What happens when you combine a cloud orchestration service with a Spark cluster?! The answer is a feature rich, graphical, scalable data flow environment to rival any ETL tech we’ve previously had available in Azure. In this session we will look at Azure Data Factory and how it integrates with Azure Databricks to produce a powerful abstraction over the Apache Spark analytics ecosystem in the form of Mapping and Wrangling Data Flows. If you have ever transformed datasets using SQL Server Integration Services (SSIS) packages or via Power BI’s Power Query tool this is the session for you. Now we can transform data in Azure using our favourite interfaces but with the support of Azure Databricks doing the heavy lifting. In this session you will get a quick introduction to Azure Data Factory before we go deeper into the services new Mapping and Wrangling Data Flows features. Start using cloud native technology and scale out compute within a convenient, easy to use Data Factory rich graphical interface.

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