AWS Data Pipeline is a web service that you can use to automate the movement and transformation of data. With AWS Data Pipeline, you can define data-driven workflows, so that tasks can be dependent on the successful completion of previous tasks.
A data pipeline includes various technologies to verify, summarize, and find patterns in data to inform business decisions. Well-organized data pipelines support various big data projects, such as data visualizations, exploratory data analyses, and machine learning tasks.
Describes all the API operations for AWS Data Pipeline in detail. Also provides sample requests, responses, and errors for the supported web services protocols.
To use AWS Data Pipeline, you create a pipeline definition that specifies the business logic for your data processing. A typical pipeline definition consists of activities that define the work to perform, and data nodes that define the location and type of input and output data.
What is AWS Data Pipeline? AWS Data Pipeline automates data movement and transformation, defining data-driven workflows to schedule and run tasks like copying logs to Amazon S3 and launching Amazon EMR clusters.
AWS Data Pipeline automates data movement and transformation, defining data-driven workflows to schedule and run tasks like copying logs to Amazon S3 and launching Amazon EMR clusters.
What is AWS Data Pipeline? AWS Data Pipeline automates data movement and transformation, defining data-driven workflows to schedule and run tasks like copying logs to Amazon S3 and launching Amazon EMR clusters.
As a managed ETL (Extract-Transform-Load) service, AWS Data Pipeline is designed to allow you to define data movement and transformations across various AWS services, as well as for on-premises resources.
AWS Data Pipeline implements two main sets of functionality. Use the first set to create a pipeline and define data sources, schedules, dependencies, and the transforms to be performed on the data. Use the second set in your task runner application to receive the next task ready for processing.
