Cognizant AWS Data Engineer Interview Questions, Process, and Tips

AWS offers the most comprehensive and flexible cloud platform with unmatched scalability, security, and reliability.

• AWS has the largest and most mature cloud ecosystem with a wide range of services and tools

• AWS provides unmatched scalability and flexibility to meet the needs of any organization

• AWS has a strong focus on security and compliance, with a wide range of certifications and compliance programs

• AWS offers high a...read more

AWS Glue is a fully managed ETL service that makes it easy to move data between data stores.

• AWS Glue crawls your data sources and constructs a data catalog using metadata.

• It then generates ETL code to transform and move data between data stores.

• AWS Glue supports various data sources like Amazon S3, JDBC, Amazon RDS, etc.

• It also provides a serverless environment to run your ETL jobs.

• AWS Glue integrates with other AWS se

AWS Kinesis is a managed service that enables real-time processing of streaming data at scale.

• Kinesis can handle large amounts of data in real-time from various sources such as IoT devices, social media, and logs.

• It allows data to be processed in real-time using AWS Lambda, Kinesis Analytics, or Kinesis Data Firehose.

• Kinesis can be used for various use cases such as real-time analytics, machine learning, and fraud dete...read more

Python provides built-in libraries to parse JSON messages easily.

• Use the json module to load and parse JSON data

• Access the data using keys and indexes

• Use loops to iterate through JSON arrays

• Use dumps() method to convert Python objects to JSON format

To print current time in Python, use the datetime module.

• Import the datetime module

• Use the now() method to get the current date and time

• Use the strftime() method to format the time as a string

I have used various libraries in my project such as Pandas, NumPy, Matplotlib, etc. and I import them using the import statement.

• I have used Pandas for data manipulation and analysis

• I have used NumPy for numerical operations

• I have used Matplotlib for data visualization

• I import them using the import statement followed by the library name

Types of compression include lossless and lossy compression.

• Lossless compression reduces file size without losing any data.

• Lossy compression reduces file size by removing some data, resulting in lower quality.

• Examples of lossless compression include ZIP, GZIP, and PNG.

• Examples of lossy compression include JPEG and MP3.