![]() ![]() ![]() On other hand, it helps you to control the access each environment for only specific people. Having multiple ADF instances does not cost you anything extra. First thing to consider in design is not to share an ADF instance with multiple projects or multiple environments. A proper resource design will decide how secure your data in cloud. Figure: A secured way of implementing Azure Data Factory Multiple ADF Instancesĭesigning Azure resource groups and Azure resources is very important when it comes to an ADF implementation. Nevertheless, I will add Microsoft documentation related to each section so that you can read more about it. One thing that remember that in this post I will not go in details for any of these features. Your implementation you might or might not be able to use all the component I have listed down in this post based on your organizational requirements. In below diagram I’m trying to place my way of securing organizational data when Azure Data Factory is used in a data integration solution. In this post, I’m trying to cover how we can configure Azure Data Factory in a secured way to protect the data it processes. Data is the most important assert of an organization! Safeguarding organizational data has paramount importance for any organization and companies are spending millions of dollars for that. ![]()
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