What do you understand by database, Data Warehousing, data lake, and datamarts? What are the benefits of the use of ELT over ETL? What's your experience with AWS Redshift? What's your experience with the cloud watch and how do you debug?

Question

Accepted Answer

A database is a structured collection of data, Data Warehousing is the process of collecting and managing data from various sources, data lake is a storage repository that holds a vast amount of raw data, and datamarts are subsets of data warehouses.

Database is a structured collection of data organized for easy access, retrieval, and management.
Data Warehousing involves collecting and managing data from various sources to provide meaningful insights for decision-making.
Data lake is a storage repository that holds a vast amount of raw data in its native format until it's needed.
Datamarts are subsets of data warehouses that focus on specific business lines or functions.
ELT (Extract, Load, Transform) is beneficial over ETL (Extract, Transform, Load) as it allows for processing data directly in the target system, reducing data movement and improving performance.
Experience with AWS Redshift involves working with Amazon's cloud-based data warehousing service for large-scale data analytics.
Experience with CloudWatch includes monitoring and managing AWS resources, setting alarms, and viewing logs for debugging purposes.

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What do you understand by database, Data Warehousing, data lake, and datamarts? What are the benefits of the use of ELT over ETL? What's your experience with AWS Redshift? What's your experience with the cloud watch and how do you debug?

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