Task Execution and Workflow Automation
Question
Azure Data Factory (ADF) is made up of 4 core components.
These components work in collaboration to provide a platform that allows composing data-driven workflows with steps to move & transform data.
Which component can be described by: “It is created to perform a specific task by composing the different activities in the task in a single workflow.
This can be scheduled to execute, or a trigger can be defined that determines when an execution needs to be kicked off.”
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D. E.Correct Answer: B
An Azure subscription can consist of 1 or more Azure Data Factory (ADF) instances.
ADF is composed of 4 core components i.e Dataset, Activity, pipeline and Linked Services.
These components work in collaboration to provide a platform where data-driven workflows can be composed with steps to move & transform data.
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Option A is incorrect.
Activity is a specific action executed on the data in a pipeline like the ingestion or transformation of the data.
Each pipeline may consist of 1 or more activities in it.
Option B is correct.
The given description is for Pipeline.
Option C is incorrect.
This is the data collected by users which are utilized as input for the ETL process.
Datasets can be in various formats like CSV, JSON, text or ORC format.
Option D is incorrect.
Linked Service is not the right answer.
Option E is incorrect.
The given description is for Pipeline.
To know more about Azure Data Factory, please visit the below-given link:
The component that can be described as follows is the Pipeline in Azure Data Factory (ADF).
A pipeline is a logical grouping of activities that together perform a specific task or business operation. Activities within a pipeline can include a wide range of actions, such as copying data from a source system, transforming the data, and storing the transformed data in a target system.
A pipeline provides a platform for composing data-driven workflows by arranging and linking together activities to achieve a specific data integration goal. Pipelines can be scheduled to run on a regular basis or can be triggered to run when specific events occur, such as the arrival of new data.
In summary, while each of the components in Azure Data Factory (ADF) has a specific role to play, the Pipeline component is responsible for composing activities into a logical workflow to perform a specific task, which can be scheduled to execute or triggered based on specific events.