Infosys IT (Data Analytics) Interview Questions and Answers

Q1. What is time series?
Ans. 
Time series is a sequence of data points collected at regular time intervals, used to analyze trends and patterns over time.
• Time series data is ordered chronologically

• Commonly used in forecasting future values based on past patterns

• Examples include stock prices, weather data, and sales figures
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Q2. How do you handle missing values in dataset?
Ans. 
Handle missing values using techniques like imputation, deletion, or modeling.
• Use imputation techniques like mean, median, mode for numerical data

• For categorical data, use mode or create a new category for missing values

• Consider using advanced techniques like KNN imputation or predictive modeling

• Delete rows or columns with high percentage of missing values if appropriate
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Q1. About your self
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Q2. Why should I hire you ?
Ans. 
I have a strong background in data analytics, with proven experience in delivering actionable insights and driving business growth.
• I have a solid understanding of statistical analysis and data visualization techniques.

• I am proficient in using tools such as Python, R, SQL, and Tableau to analyze and interpret data.

• I have a track record of successfully identifying trends and patterns in data to inform strategic decision-...read more
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Q3. What'sis strength ? Not asking weeknes..
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Q4. Why should I need this job?
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You should hire me for my strong analytical skills, experience in data analytics, and passion for problem-solving.
• I have a proven track record of successfully analyzing data to provide valuable insights and recommendations.

• My expertise in data visualization tools like Tableau and Power BI can help in presenting complex data in a clear and understandable manner.

• I am constantly learning and adapting to new technologies a...read more
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Q5. Why are you choosing this job?
Ans. 
I am choosing this job because of my passion for data analysis and the opportunity to make a meaningful impact through insights.
• Passion for data analysis and problem-solving

• Opportunity to make a meaningful impact through insights

• Interest in working with data-driven decision-making processes
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