Proftware Senior Data Analyst Interview Questions and Answers

Good questions. 3 SQL case studies at end

Q1. Power BI, SQL, Excel technical questions
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Q1. Bias variance trade off
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Q2. What is AB testing
Ans. 
AB testing is a method used to compare two versions of a webpage or app to determine which one performs better.
• AB testing involves creating two versions (A and B) of a webpage or app with one differing element

• Users are randomly assigned to either version A or B to measure performance metrics

• The version that performs better in terms of the desired outcome is selected for implementation

• Example: Testing two different call...read more
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Q3. Basic traditional ML question about ML metrics, bagging boosting etc.
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It was a classification problem

Q1. Questions about assignment
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Q2. Questions from resume.
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Q3. Questions based on probability, statistics and loss functions
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Q1. Explain about prev projects
Ans. 
I have worked on projects involving data analysis, visualization, and predictive modeling.
• Developed predictive models using machine learning algorithms

• Performed data cleaning and preprocessing to ensure data quality

• Created interactive dashboards for data visualization

• Collaborated with cross-functional teams to derive insights from data
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Q2. Windows function based sql question
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Well designed to test the aptitude competence of the candidate.

Q1. Explanations for the answers given to the aptitude questions.
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Q2. Questions from python.
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Q1. Coalesce, SQL Order of Execution
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Q2. Given a table with fields(id, name, salary, managerId) find out the managers who have atleast 5 reportees under him/her.
Ans. 
Use SQL query to count number of reportees for each manager and filter out those with atleast 5 reportees.
• Write a SQL query to count number of reportees for each manager using GROUP BY clause

• Add HAVING clause to filter out managers with atleast 5 reportees

• Example: SELECT managerId, COUNT(id) AS num_reportees FROM table_name GROUP BY managerId HAVING num_reportees >= 5
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Q3. How to manage large datasets in python
Ans. 
Use libraries like pandas and dask to efficiently manage large datasets in Python.
• Use pandas library for data manipulation and analysis.

• Use dask library for parallel computing and out-of-core processing.

• Optimize memory usage by loading data in chunks or using data types efficiently.

• Consider using cloud services like AWS S3 or Google BigQuery for storing and processing large datasets.
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Q4. Name few of the commonly used python libraries used by DA
Ans. 
Some commonly used Python libraries for Data Analysts are Pandas, NumPy, Matplotlib, and Scikit-learn.
• Pandas - used for data manipulation and analysis

• NumPy - used for numerical computing and working with arrays

• Matplotlib - used for data visualization

• Scikit-learn - used for machine learning and data mining
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