This post has been republished via RSS; it originally appeared at: MSDN Blogs.
Welcome to another Azure Content Spotlight! These articles are used to highlight items in Azure that could be more visible to the Azure community.
This week our content spotlight is about Azure Data Factory. From my experience as a Cloud Architect, moving, storing and transforming data in Azure is one of the biggest topics at this moment for organizations. Microsoft is releasing a lot features around data solutions at the moment, and one of these features is Azure Data Factory. Data is mostly stored in relational, non-relational, and other storage systems. But raw data doesn't have the proper context or meaning to provide meaningful insights to analysts, data scientists, or business decision makers.
Azure Data Factory provides a service that can orchestrate processes to refine these enormous stores of raw data into actionable business insights. It is build for complex hybrid extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects.
To get started with Azure Data Factory, you can refer to the following video's and articles:
- Azure Data Factory Documentation
- Visually build pipelines for Azure Data Factory V2
- Quickly build data integration pipelines using templates in Azure Data Factory
- Code-free data transformation at scale using Azure Data Factory
- Enhanced productivity using Azure Data Factory visual tools
- Run Azure Functions from Azure Data Factory pipelines
Cheers, Sjoukje