Hybrid data integration at scale, made easy
- Create, schedule, and manage data pipelines
- Fully managed ETL/ELT service in the cloud
- Run your SQL Server Integration Service packages directly in the cloud
- Accelerate your data integration with multiple native data connectors
- Modernize your data warehouse with big data integration
- Orchestrate your data integration workflows wherever your data lives
Customers using Azure Data Factory
Azure Data Factory is a hybrid data integration service that allows you to create, schedule and orchestrate your ETL/ELT workflows at scale wherever your data lives, in cloud or self-hosted network. Meet your security and compliance needs while taking advantage of ADF’s extensive capabilities.
Ingest and prepare
Use Azure Data Factory, a globally-deployed data movement service in the cloud, to ingest data from multiple on-premises and cloud sources. Orchestrate your data integration workflows wherever your data lives, accelerate your data integration with multiple data connectors, and prepare and partition your data as you ingest it or apply pre-processing steps.
Transform and analyze
Schedule and manage your data transformation and analysis process. Choose from a wide range of processing services, and put them into managed data pipelines to use the best tool for the job. For example, add a Hadoop processing step for big or semi-structured data, a stored procedure invocation step for structured data, a machine-learning step for analytics, or insert your own custom code as a processing step in any pipeline.
Publish and consume
Use data pipelines to transform raw data into finished or shaped data that's ready for consumption by BI tools or applications. Get your valuable data where it needs to go for consumption by your on-premises or cloud applications and services.
Monitor and manage
Monitor and manage your network of data pipelines at a glance to identify issues and take action. Easily understand when data arrives, where it comes from, and how and when it’s ready for processing. Set up alerts to monitor your overall Data Factory service health. Save time and money by automating your data pipelines with on-demand cloud resource management.
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