Elder Projects Data Analyst Interview Questions and Answers

It was simple but lengthy

Q1. Tell me about yourself
Ans. 
I am a data analyst with a strong background in statistics and data visualization.
• Graduated with a degree in Statistics

• Proficient in programming languages like Python and R

• Experience in analyzing large datasets and creating data visualizations

• Strong problem-solving skills
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Q2. About resume and technical
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Q1. Excel shortcut keys?
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Q2. WHAT IS THE ROLE OF DATA ANALYST?
Ans. 
Data Analysts are responsible for collecting, processing, and analyzing data to help organizations make informed decisions.
• Collecting and organizing data from various sources

• Cleaning and processing data to ensure accuracy and reliability

• Analyzing data to identify trends, patterns, and insights

• Creating visualizations and reports to communicate findings

• Providing recommendations based on data analysis

• Collaborating with st...read more
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Q3. What are the skills need for data analyst?
Ans. 
Skills needed for data analyst include strong analytical skills, proficiency in data analysis tools, programming knowledge, and communication skills.
• Strong analytical skills to interpret complex data sets

• Proficiency in data analysis tools such as Excel, SQL, Python, R, etc.

• Programming knowledge to manipulate and analyze data effectively

• Communication skills to present findings and insights to stakeholders
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They conduct written test

Q1. Asking questions like ur skills and qualification
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Q2. Which option u prefer quality or ontime delivery
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Q1. Asking about ur capabilities
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Q1. Tell me about the project you have worked recently
Ans. 
Developed a predictive analytics model to forecast customer churn for a telecom company
• Used Python and SQL to clean and analyze customer data

• Implemented machine learning algorithms such as logistic regression and random forest

• Evaluated model performance using metrics like accuracy, precision, and recall
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Q2. What kind of forecasting have you done
Ans. 
I have experience in time series forecasting using statistical models and machine learning algorithms.
• Utilized ARIMA model to forecast sales data for a retail company

• Implemented Prophet algorithm to predict stock prices for a financial institution

• Used LSTM neural network for demand forecasting in supply chain management
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Excel assessment- was made to make a report from multiple sheets

1 hour baisc on general aptitude