Netlink Software Data Analyst Interview Questions and Answers for Experienced

SQL and python questions are very easy.

Basic aptitude and coding question

Q1. It goes for two rounds
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Q2. Moderate sql question regarding joins have where cluase
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Q1. It take only 10 minutes
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Q1. Probability related questions and 1 coding easy leetcode question
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Though I applied for Data Analyst position through campus Recruitment Program (Kolkata). It had MCQs and Coding test, but surprisingly the MCQs were about Java, OOPs concept and basic coding questions. Hardly any ML or Analytics related like Python, SQL or BI tools related questions. As if I appeared for SDE role, not sure why it happened, but later I came to know they hired none from our college.

This did not happen, as they didn't call anyone from our college.

Easy question. Easy to clear the round

Q1. One to one technical questions based on SQL and python.
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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
Ans. 
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
Ans. 
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
Ans. 
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
Ans. 
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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