Ingest, prepare, and transform using Azure Databricks and Data Factory

Today’s business managers depend heavily on reliable data integration systems that run complex ETL/ELT workflows (extract, transform/load and load/transform data). These workflows allow businesses to ingest data in various forms and shapes from different on-prem/cloud data sources; transform/shape the data and gain actionable insights into data to make important business decisions.

 

With the https://azure.microsoft.com/en-us/blog/azure-databricks-industry-leading-analytics-platform-powered-by-apache-spark/ of Azure Databricks comes support for doing ETL/ELT with https://azure.microsoft.com/en-us/services/data-factory. 

 

 

Read more about it in the https://azure.microsoft.com/en-us/blog/operationalize-azure-databricks-notebooks-using-data-factory/.