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

Kensu gathers metadata from Azure Data Factory pipeline runs and datasets used in the pipelines, feeding valuable insights into data lineage, schema changes, and performance metrics.

This is done by visualizing the Azure Data Factory pipelines' full column-level with source-to-target traceability through different data transformations at the most detailed level.

This is done by visualizing the Azure Data Factory pipelines’ full column-level with source-to-target traceability through different data transformations at the most detailed level. This thorough ...

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 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.

Data teams are then able to observe data within their Azure Data Factory pipelines to receive valuable insights, as well as manage tickets within Azure Devops and alerts in Microsoft Teams.