subsets of the training data.

• Each tree in the random forest independently predicts the outcome, and the final prediction is made by averaging the predictions of all the trees.

• Random forest is effective in handling high-dimensional data and can...read more
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Q4. Explain over fitting
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Overfitting occurs when a model learns the noise in the training data rather than the underlying pattern.
• Overfitting happens when a model is too complex and captures noise in the training data.

• It leads to poor generalization to new, unseen data.

• Regularization techniques like L1/L2 regularization can help prevent overfitting.

• Cross-validation can be used to detect and prevent overfitting.

• Example: A decision tree with too...read more
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Q5. Explain macros inExcel
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Macros in Excel are automated sequences of commands that can be created to perform repetitive tasks.
• Macros can be recorded or written using Visual Basic for Applications (VBA)

• They can automate tasks such as formatting, data manipulation, and calculations

• Macros can be assigned to buttons or keyboard shortcuts for easy access

• They can save time and reduce errors in repetitive tasks
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