Random Trees Data Analyst Interview Questions and Answers

General Aptitude Questions

Q1. Queries on SQL, Basic Statistic Question related to normal curve, Basic Python question(from python interview question list of any website)
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Q2. Shape of normal Distribution
Ans. 
The shape of a normal distribution is bell-shaped and symmetrical.
• A normal distribution has a peak at the mean and tails that extend to infinity in both directions.

• The distribution is symmetrical, meaning that the left and right halves mirror each other.

• The standard deviation determines the spread or width of the distribution.

• Many natural phenomena and measurements in various fields follow a normal distribution.

• Example...read more
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Q3. Valuess of mean median and mode
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Mean, median, and mode are measures of central tendency in statistics.
• Mean is the average of a set of numbers, calculated by summing all the values and dividing by the total count.

• Median is the middle value in a sorted list of numbers. If there is an even number of values, it is the average of the two middle values.

• Mode is the value that appears most frequently in a set of numbers. It can be a single value or multiple
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Q1. General HR questions
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Q1. General discussion round with ceo and about projects
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Q1. Advance level sql questions
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Q1. Sql concepts and scenarios
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Q1. Intermediate and Advanced SQL Questions, for best, try leetcode sql practice.
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Basics of SQL was asked, having good foundation will really help in clearing this round

It wa really a great experience.

It was really a great experience.

Q1. Where do you see yourself after 3 years?
Ans. 
In 3 years, I see myself leading a team of data engineers, implementing cutting-edge technologies, and driving impactful data-driven decisions.
• Leading a team of data engineers

• Implementing cutting-edge technologies

• Driving impactful data-driven decisions
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Q2. What are your strenghts?
Ans. 
My strengths include strong analytical skills, attention to detail, and the ability to work well in a team.
• Strong analytical skills - able to analyze complex data sets and derive meaningful insights

• Attention to detail - meticulous in ensuring data accuracy and quality

• Team player - collaborate effectively with colleagues to achieve common goals
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Q1. What projects you have worked upon?
Ans. 
I have worked on projects involving building data pipelines, optimizing database performance, and creating machine learning models.
• Built data pipelines using Apache Spark and Kafka

• Optimized database performance by tuning queries and indexes

• Created machine learning models for predictive analytics

• Implemented real-time data processing using technologies like Apache Flink
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Q2. What is your CGPA?
Ans. 
My CGPA is 3.8 out of 4.0.
• My CGPA is 3.8, which is considered high in my university.

• I have consistently maintained a high CGPA throughout my academic career.

• I have received several academic awards based on my CGPA.

• My CGPA reflects my dedication and hard work towards my studies.
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Q3. What are your hobbies?
Ans. 
My hobbies include hiking, photography, and playing the guitar.
• Hiking: I enjoy exploring nature trails and challenging myself physically.

• Photography: I love capturing moments and landscapes through my camera lens.

• Playing the guitar: I find relaxation and creativity in strumming chords and learning new songs.
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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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Q1. Basic 10-15btheorotical question
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Q2. Join + window funct question
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