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.

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

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.

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.

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.

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.

If you want to make good data-driven decisions, it’s critical for your data to be as accurate as possible. But ensuring the accuracy of data can be a difficult task in large enterprise environments ...

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 ...