Cognizant Data Engineer Interview Questions, Process, and Tips

Q1. Why you want to join cognizant
Ans. 
I want to join Cognizant because of its reputation for innovation and growth opportunities.
• Cognizant is known for its cutting-edge technology solutions

• I am impressed by Cognizant's commitment to employee development

• I believe Cognizant will provide me with a challenging and rewarding work environment
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Q2. Why are you looking for only data engineer role.
Ans. 
I am passionate about working with data and enjoy the challenges and opportunities that come with being a data engineer.
• I have a strong background in data engineering and enjoy working with data processing technologies such as Hadoop, Spark, and Kafka.

• I find data engineering to be a dynamic and evolving field that allows me to continuously learn and grow my skills.

• I am excited about the impact that data engineering can...read more
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Q1. Sql related questions
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Q2. Hive related questions
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Q1. Word count by spark,, falt map and map difference
Ans. 
Word count by spark, flatMap, and map difference
• Spark is a distributed computing framework for big data processing

• flatMap is used to split each input string into words

• map is used to transform each word into a key-value pair for counting

• The difference lies in how the data is processed and transformed
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Q2. Flat map and map difference
Ans. 
Flat map is used to flatten nested arrays while map is used to transform each element in an array.
• Flat map is used to flatten nested arrays into a single array.

• Map is used to transform each element in an array using a function.

• Flat map is commonly used in functional programming languages like JavaScript and Scala.

• Map is a higher-order function that applies a given function to each element in an array.
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Q3. Pationong and bucket difference
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Partitioning is dividing data into smaller chunks for better organization and performance, while bucketing is grouping data based on a specific criteria.
• Partitioning is dividing data into smaller subsets based on a column or key.

• Bucketing is grouping data based on a specific number of buckets or ranges.

• Partitioning is commonly used in distributed systems for better data organization and query performance.

• Bucketing is o...read more
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50 MCQ for python SQL

Q1. What is the difference between supervised and unsupervised learning?
Ans. 
Supervised learning uses labeled data to train the model, while unsupervised learning uses unlabeled data.
• Supervised learning requires a target variable to be predicted, while unsupervised learning does not.

• In supervised learning, the model learns from labeled training data, whereas in unsupervised learning, the model finds patterns in unlabeled data.

• Examples of supervised learning include regression and classification...read more
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Q2. Elaborate concepts of Object Oriented Programming in Python.
Ans. 
Object Oriented Programming in Python focuses on creating classes and objects to organize code and data.
• Python supports classes, objects, inheritance, polymorphism, and encapsulation.

• Classes are blueprints for creating objects, which are instances of classes.

• Inheritance allows a class to inherit attributes and methods from another class.

• Polymorphism enables objects to be treated as instances of their parent class.

• Encap...read more
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Q3. How to find delta between two tables in SQL?
Ans. 
To find delta between two tables in SQL, use the EXCEPT or MINUS operator.
• Use the EXCEPT operator in SQL to return rows from the first table that do not exist in the second table.

• Use the MINUS operator in SQL to return distinct rows from the first table that do not exist in the second table.
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Q4. Illustrate exception handling in python.
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Exception handling in Python allows for graceful handling of errors and preventing program crashes.
• Use try-except blocks to catch and handle exceptions.

• Multiple except blocks can be used to handle different types of exceptions.

• Finally block can be used to execute code regardless of whether an exception was raised or not.

• Custom exceptions can be defined by creating a new class that inherits from the built-in Exception c
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Q5. Give an example of decorators in Python?
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Decorators in Python are functions that modify the behavior of other functions.
• Decorators are defined using the @decorator_name syntax before the function definition.

• They can be used for logging, timing, authentication, etc.

• Example: @staticmethod decorator in Python makes a method static.
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Q1. Self Introduction
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Q2. About the current project
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Q3. Different types of joins in SQL
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Different types of joins in SQL include inner join, left join, right join, and full outer join.
• Inner join: Returns rows when there is a 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 table.

• Full outer join: Returns rows when there is a match in either table.
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Q4. Questions related to Cloud
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Q1. Roles and responsibilities in current project
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Q2. Optimizations used in present project
Ans. 
Various optimizations such as indexing, caching, and parallel processing were used in the project.
• Implemented indexing on frequently queried columns to improve query performance

• Utilized caching mechanisms to store frequently accessed data and reduce database load

• Implemented parallel processing to speed up data processing tasks

• Optimized algorithms and data structures for efficient data retrieval and manipulation
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Q3. How did you overcome out of memory issues
Ans. 
I optimized code, increased memory allocation, used efficient data structures, and implemented data partitioning.
• Optimized code by identifying and fixing memory leaks

• Increased memory allocation for the application

• Used efficient data structures like arrays, hashmaps, and trees

• Implemented data partitioning to distribute data across multiple nodes
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