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. Data teams ...

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.

Ignite 2019: Microsoft has revved its Azure SQL Data Warehouse, re-branding it Synapse Analytics, and integrating Apache Spark, Azure Data Lake Storage and Azure Data Factory, with a unified Web ...

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 ...

It integrates with Azure DataOps, and supports the use of parameters, triggers, and complex orchestrations of data pipelines involving custom-state passing and looping containers.

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.