Aress Software and Education Technologies Data Analyst Interview Questions and Answers

Q1. About your self
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Q2. Communication skills
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Q1. Programming language
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Q2. What tools do you utilize for data analysis?
Ans. 
I utilize tools such as Excel, Python, SQL, and Tableau for data analysis.
• Excel for basic data manipulation and visualization

• Python for advanced data analysis and machine learning

• SQL for querying databases

• Tableau for creating interactive visualizations
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Q3. Pandas numpy seaborn matplot
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Data analysis of code in the context of data analysis.

Coding logical question paper.

Basics of mathematical ability and verbal ability

Q1. Introduction - explain projects
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Q2. Data analytics explain
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Sql python bigdata hadoop hive spark

1 hour simple coding python sql

Q1. Advantages of sql
Ans. 
SQL allows for efficient data retrieval, manipulation, and analysis in relational databases.
• SQL is widely used in querying databases to retrieve specific data.

• It allows for data manipulation, such as adding, updating, and deleting records.

• SQL can perform complex data analysis tasks, such as aggregations and joins.

• It provides a standardized language for interacting with relational databases.

• SQL is essential for generati...read more
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Q2. Advantages of python
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Python is a versatile programming language known for its simplicity, readability, and vast library support.
• Easy to learn and use, making it ideal for beginners and experienced programmers alike

• Extensive library support for data analysis, machine learning, web development, and more

• Strong community support with active forums and resources for problem-solving

• Cross-platform compatibility allows for seamless integration wit...read more
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Q3. Spark and its benefits
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Spark is a fast and powerful big data processing framework that offers benefits like speed, ease of use, and versatility.
• Spark is known for its speed, as it can process data up to 100 times faster than traditional Hadoop MapReduce.

• It offers ease of use with high-level APIs in Java, Scala, Python, and SQL, making it accessible to a wide range of users.

• Spark is versatile, supporting various workloads such as batch proces...read more
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Q4. Why to leave the company
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Q5. Huddles of data engineer
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Huddles of data engineers refer to collaborative meetings or discussions among data engineers to share insights, solve problems, and make decisions.
• Huddles are typically informal and can be scheduled or ad-hoc.

• They provide a platform for data engineers to brainstorm, troubleshoot, and exchange ideas.

• Huddles may involve reviewing code, discussing data pipelines, or addressing technical challenges.

• Effective huddles promo...read more
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Online aptitude test with maths and statistics and data analysis

Q1. Joins sql groups python numpy pandas
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Q1. How to perform Set Actions, LOD's
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Q1. General discussion of background and technical interview availability.Expected Salary,current salary
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Q1. Tell me about yourself.
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Q2. Which project have you recently worked on?
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Q3. How much experience do you have in python and R?
Ans. 
I have 3 years of experience in Python and 2 years in R.
• 3 years of experience in Python, used for data cleaning, analysis, and visualization.

• 2 years of experience in R, utilized for statistical analysis and data modeling.

• Proficient in using libraries like pandas, numpy, matplotlib in Python and ggplot2, dplyr in R.
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Q4. What project have you worked on in R programming?
Ans. 
I have worked on a project in R programming analyzing customer churn for a telecommunications company.
• Used R programming to clean and analyze customer data

• Created visualizations to identify patterns and trends in customer behavior

• Built predictive models to forecast customer churn rates

• Collaborated with stakeholders to present findings and recommendations
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Q5. Which databases have you worked on?
Ans. 
I have worked on databases such as MySQL, SQL Server, and MongoDB.
• MySQL

• SQL Server

• MongoDB
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Q6. Given a list of strings, find the string matching a particular pattern.
Ans. 
Find a string matching a specific pattern in a list of strings.
• Use regular expressions to search for the pattern in each string.

• Iterate through the list of strings and apply the pattern matching logic.

• Return the string that matches the pattern, if found.

• Example: List of strings - ['apple', 'banana', 'cherry'], pattern - 'ba' would return 'banana'.
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Q7. Given a list of dictionary, find the dictionary which has the count of key highest among all the dictionaries. eg: [{a:5},{b:2}.......] Now here 5 is the highest key value so it should be printed.
Ans. 
Find the dictionary with the highest count of keys in a list of dictionaries.
• Iterate through the list of dictionaries and keep track of the dictionary with the highest count of keys.

• Use a loop to count the keys in each dictionary and compare it with the current highest count.

• Return the dictionary with the highest count of keys.
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Q8. Do you have experience in converting python scripts to R?
Ans. 
Yes, I have experience in converting Python scripts to R.
• I have converted several Python scripts to R for data analysis projects.

• I am proficient in both Python and R programming languages.

• I can provide examples of projects where I have successfully converted Python scripts to R.
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Q1. Basis HR questions
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Q2. Answer confidently
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Q1. Based on previous work
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Q2. Answer correctly what you had worked in your previous work
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