Gaurav Malhotra discusses how you can operationalize Jars and Python scripts running on Azure Databricks as an activity step in a Data Factory pipeline.

For more information:

Just when you thought Azure Databricks couldn’t get any better, watch this video where Yatharth Gupta, Principal Program Manager for Azure Databricks, talks about the newly introduced integration with R Studio.

For data scientists looking at scaling out R-based computing to big data, Azure Databricks provides the best way scale out their R models with Spark, that is easy to setup and integrates with the most popular R tools and frameworks. Data scientists can use Azure Databricks and R Studio to easily create analytics models, quickly access and prepare high quality data sets, and automatically run R workloads at unprecedented scale.

Today’s business managers depend heavily on reliable data integration systems that run complex ETL/ELT workflows (extract, transform/load and load/transform data).

Gaurav Malhotra joins Scott Hanselman to discuss how you can iteratively build, debug, deploy, and monitor your data integration workflows (including analytics workloads in Azure Databricks) using Azure Data Factory pipelines.

For more information: