Microsoft Azure Data Engineer Associate - DP-203
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In a scenario where you need to implement data security for a data pipeline that involves data transformation and analysis using Azure Databricks, describe the steps you would take to ensure that the data is secure and compliant with data protection regulations.
A
Use Azure Databricks' built-in libraries for data transformation and analysis, and implement Azure Data Lake Storage (ADLS) with encryption at rest and Azure Active Directory (AAD) for authentication and authorization.
B
Configure Azure Databricks to use Azure Key Vault for storing and managing encryption keys, and apply column-level encryption to sensitive data during data transformation and analysis.
C
Utilize Azure Data Factory to orchestrate the data pipeline and implement Azure Policy to enforce data security policies for data governance and compliance.
D
Implement Azure Databricks for data transformation and analysis, and use Azure Information Protection (AIP) to classify and protect sensitive data throughout the data pipeline.