Capgemini Engineering Senior Data Analyst Interview Questions and Answers

Q1. DAX Related Syntax and Codes
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Q2. Data Modelling, SQL, Python
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Q1. No Response from HR after calling of selection after Round 1
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It was related to Aptitude MCQ and 2-coding test

Q1. Palindrome of a number
Ans. 
A palindrome of a number is a number that remains the same when its digits are reversed.
• To check if a number is a palindrome, reverse the number and compare it with the original number.

• Examples: 121 is a palindrome, 123 is not a palindrome.
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Q2. Merge 2linked list
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Merging two linked lists involves combining the elements of both lists into a single list.
• Create a new linked list to store the merged elements

• Traverse through both linked lists and add elements to the new list

• Handle cases where one list is longer than the other
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Q3. About projects you have done
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Q1. Explain your resume fully
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Q2. General questions on the behaviour
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Q1. How to do model inference?
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Model inference is the process of using a trained machine learning model to make predictions on new data.
• Load the trained model

• Preprocess the new data in the same way as the training data

• Feed the preprocessed data into the model to make predictions

• Interpret the model's output to make decisions or take actions
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Q2. How to optimize spark query?
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Optimizing Spark queries involves tuning configurations, partitioning data, using appropriate data formats, and caching intermediate results.
• Tune Spark configurations for memory, cores, and parallelism

• Partition data to distribute workload evenly

• Use appropriate data formats like Parquet for efficient storage and retrieval

• Cache intermediate results to avoid recomputation
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Q1. Have you used GEN AI?
Ans. 
No, I have not used GEN AI in my work as a Data Scientist.
• I have not used GEN AI in any of my projects or analyses.

• I am not familiar with GEN AI and its capabilities.

• I have not had the opportunity to work with GEN AI in any capacity.
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Q2. How do you take your solution to production?
Ans. 
I take my solution to production by following a structured process involving testing, deployment, monitoring, and maintenance.
• Develop a robust testing strategy to ensure the solution performs as expected in a production environment

• Use continuous integration and continuous deployment (CI/CD) pipelines to automate the deployment process

• Implement monitoring tools to track the performance of the solution in real-time and a...read more
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Q1. Can you tell me about yourself? Why do you want to work as a data analyst? What do you know about our company?
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Q2. What are your short-term and long-term career goals in the field of data analysis? Why do you wish to pursue a career in data analysis? What factors motivate you to work in a data-driven environment?
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Asked the question about ml and basic python questions

Q1. Interesting facts about ourselves
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Q2. Introduced about ourselves
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Q1. 1. Basics of Python 2. Basics of ML like supervised and unsupervised learning
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