![]() ![]() We are focusing here on governance the code of ADF and how to deploy it from a code repository to the service, hence mentioning the integration with GIT was on purpose. Today, ADF is a pretty mature product and offers a lot of useful features, including Global Parameters, Mapping Data Flow, GIT integration and much more. At the time, the whole ADFv2 was in preview and the product was (and still is) fastly develop by MS Team (kudos to Mark Kromer and his team). This post is completely focused on the topic of deployment (aka publish) Azure Data Factory from code to the instance (service) in the cloud. ![]() This post is NOT about what Azure Data Factory is, neither how to use, build and manage pipelines, datasets, linked services and other objects in ADF. Two methods of deployment Azure Data FactoryĪzure Data Factory is a fantastic tool which allows you to orchestrate ETL/ELT processes at scale. ![]()
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