Sony Data Analyst Interview Questions and Answers

Q1. Asked to create a power bi dashboard
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Q1. Had coding test on SQL and Python
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Q1. Sql rank order explain
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SQL rank order function explanation
• Rank order function in SQL assigns a rank to each row based on a specified column

• It can be used to determine the top or bottom N records in a dataset

• Example: SELECT column1, column2, RANK() OVER (ORDER BY column3 DESC) AS rank_order FROM table_name
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Q2. Merging two tables
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Merging two tables involves combining data from both tables based on a common key.
• Identify a common key between the two tables

• Use SQL JOIN statements to merge the tables

• Choose the appropriate type of join (e.g. inner join, outer join)

• Consider the size of the tables and the performance implications of the merge
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Q1. Tell me about yourself
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Q1. About yourself n work profile
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Q1. Explain IOT database
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IOT database is a database that stores data generated by Internet of Things (IOT) devices.
• IOT database is designed to handle large volumes of data generated by IOT devices.

• It stores data in a structured format that can be easily queried and analyzed.

• IOT databases often use NoSQL databases like MongoDB or Cassandra.

• Examples of IOT databases include AWS IoT Core, Azure IoT Hub, and Google Cloud IoT Core.
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How to ready for my work

Q1. What type of work do you typically perform in an office setting?
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Q2. How to developed for in team working
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Q1. Data engineering related
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Q1. Introduce yourself
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Q2. Expectations
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Q1. Offers and benefits
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Basic python questions

Q1. Explain xgboost
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XGBoost is a popular machine learning algorithm known for its speed and performance in gradient boosting.
• XGBoost stands for eXtreme Gradient Boosting.

• It is an implementation of gradient boosted decision trees designed for speed and performance.

• XGBoost is widely used in machine learning competitions and has become a popular choice for data scientists.

• It can handle missing data and is optimized for parallel processing.

• XG...read more
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Q2. Explain decision tree
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Decision tree is a predictive modeling tool that uses a tree-like graph of decisions and their possible consequences.
• Decision tree is a supervised learning algorithm used for classification and regression tasks.

• It breaks down a dataset into smaller subsets based on different attributes.

• Each internal node represents a feature or attribute, each branch represents a decision rule, and each leaf node represents the outcome...read more
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