What is the primary role of AWS Glue Workflows?

What is the primary role of AWS Glue Workflows?

• A. To analyze big data in real-time
• B. To manage ETL jobs and data processing workflows systematically
• C. To store unstructured data securely
• D. To monitor cloud resource costs

Answer: (B)

The primary role of AWS Glue Workflows is to manage ETL (Extract, Transform, Load) jobs and data processing workflows systematically. AWS Glue Workflows provide a visual interface that allows users to design and manage complex data workflows, making it easier to orchestrate the various stages of data processing. By utilizing Glue Workflows, users can define a series of tasks that need to be executed in a specific order, enabling the automation of data integration processes. This feature is crucial for data analytics, as it ensures that data is processed efficiently and in the correct sequence, which can involve cleaning, transforming, and loading data into data lakes or warehouses. Other options do not align with the main purpose of AWS Glue Workflows. While analyzing big data in real-time is an important aspect of data analytics, it is not the primary function of AWS Glue, which focuses on ETL and data preparation. Storing unstructured data securely pertains to storage solutions like Amazon S3 rather than workflow management. Monitoring cloud resource costs involves tools that track usage and expenses, which again falls outside the scope of Glue Workflows.

The primary role of AWS Glue Workflows is to manage ETL (Extract, Transform, Load) jobs and data processing workflows systematically. AWS Glue Workflows provide a visual interface that allows users to design and manage complex data workflows, making it easier to orchestrate the various stages of data processing.

By utilizing Glue Workflows, users can define a series of tasks that need to be executed in a specific order, enabling the automation of data integration processes. This feature is crucial for data analytics, as it ensures that data is processed efficiently and in the correct sequence, which can involve cleaning, transforming, and loading data into data lakes or warehouses.

Other options do not align with the main purpose of AWS Glue Workflows. While analyzing big data in real-time is an important aspect of data analytics, it is not the primary function of AWS Glue, which focuses on ETL and data preparation. Storing unstructured data securely pertains to storage solutions like Amazon S3 rather than workflow management. Monitoring cloud resource costs involves tools that track usage and expenses, which again falls outside the scope of Glue Workflows.