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The new Mapping Data Flows feature in Azure Data Factory allows Data Engineers to visually design, debug, manage, and operationalize data transformations at scale in the cloud.
You can use Azure Data Factory to operationalize your Azure HDInsight Spark and Hadoop workloads against HDInsight clusters with Enterprise Security Package that are joined to an Active Directory domain.
You can monitor the health of your data factory pipelines by using the Azure Data Factory Analytics service pack available in the Azure Marketplace.
Azure Data Factory visual tools are now integrated with GitHub, so you can collaborate with other developers, do source control, and version your data factory assets.
You can share an existing self-hosted IR with multiple data factories. This functionality helps you reuse an existing self-hosted IR infrastructure in another data factory while building a hybrid data-integration pipeline.
You can now parameterize a linked service in Azure Data Factory.
Azure Data Factory now generates linked Resource Manager templates for CI/CD by breaking the factory payload into several files to help users with Resource Manager template limits.
Azure Functions is now integrated with Azure Data Factory, so you can run an Azure function as a step in your data factory pipelines.
Organizations can now improve operational productivity by creating alerts on data integration events (success/failure) and proactively monitor with Azure Data Factory.
Azure Data Factory pipelines now include tagging support and enhanced monitoring capabilities, including dashboards and improved debugging support.
You can visually design, build, and manage data transformation processes without learning Spark or having a deep understanding of the distributed infrastructure.
Data Engineers or data developers can now use templates in Azure Data Factory to quickly build data integration pipelines, improve developer productivity, and reduce development time for repeat processes.
Azure Data Factory now supports service principal and MSI authentication for Azure Data Lake Storage Gen2 connectors.
Azure Data Factory added a new capability that enables secured, governed, and scalable access of Office 365 data in Azure.
You can now copy data from Oracle Service Cloud and Google AdWords into Azure by using Azure Data Factory.
Azure Data Factory now supports service principal and MSI authentication for Azure Blob connectors.
Azure Data Factory now supports writing to Azure Cosmos DB by using UPSERT in addition to INSERT.
The Data Factory Lookup activity supports retrieving a dataset from any of the ADF-supported data sources.
The Data Factory GetMetadata activity supports more sources and metadata options.
New connectors are available in Azure Data Factory: Salesforce Marketing Cloud and Oracle Responsys.