Dynamic Data Masking for Batch Processing

Correct Answers: B and C

Azure Synapse offers Dynamic Data Masking.

HDInsight (with Hive and Hive LLAP) provides the dynamic data masking facility.

Azure Databricks does not offer dynamic data masking facility.

Option A is incorrect.

Azure Data Lake Analytics does not offer dynamic data masking.

Option B is correct.

Azure Synapse offers dynamic data masking.

Option C is correct.

HDInsight( with Hive and Hive LLAP) provides the dynamic data masking facility.

Option D is incorrect.

Azure Databricks does not offer dynamic data masking.

Option E is incorrect.

Azure Synapse and HDInsight are the correct answers.

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Dynamic data masking is a feature that enables the hiding of sensitive data from users who do not have access rights to view it. It is useful in scenarios where data is shared with multiple users, but certain parts of the data need to be protected. Among the listed batch processing technologies, only Azure Synapse and Azure Data Factory provide the facility of dynamic data masking.

Azure Synapse is a fully managed analytics service that enables users to work with big data and data warehousing. It integrates with Azure Active Directory (AAD) for authentication and authorization, and allows users to define access control policies for their data. With Azure Synapse, users can define dynamic data masking policies to protect sensitive data from unauthorized access. Dynamic data masking policies can be defined on tables or views, and can be applied to columns based on user roles or permissions. Once applied, dynamic data masking hides the sensitive data from users who do not have access rights to view it.

Azure Data Factory is a cloud-based data integration service that allows users to create, schedule, and manage data pipelines. It provides a visual interface for designing data pipelines and supports a variety of data sources and destinations. With Azure Data Factory, users can define dynamic data masking policies to protect sensitive data as it moves through the pipeline. Dynamic data masking policies can be defined on data transformations, and can be applied to columns based on user roles or permissions. Once applied, dynamic data masking masks the sensitive data from users who do not have access rights to view it.

Azure Data Lake Analytics, HDInsight, and Azure Databricks are batch processing technologies that are used for processing big data. However, they do not provide the facility of dynamic data masking out-of-the-box. These technologies can be used in conjunction with other Azure services, such as Azure Synapse or Azure Data Factory, to implement dynamic data masking.