Avanze Technologies Indexing Abstracting Associate Interview Questions and Answers

Q1. Concepts on oops progressing the way that it will include
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Q2. Answers on the dilegent way
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Q1. How many year experience
Ans. I have 10 year experience same office
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Q2. When you will join company?
Ans. If i got selected i need 30 days paper period on my current office
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Q3. How much salary you will expected?
Ans. I will expect 20 k salary
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Q4. Are u interested to work night shift
Ans. Yes I interested day or night shift
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Q5. Are u interested to week end
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Q6. Why you resign your current office
Ans. I interested to learn new things that's only reason
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Q7. You interested voice or non voice job
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Q8. Tell me your interest skills
Ans. I am to work always sir
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Q1. Exceptions and thread implementation
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Q2. Basics of restful web services
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Q1. Finding the second maximum number in the list
Ans. 
To find the second maximum number in a list, sort the list in descending order and return the second element.
• Sort the list in descending order

• Return the second element in the sorted list
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Q1. Loops in Informatica
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Loops in Informatica are used to iterate over a set of data or perform repetitive tasks.
• Loops in Informatica can be implemented using the 'Expression' or 'Router' transformations.

• They are useful for processing multiple rows of data in a mapping.

• Common types of loops include 'While' and 'For' loops.

• Loops can help in performing complex data transformations and validations.
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Q1. What is the reason for change
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Two coding round in Javascript, first one to right CRUD operation in React.

Second one have to right JS for Flattened Array

Q1. Asking about Salary Structure
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Basic speaking test, english

Q1. What is your analysis of the graphs?
Ans. 
The graphs show a steady increase in sales over the past year.
• Sales have been consistently rising month over month.

• There was a significant spike in sales during the holiday season.

• The overall trend is positive and indicates growth in the business.
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Q1. Org fit check questions
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Q1. Explain random forest
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Random forest is an ensemble learning method that builds multiple decision trees and merges them to improve accuracy and prevent overfitting.
• Random forest is a type of ensemble learning method.

• It builds multiple decision trees during training.

• Each tree is built using a subset of the training data and a random subset of features.

• The final prediction is made by averaging the predictions of all the individual trees.

• Random...read more
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Q2. What is boosting
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Boosting is a machine learning ensemble technique where multiple weak learners are combined to create a strong learner.
• Boosting is an iterative process where each weak learner is trained based on the errors of the previous learners.

• Examples of boosting algorithms include AdaBoost, Gradient Boosting, and XGBoost.

• Boosting is used to improve the accuracy of models and reduce bias and variance.
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