Mapping Data Flows allows users to build data pipelines in an accessible visual environment, without having to go through the additional hassle of infrastructure management.

In a recent blog post, Microsoft announced the general availability (GA) of their serverless, code-free Extract-Transform-Load (ETL) capability inside of Azure Data Factory called Mapping Data Flows.

In addition, the company revealed that its Azure Data Factory Mapping Data Flow services are now available in preview for users to experiment with using their Azure workloads.

We also announced the preview of Azure Data Factory Mapping Data Flow. With these updates, Azure continues to be the best cloud for analytics with unmatched price-performance and security.

Microsoft has announced that both Gen2 of Data Lake Storage and Azure Data Explorer are now generally available. Furthermore, a preview of Mapping Data Flow in Data Factory is also live.

In response to developer feedback, Microsoft is taking a page from the growing visual, low-code development approach to simplify Big Data analytics in the cloud with Azure Data Factory.

At Build 2019, Microsoft rolled out a slew of IoT, mapping, databases, storage, and analytics updates across Azure services.

Locking down AI pipelines in Azure? A zero-trust, metadata-driven setup makes it secure, scalable and actually team-friendly.

Whether you're shifting ETL workloads to the cloud or visually building data transformation pipelines, version 2 of Azure Data Factory lets you leverage conventional and open source technologies ...