Comcast India Engineering Center Data Engineer 3 Interview Questions and Answers

Q1. Basicn details to check for qualifications
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Q1. About my projects
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Q1. More details about ML models
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Python Programming related questions, along with one advanced SQL query problem. The final question was a Data Science project on prediting sales potential of various outlets.

Q1. Pattern based - Three memory chips, each of 1GB. You have to store 3GB of data in these chips in such a way that even if one memory chip is corrupted, no data is lost.
Ans. 
Use RAID 5 to store data across all three memory chips with parity bits for fault tolerance.
• Implement RAID 5 to distribute data and parity bits across all three memory chips.

• If one memory chip is corrupted, the data can be reconstructed using the parity bits from the other two chips.

• Example: Store 1GB of data on each chip and use the remaining space for parity bits to ensure fault tolerance.
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Q2. DSA question - Get the longest common prefix string from a list of strings
Ans. 
Find the longest common prefix string from a list of strings.
• Iterate through the characters of the first string and compare with corresponding characters of other strings

• Stop when a mismatch is found or when reaching the end of any string

• Return the prefix found so far
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Q3. DBMS question - What are joins and what are their types?
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Joins are used in DBMS to combine rows from two or more tables based on a related column between them.
• Types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.

• INNER JOIN returns rows when there is at least one match in both tables.

• LEFT JOIN returns all rows from the left table and the matched rows from the right table.

• RIGHT JOIN returns all rows from the right table and the matched rows from the left tab...read more
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Q4. ML and DL question - Activation functions, Exploding and Vanishing Gradient problems, LSTM and GRU models frameworks and differences.
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Was taken by the product manager employed in the company. Basic case study question regarding a ride share app planning to expand internationally.

A formal orientation and introduction with the VP and founder of ION India

Q1. Introduce yourself and mention your work that makes you relevant for the job.
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Q2. Is there any correlation between algorithms and law?
Ans. 
Algorithms and law can be correlated through the use of algorithms in legal processes and decision-making.
• Algorithms can be used in legal research to analyze large amounts of data and identify patterns or trends.

• Predictive algorithms can be used in legal cases to assess the likelihood of success or failure.

• Algorithmic tools can help in legal document review and contract analysis.

• However, there are concerns about bias i...read more
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Written test, asked general question for testing our skills

Q1. Asked about me and why you are choosing our company
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Q2. Asked regarding my internship project
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Q1. Asked my goals and future planning
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Q2. Asked about my weakness and strength
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Q1. Cache vs persist
Ans. 
Cache is used for temporary storage of data in memory, while persist is used for saving data to disk for long-term storage.
• Cache is typically faster as it stores data in memory for quick access.

• Persist saves data to disk for durability and long-term storage.

• Cache is often used for temporary data that can be recomputed if lost, while persist is used for important data that needs to be retained.

• Examples: Using cache for ...read more
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Q2. Broadcast join and other optimization techniques
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Q1. Sql window function
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Q2. Spark architecture, dataframe vs rdd
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Q3. Python reverse sentence
Ans. 
Reverse a sentence using Python
• Split the sentence into words using split() method

• Reverse the list of words using list slicing

• Join the reversed list of words back into a sentence using join() method
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Q4. Join based on nulls in sql
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Q1. Tell me about your self?
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Q2. What technology & tools u know ? And basic questions regarding that topics ?
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Q1. Job culture and job responsibilities ?
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Q2. Some questions on an analytical tools like power BI ?
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Q1. Write a lambda function in python
Ans. 
A lambda function in Python is a small anonymous function defined using the lambda keyword.
• Lambda functions can have any number of arguments, but can only have one expression.

• Syntax: lambda arguments : expression

• Example: lambda x, y : x + y
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Q2. Dbutils in databricks
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dbutils is a utility provided by Databricks for interacting with files and directories in the Databricks environment.
• dbutils.fs.ls('/') - list files in root directory

• dbutils.fs.cp('dbfs:/file.txt', 'file.txt') - copy file from DBFS to local file system

• dbutils.fs.mkdirs('dbfs:/new_dir') - create a new directory in DBFS
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Q3. Persist and cache
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Q4. What is commit in SQL
Ans. 
A commit in SQL is a command that saves all the changes made in a transaction to the database.
• A commit is used to make all the changes made in a transaction permanent.

• Once a commit is issued, the changes cannot be rolled back.

• It is important to use commit to ensure data integrity and consistency.

• Example: COMMIT; - this command is used to commit the changes in a transaction.
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Q5. Rank and dans_rank
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It contain both Aptitude and Coding about base models and Deep learning too

Q1. What different models technique ?
Ans. 
Different models techniques include linear regression, decision trees, random forests, support vector machines, and neural networks.
• Linear regression is used for predicting continuous values.

• Decision trees are used for classification and regression tasks.

• Random forests are an ensemble method based on decision trees.

• Support vector machines are used for classification tasks.

• Neural networks are used for complex pattern re
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Q2. What are performance metric where to use what?
Ans. 
Different performance metrics are used for different types of machine learning models to evaluate their effectiveness.
• For classification models, metrics like accuracy, precision, recall, F1 score, and ROC-AUC are commonly used.

• For regression models, metrics like mean squared error (MSE), mean absolute error (MAE), and R-squared are commonly used.

• For clustering models, metrics like silhouette score and Davies-Bouldin in...read more
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Q1. Explain about Project
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Q2. What are problems faced in that project?
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